Anyone in business spends roughly 40% of their professional life trying to move people from Point A to Point B, selling visions to candidates, budgets to the CFO, change to a skeptical workforce...

In an era where AI can automate your code, draft your emails, synthesize your data, and make videos of singing cats, these human-centric influence skills are the only truly resilient assets we have left.

However, the vast majority of business leaders never spent a single hour studying the actual mechanics of influence, so they rely on “gut feel” and “charisma”... fragile tools that fail the moment the stakes get high.

I have spent two decades in management consulting across the US, Europe, Asia, and Australia distilling these 63 principles: your field manual for the 40% of your job you were never trained for... and your only biological advantage in the age of Artificial Intelligence.

In this article, I am going to share with you these gold nuggets.

Read them, study them, understand them, re-read them, practice them, stick to what works (and share this post with a friend!!). If you do that, you will be unrecognizable in 1 year.

Let’s start!

I. The foundational mindset: sales as leadership

1) Sales is the engine of strategic execution

Strategy is easy; execution is hard. The space between a slide and a finished product is filled with people who need to be convinced: if you cannot persuade your team to change their habits or your board to release capital, then consider your “strategy” as an expensive hallucination.

2) The 40% reality check

Data shows business leaders spend roughly 40% of their time “non-sales selling”, ie, persuading, influencing, moving others, etc. If you spend nearly half your week doing something you have not studied, try to tell me you are not an amateur at the most frequent part of your job?

3) The “used car” fallacy

The “used-car salesperson” stereotype is about extraction: taking value away from someone. Modern leadership sales is instead about alignment: creating value where none existed. To sell properly, think about how the other person is going to win off what you sold.

4) Meritocracy is BS

If you follow me, you already know the belief that “the best work wins” is a comforting lie. The corporate graveyard is full of technically superior products that nobody bought because their founders weren’t able to sell them. High-quality work requires a champion who can navigate the politics of buy-in: without a “sales” effort, you will squander your great work.

5) Being technically great is definitely not enough

An elegant piece of code or a perfect financial model is just an input, where the output is organizational change. If you don’t sell the “why” to the people who have to live with the “how,” they will subconsciously sabotage your greatness to protect their own comfort.

6) Preparation beats charisma

Over time I learned that charisma is a fragile asset because it fluctuates with your mood. Preparation is a rock: knowing your client’s quarterly goals, their recent failures, their boss’ pressures, the next half-year strategy, etc allows you to speak with an authority that “charm” alone can never replicate.

7) Influence is a learnable structure

Stop hiding behind the excuse that you are not a “natural”: it is a trite one. Understand that influence is a sequence of steps: research, diagnosis, framing, and co-design. It is a hard skill, much like financial analysis, and it yields to practice and protocol.

8) Sell with intent

Never walk into a meeting just to “catch up.” Every interaction should have a measurable objective (eg, learning something new) or a strategic objective (eg, moving a decision forward).

Sell with intent rather than “socializing” on the company’s dime.

9) Ethics are your armor

As I explain in detail in my #1 Amazon best-seller Beyond Slides, in a tight professional network your reputation travels faster than your resume. Ethical persuasion is the most pragmatic thing you can do. If you trick someone into a “yes” today, you lose the ability to ask for anything for the next 10 years. Be careful!

II. Trust is an equation

10) The formula

Because I am an engineer, I like formulas for everything. In their popular book The Trusted Advisor, David Maister, Charles H. Green and Robert M. Galford show that trust is a calculation:

Trust is computable. If the result is low, you can usually point to exactly which variable you are failing on.

11) Credibility is your entry fee

This is your “right to speak”, built on domain expertise and the quality of your insights. Bear in mind that, if you have not done the work to understand the industry or the problem or both, no amount of “sales technique” will save you!

12) Reliability is the boring superpower

In my definition, reliability is the consistent absence of surprise. If you promise a follow-up by noon and deliver it at 11:55am, you are slowly depositing trust points which, over time, reduce the perceived risk of saying “yes” to your big ideas. The opposite is also true...

13) Intimacy creates safety

Intimacy in a professional sense means “the ability to talk about what actually matters.” You need to create an environment with your clients where they can say, “I am worried this project will make me look bad to my boss” without fearing it will be used against them.

14) Self-orientation is deadly

This is the denominator of the trust equation above. If your “self-orientation” is high (ie, you clearly care more about your promotion, your quota, your ego, your ideas, etc than the other person’s problem) the trust score goes to zero, no matter how smart or reliable you are.

15) Check your Ego at the door

To influence another person you have to make that other person feel like the hero of the story. If you are too busy trying to be the smartest person in the room, you are signaling high self-orientation which actively destroys your own influence.

III. It is all measurable

16) Stop the pitch

A pitch is performative. A pitch demands a grade. When you pitch, the other person instinctively moves into “judge” mode, and continuously looks for flaws. A pitch creates an adversarial dynamic from the very first sentence. Hence, stop the pitch.

17) Open with what hurts

I have never seen a doctor bursting into the room shouting about a new miraculous drug. Normally, they come near you and ask you where it hurts. You should learn from that: don’t offer a solution until you have performed a thorough “biopsy” of your client’s current situation.

18) Avoid “performance mode”

When you start “selling,” your voice changes, your posture shifts, and you start looking for approval. This whole demeanor triggers the buyer’s flight or fight response. Stay in “consultant mode”: calm, curious and objective.

19) Lower the defenses

A diagnostic/measurement approach makes your client feel “seen”. Naturally, when people feel understood, their biological defenses tend to drop. They stop looking for reasons to say “no” and they become more inclined to look for ways to collaborate.

20) Measure by outcomes

Amateur salespeople celebrate the signature to their contracts, but long-term, real leaders celebrate the impact they manage to create. If the project fails 6 months after the “sale”, you did not succeed. And you did not succeed simply because you have failed (which you did, by the way) but more because you have just created a future detractor.

21) The organic reference

When you solve a problem through diagnosis, the client becomes your best salesperson! They will all over spread the idea that you didn’t simply sell them a tool but that you understood their business and fixed it. That is how you build a career.

IV. Stakeholder management: mapping the invisible

22) The organization is a web.

Business decisions are rarely made by one person in a vacuum. They are the result of a complex, often invisible web of internal politics, debts, history, compromises, past agreements, and fears. Your job is to map that web before you try to pull on any of the strings.

23) Find the hidden power

Counterintuitively, title does not always equal influence. Often, the most important person to “sell” is the long-tenured middle-manager or the executive assistant (!) who has the ear of the General Manager. Ignore them at your peril.

24) Informal authority rules

In every company, there are people who everyone goes to for “the real story.” If these informal leaders have not been sold on your idea, they will kill it with a single skeptical comment in the hallway or a joke that isn’t a joke, and you will suffer the consequences.

25) The peer sale is the hardest

Generally speaking, your peers are your competitors for resources and attention. To get them to support you, you must find the “WIIFM” (What’s In It For Me). If your project doesn’t make their life easier, or doesn’t make them look good, or doesn’t make them money, why would they help you?

26) Consensus first, ask second

The big meeting should never be the place where people hear your idea for the first time. The meeting is just the public confirmation of a dozen private “yeses” you have already secured.
Great work rarely gets sold in the boardroom. It gets seeded in the corridor, in casual chats, in the 10 minutes before the meeting starts. That’s when the real pitch begins.

27) Multi-thread

If you only have one champion in an organization, you are one resignation away from total failure: how do you people don’t get that? This must be the #1 mistake in B2B sales. Build relationships at multiple levels: above, below, and beside your main contact. Create more than 1 champions.

28) Personal success metrics

Every stakeholder is motivated by something personal: maybe they want to work fewer hours, maybe they want a specific title, maybe they want to advance their financial position, maybe they want the glory of high achievement. If you can align your project with their personal ambition, they will fight for you.

29) Build the well before you are thirsty

If the first time a client hears from you is when you need a budget approval, you have already lost, my friend. You have to work on building those relationships during the moments when everything is going well; don’t wait for the moments of crisis.

V. Discovery: the science and art of listening

30) The 70/30 rule

About 20 years ago, I had a Scottish boss who told me this sentence for the first time: “You have two ears and one mouth for a reason”. If you are talking, you are only repeating what you already know. If you are listening, you are gathering the intelligence you need to win.

31) Curiosity is a weapon

Genuine curiosity is disarming: when you ask deep, probing questions (your consultative line of questioning) about how a business works, you demonstrate that you care enough to get the root cause right without stopping at the symptoms.

32) The power of open-ended questions

Questions that start with “How” or “What” force the other person to think and reveal their logic. “Do you like this?” is a dead end, why would you let your client talk less when you can have them talk more? For example, “How would this impact your team’s workload?” is a gold mine. Use that category of questions.

Also, check my viral article on Consulting Intel (my popular newsletter):

33) The 3-second silence

Human beings hate silence. When a stakeholder finishes an answer, wait 3 seconds. In that vacuum, they will almost always add a “but...” or an “actually...” or something else that will give you more information. That contains additional nuance to a truth they were hesitant to share.

34) Listen for “no-shows”

OK, careful on this one... You must pay attention to what is conspicuously missing. If a manager talks about everything except their team’s morale, the team’s morale is likely the problem. That silence is louder than the words they spoke.

35) Symptoms vs. root causes

“We need more leads” is a symptom. “Our sales team doesn’t know how to close” is a root cause. If you only treat the symptom and never investigate the root cause (a bit like the NHS in the UK does 🤣), the disease will just move elsewhere. Always ask “Why?” until you hit bedrock (Toyota famously came up with the five whys).

36) Mirroring language

If a client calls their problem a “cluster,” why do you call it an “issue”? Use their specific vocabulary, show that you are an insider who truly understands their specific pain. Leverage a bit of psychology here: mirroring works.

37) Knowledge is the scoreboard

Every meeting is an intelligence-gathering mission for us. If you didn’t walk away with a piece of information you didn’t have before, you lost an opportunity and you squandered the meeting, even if everyone smiled and the coffee tasted good (rare event outside of Italy, anyway).

VI. Sell career safety

38) Features are for amateurs

Do you really believe your client cares about “near real-time data sync”? Your client cares about not having to stay late on a Friday to fix a report and then get pounded by their boss at 8:30am on Monday around why that happened. Do not talk about what the product is, but spend time talking about what the product does for the buyer.

39) Sell emotional safety

High-level executives in large enterprises typically optimize their careers on doing damage-control, are generally risk-averse, and rarely looking for “revolutionary” change. They look for the option that won’t blow up in their face. Your job is to prove that your solution is the safest bet they can take.

40) The 2 executive questions

Every C-suite decision is filtered through 2 fundamental lenses: 1) “Will this make me look good?” and 2) “Will this reduce my risk?”

If your proposal doesn’t answer both, it will be ignored and forgotten, in favor of another proposal that does it.

41) Impact language

Translate everything into the language of the C-suite: risk mitigation, capital efficiency, market share, strategic legacy, etc.

If you can’t describe your project in these terms, you are not ready to present it. I touch on this in Chapter 4 of Beyond Slides (a brief extract below):

42) It is all about the data, until it isn’t

Data is necessary but insufficient. People use data to justify a decision, but they make the decision based on trust and a good story. Use the data as a foundation, but build a strong narrative on top of it.

43) Professional survival

If you lived the corporate world long enough, you must have realized that everyone is scared. If you can show a stakeholder that your project will act as a shield for their career and/or a ladder for their promotion, they will become your most loyal advocate. Show them unequivocally what’s in it for them.

VII. Co-design to your advantage

44) Perfection is a barrier

A perfect, polished presentation feels like a finished product that leaves little room for your client to add their “fingerprints” on it. This makes them feel like a spectator rather than an owner, and may be counterproductive if you need their support later on.

45) The 70% draft

Show up with a proposal that is solid, on the “right direction”, but deliberately incomplete. Caveat the presentation with a “This is my 70% thinking; I need your expertise to get the last 30% right”. This transforms the conversation from a “review” into a “workshop.”

46) Joint ownership

Betty Crocker’s instant cake mixes initially failed because they were too easy. Then, she asked consumers to add fresh eggs themselves (thus increasing the effort involved), and sales skyrocketed. Psychologically, we are biased toward things we help create (the “IKEA effect”): treat your client as your co-author.

47) Redlining is your shortcut

Every time a stakeholder suggests a change and you incorporate it, they are buying in. By the time the final version is ready, they can’t say “no” because they would be saying “no” to their own ideas. Who does that?!

48) Recruit your critics first

If you know someone is going to oppose your idea, go to them first. Openly ask them to coach and mentor you. Request their “expert advice” on how to fix the flaws in your plan. Be strategic about it and don’t get scared: if they help you fix it, they can no longer attack that flaw in public because that would reflect negatively on themselves.

VIII. Reframing resistance and “no”

49) Use every “no” as data

People don’t understand that a “no” is rarely the end of the conversation. An initial negative reaction is just the start of the actual process of diagnosis. It means you have hit a nerve or a boundary. At that point, your job is to calmly and methodically investigate what that boundary is made of.

50) The shield of resistance

Resistance is usually a protective mechanism. When a client tells you something like “it’s too expensive”, what they mean is that they don’t trust the value enough to risk their budget. In that scenario, you should address the fear rather than going straight to price.

51) The magic question

This is as helpful to you as it is helpful to your client: “What would need to be true for this to work?” This single question makes your brain go from “rejection mode” to “problem-solving mode”, and it forces the client to detail out the roadmap to a “yes.”

52) Translate the value

When I first moved to the UK from Italy, people could not understand me and I could not understand them. Same for your clients: if they don’t see the value, you are speaking the wrong dialect. A CFO cares about cash flow, a CMO cares about brand equity. If you use the CMO’s language with the CFO, then why do you complain when you hear a “no”?

53) The cost of “doing nothing”

Sometimes the most powerful thing you can sell is the status quo’s price tag: in a lot of enterprises that’s a very expensive number. Show them exactly how much money or time they are losing every day by not doing the thing. Make the “no” feel more expensive than the “yes”: show with precision the cost of doing nothing.

54) Engagement is the goal

This is not easy to see through, but I came to realize that argument is a form of interest. If someone is challenging your logic, they are likely mentally “trying on” your solution. The only thing you should fear in that context is apathy, the polite “thanks, we will think about it” that goes nowhere.

IX. Tactical execution

55) Recruiting is a high-stakes sale

All the people that you would want in your team have options: you are not special. To hire them, you must do a great job at selling them on a vision of their own future growth. Flip it in your head: it’s not you buying their time but you selling them a purpose.

56) Budgets are won, not granted

When you work in a medium/large enterprise, you learn to look at a budget request as a competitive sale, where you are competing against every other department’s “great idea.” Your job is to frame your request as the highest-yield investment the company can make.

57) Change is a 1-1 game

I am very clear on this: you never change a culture with a series of town halls and all-hands meetings. Actually, changing a culture is so so hard. Your only hope is through dozens of individual “sales” calls with key influencers until you reach a tipping point where the “new way” becomes the “easy way”. Still hard!

58) Be brief

Learn this as early as possible please. Executives have “attention poverty”, and so if you can’t explain the impact of your idea in 120 seconds or less, they will assume you have no clue what you are talking about. Cut the fluff, start with the bottom line, avoid word salads, go straight to the point and be brief.

59) Check the incentives

People are rational actors based on how they are paid. If your proposal makes the company money but costs a manager his bonus, guess what that manager will do? He will kill it.

Always follow the money, it’s easy.

60) Intention beats “smooth”

People can smell a “salesy” person from a mile away. If your genuine intention is to solve their problem, your occasional stumbles or lack of “polish” won’t matter much. Be genuine and truly willing to help: that’s the ultimate lubricant for influence in my experience.

61) You are not Jordan Belfort

Have you watched the Wolf of Wall Street, the movie about Jordan Belfort’s life? Yeah, forget about that stuff. High-pressure tactics are for people who never plan on seeing the buyer again! In leadership, you see the same people every damn day: play the long game please, do not take yourself out of it.

62) Walk through the door together

There will be moments when you won’t see eye to eye with your clients. In those moments, remember what you are there to do. You don’t need to “win” an argument. Your goal is to reach a point where both parties agree that the proposed path is the most logical one. If you had to “beat” them, they will resent you later.

63) The post-sale is the real sale

The moment they say “yes” is when the real work begins. If you disappear after the approval, get called and redirect the problems to someone else, or are suddenly too busy to show up on a day’s notice, you will destroy your Reliability variable for the next time you need something (check Rule #10 above).

I have created a 1-hour presentation around sales essentials for business leaders. I have given the talk to MBA students, consulting professionals, and corporate employees.

If you want to have access to the presentation, I would be very happy to share it with you - I don’t like to hoard!

Leave a comment and I will DM you the link to the presentation.

Many thanks, and all the best in your personal and professional life!

As usual, if you enjoy reading Consulting Intel, please do me a favor: spread the word and share this post.

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👀 Links of interest

A few corners of the internet you may find interesting:

• I swear this is the absolute most entertaining video on the whole of YouTube. Oz Pearlman, the famous “mentalist”, gets ripped apart in this FIVE-HOUR VIDEO (yes, 5 hours!) by an Australian Law student who reveals his entire set of tricks. Super fascinating. I’m sure you’ll find bits and pieces you’ll want to steal here…

• My first book Beyond Slides became a #1 Amazon Best Seller in the USA, UK, Australian and Italy. This is a review from a reader:

  

• Have you looked into the Leaders Toolkit? It is a deck of 52 tools, frameworks and mental models to make you a better leader (use code CONSULTANT10 for 10% off);

• The Consulting Intel private Discord group with 250+ global members is where consultants meet to discuss and support each other (it’s free).

Big podcasts and large publications chase Bezos-level names who talk about strategy from 30,000 feet: it’s inspiring, yes, but useless if tomorrow you are walking into a meeting with your client and a deck to defend…

EDGE, a format by Consulting Intel, is where I sit down with world-class operators, consultants, and investors working between business, tech, and AI… and where I distill what I learn in something you can read in ~7 minutes.

LFG! 🔥

In an era that rewards the “hustle” and the superficial pivot, Andrea Chiarelli stands as a testament to a more traditional, rigorous path.

He is a man who transitioned from the cold, deterministic world of engineering into the nuanced, qualitative waters of high-stakes research consultancy.

The surprising claim at the heart of his philosophy is that structure is not the enemy of creativity but its primary accelerator.

Andrea is a seasoned management consultant based in Nottingham, United Kingdom, where he advises research funders, government departments, universities, and academic publishers.

He holds a PhD in Civil Engineering, an Executive MBA, and an MSC in Nuclear and Energy Engineering, alongside a history as an indie game developer and a passion for coding. He is the quintessential “T-shaped” professional, possessing deep technical mastery alongside an expansive strategic breadth.

Let’s jump into the conversation!

Origin Story

Andrea’s journey began in Alba, Piedmont (he is a fellow Italian) at a STEM-focused high school that refused to sacrifice the humanities for the sake of the lab. While other courses at the school focused mainly on a scientific curriculum, Andrea’s training included extra Latin, philosophy, and literature. This broad education contributed to building a holistic way of thinking, one that valued numbers but understood they were meaningless without a narrative.

As a teenager, he was deeply into Linux and open source software, obsessed with the custom assembly of computers and the granular control of his devices. Naturally, he intended to study Computer Science, but a glance at the curriculum revealed a massive deterrent: “too much mathematics.” He pivoted to Energy Engineering at the Polytechnic of Turin, only to discover that the advanced maths was still there, merely hidden under different module titles…

The defining moment of his early career came during his Master’s degree.

Standing in a lecture hall with 250 other engineering students, Andrea performed a cold, internal audit. He realized that if he followed the standard path, he would be one of hundreds of identical competitors in the local market. His first truly independent strategic decision was to seek an “edge” (and he was too young to know that, decades later, he would be featured on Edge!). He asked his thesis advisor to send him abroad.

He landed at Virginia Tech, in the United States, for six months, completely alone, knowing no one. It was a baptism by fire.

While supporting a doctoral student’s research, he observed the PhD lifestyle: the total intellectual autonomy, the ability to walk in and out of the office at will, and the deep pursuit of a single, fascinating problem.

That’s what led Andrea to applying for a PhD himself, and eventually landed him to Nottingham - where he lives now.

Edge

Andrea’s differentiator is his ability to apply the rigorous structural thinking of an engineer to the qualitative challenges typical of the policy sphere.

Most people view structure as a cage; Andrea views it as a map.

He segments vast, complex problems into their constituent elements, examines the structural connections, and explores them one by one.

This “Edge” was forged through a couple of radical shifts that forced him to abandon his comfort zone repeatedly:

1. During his PhD in Nottingham, Andrea studied “energy harvesting”: extracting heat from sun-baked asphalt. While his experiments ran in the lab, he refused to sit idle. He sat in the office programming in MATLAB and wrote scientific articles on the “physics of stone compaction” and “porosity networks”, topics barely related to his thesis.

2. Nearing the end of his PhD, he realized he had no work experience. He found a part-time role at a nascent boutique consulting firm (then just a founder and two part-timers) specializing in the research and higher education space. He was the firm’s first full-time employee.

His engineering background meant that he had to upskill himself and learn the nuances of qualitative research. Eventually, this expanded his toolkit, building a well-rounded “Mixed Methods” approach.

He recently developed a Claude Code pipeline to automate “thematic coding” (a task that usually consumes hundreds of hours of a consultant’s time), thanks to this blend of quantitative and qualitative expertise. By automating the “tagging,” he frees himself to perform the “synthesis”: the high-level storytelling that clients actually value.

Future

As a strategist who reaches the daily usage limits of Claude Pro multiple times a day, Andrea is an heavy user of generative AI, but with a healthy dose of skepticism.

He views Generative AI as a “three-year-old child”: imaginative, fast, but prone to “telling you about a dream as if it were reality.” This comes from his role: as a consultant who needs to take responsibility for each and every claim, trust is paramount.

Andrea identifies a looming crisis in the talent pipeline, but he argues the impact may depend on the size of the firm.

In the world of large enterprises, the crisis is obscured by layers of bureaucracy and short-term thinking. Andrea notes that large companies rarely think beyond a three-year horizon because the life cycle of a CEO is so brief. For these giants, the immediate financial gains of using AI to replace junior labor are intoxicating. However, they are effectively creating a “leadership vacuum” fifteen years down the line. Without the “grunt work” that develops a professional’s critical eye, these firms will eventually find themselves in a war for senior talent that is increasingly scarce.

In small firms, the threat is existential and immediate. Andrea explains that in a boutique consultancy, talent development is not a HR “perk” but an essential “succession planning” strategy. If a small firm fails to coach its juniors, the current directors can never dream of an “exit.” There is no one to take the reins when they retire.

To address this, Andrea’s firm has taken a deliberate step: they now record time in their accounting systems specifically for (human) coaching. They are consciously choosing to spend “unproductive” hours passing on the critical thinking skills that AI cannot replicate.

Grounding and Legacy

Alongside his senior strategic role, Andrea remains grounded through daily rituals that favor the personal over the professional.

He is a voracious reader, a habit formed as a teenager on the beaches of Italy reading stuff like Ken Follett’s The Pillars of the Earth. Today, he writes on Substack every morning while his four-year-old son eats breakfast.

His life is a cross-cultural tapestry: his wife is Moroccan, and their household is a blend of Mediterranean roots and British customs. This “openness” and willingness to embrace other cultures is something he considers a hidden asset, a willingness to connect with the world emotionally as well as intellectually.

If granted unlimited resources, Andrea would not buy a tropical island or a million-dollar supercar. Instead, he would build a “Technological Sanctuary”: a home outfitted with every possible gadget (a nod to his early tech days), and spend his days volunteering his time to support his local community.

🔹 What you can steal

Andrea’s approach can be articulated in 3 high-level tactical concepts:

1. When you use AI to “save time,” do not just celebrate the efficiency; audit the cost to your own development. Ask yourself: “Am I skipping a task that is a prerequisite for my future growth?” If the work is “donkey work” (e.g., the mindless tagging of data or formatting of tables) automate it without hesitation. However, if the task builds your “critical eye” (e.g., the drafting of a core argument or the initial interpretation of a client’s needs) you must do it manually. Using AI as training wheels is fine for the first block, but to finish the race, you eventually have to take them off and feel the balance for yourself.

2. When a client presents a complex problem, do not seek a holistic solution immediately. Deconstruct it into its constituent parts. Map the specific elements, the channels of influence (like the porosity networks that Andrea was studying) between them, and the blockages that stop progress. By addressing the granular components individually, as well as their connections, you ensure that the final “narrative synthesis” is built on a foundation of structural integrity rather than superficial eloquence. Clarity comes from the assembly of well-understood parts, not from a single stroke of genius.

3. Never allow yourself to be defined by a single job title or a narrow vertical. Andrea’s “Edge” comes from being an engineer and a programmer and a writer and a student of the humanities. In an AI world, technical skills have a shorter half-life than ever before. Your only protection against obsolescence is the “and”: the ability to synthesize insights from disparate fields that an algorithm cannot yet connect with the same level of depth and understanding. Diversity of thought is your primary strategic asset; seek out the “useless” knowledge that your competitors are ignoring.

🔹 Maurizio’s Take

Andrea’s strength is rooted in a conscious refusal to “simply do what the system expects.”

He spent years in the “slower, deliberate” world of academia, which he felt was frustratingly stagnant for his personality, yet he recognizes it as the source of a “critical toolkit” that no weekend seminar could replicate. His brilliance was in realizing when the system was no longer serving him.

He rejected the academic mandate to become a “post-doc nomad”—moving to three different countries to meet the expectations of today’s universities—and instead chose to leverage his elite training in the private sector.

In a world obsessed with “minimum viable products,” Andrea is a proponent of the “Maximum Viable Foundation.” He built a moat out of seemingly disconnected knowledge (stone compaction, Latin, complex calculus, business administration) that allows him to see patterns that others miss.

He proves that the most “efficient” path, specialization, can be dangerous, because it leaves you with no footing when the environment changes.

👀 Where to find more about Andrea

• LinkedIn

• The Art of asking questions newsletter

If you enjoyed today’s conversation and read Consulting Intel, please do me a favor: share this post, spread the edge.

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⚠ Check these links out

• I had the opportunity to try the AI-slide builder Perceptis ahead of their public launch, and I was so impressed! Unlike other apps I have tested before, this one actually builds good slides with a structure, starting from a simple prompt. Try it for 10 minutes and let me know what you think.

• My first book Beyond Slides became a #1 Amazon Best Seller in the USA, UK, Australia and Italy;

• The Leaders Toolkit is a deck of 52 tools, frameworks and mental models to make you a better leader (use code CONSULTANT10 for 10% off);

• The Consulting Intel private Discord group with 250+ global members is where consultants meet to discuss and support each other (it’s free).

We are entering the era of “vibes-based software engineering”, and the more I look into it the more I find it terrifying.

In a recent social media campaign, Cursor went all-in pushing for a simple idea: if the AI can build the feature in 30 seconds and the demo works, why spend 30 minutes reviewing the diff?

The problem they are trying to address is quite visible to software developers: it’s far more time-consuming to review code than it is to write it.

If the AI produced 1,000 lines of code in the blink of an eye, the human reviewer is faced with a choice:

1. Trust the demo, ship the code, and hope there isn’t a memory leak or a security hole;

2. Spend more time meticulously auditing the AI’s output than it would have taken to just write it manually.

Research from early 2025 (LogRocket/CodeRabbit) shows that senior engineers now spend an average of 4.3 minutes reviewing an AI-generated suggestion, compared to just 1.2 minutes for human-written code: because AI doesn’t “understand” your specific architecture, it produces defensive but bloated patterns that are exhausting to audit.

Code generation is 10x faster, but code verification is 3x harder.

According to the Sonar 2026 State of Code Report:

• 61% of developers agree that AI often produces code that “looks correct but is not reliable”;

• 96% of developers admit they do not fully trust that AI-generated code is functionally correct;

• Yet, the volume of code is exploding! GitHub’s Octoverse 2025 reported a 29% surge in merged PRs, while human review capacity remained flat. We are rubber-stamping the collapse of our own systems.

A landmark Randomized Controlled Trial (RCT) by Metr.org (July 2025) found that experienced developers took 19% longer to complete tasks when using AI tools. Those same developers believed they were 20% faster.

What is going on here?!

We are so enamored by the “magic” of the demo that we don’t even notice the hours we spend fixing the subtle hallucinations hidden in the diff?

Now, imagine a bank reviewing a new transaction ledger based on a “demo.”

“Look, the numbers moved from Box A to Box B! It works!” Meanwhile, the underlying logic doesn’t meet compliance and includes zero error handling.

It’s the AI-driven version of Schrödinger’s cat experiment: the code is both working and broken until someone hits it in production.

A 2025 study found that AI-generated code carries a vulnerability rate of ~50%, compared to 15–20% in traditional human-written code. For critical applications, a “demo” as a user test is a no-go in my opinion.

A point I bring up often is that we need better ways to verify, not just to write.

Everyone is focused on the speed of writing software but unless you can also test it rigorously at the same speed, you are not truly improving productivity for high-value code.

I wholeheartedly believe this entire idea of being content with the demo rather than with the diff is an absolute disgrace.

Is “working” enough now? Aren’t we just building a house of cards at 10x speed?

The industry seems stuck in perception: we feel 20% faster, but we are actually 19% slower.

As usual, if you enjoy reading Consulting Intel, please do me a favor: spread the word and share this post.

👋

👀 Links of interest

A few corners of the internet you may find interesting:

• A recent post I published on LinkedIn was quite well received, so I thought I should propose it here as well. As usual, feel free to connect with me on LinkedIn (always great to see you there too!):

  

• I had the opportunity to try the AI-slide builder Perceptis ahead of their public launch, and I was so impressed! Unlike other apps I have tested before, this one actually builds good slides with a structure, starting from a simple prompt. Try it for 10 minutes and let me know what you think.

  

• My first book Beyond Slides became a #1 Amazon Best Seller in the USA, UK, Australian and Italy. This is a message I received the other day from a new reader:

  

• Have you looked into the Leaders Toolkit? It is a deck of 52 tools, frameworks and mental models to make you a better leader (use code CONSULTANT10 for 10% off);

• The Consulting Intel private Discord group with 250+ global members is where consultants meet to discuss and support each other (it’s free).

Big podcasts and large publications chase Bezos-level names who talk about strategy from 30,000 feet: it’s inspiring, yes, but useless if tomorrow you are walking into a meeting with your client and a deck to defend…

EDGE, a format by Consulting Intel, is where I sit down with world-class operators, consultants, and investors working between business, tech, and AI… and where I distill what I learn in something you can read in ~7 minutes.

LFG! 🔥

Most “tech gurus” are obsessed with the shiny and new. Mario Peshev is obsessed with what actually works when the bill comes due. While the world treats AI like a magic wand, Mario treats it like a high-speed assembly line that is currently running out of raw materials.

He believes AI is currently cannibalizing itself. Businesses are optimizing internal processes to save costs, but they aren’t actually creating new wealth: if everyone gets 40% more efficient at the same task, the price of that task simply drops to zero. Mario’s story is a roadmap for how to survive the “race to the bottom” by pivoting from a service provider to a “Value Creator.”

Mario is the CEO of DevriX (enterprise engineering and RevOps) and Growth Shuttle (SME consulting). He is an angel investor in over 25 companies—including Substack, Beehiiv, and Doola—and has clocked over 10,000 hours training engineers at the world’s most elite organizations, from CERN to Saudi Aramco.

Let’s jump into the conversation!

Origin Story

Mario’s career didn’t start in a boardroom; it started in 1999 with a single website and a passion for engineering. For the next two decades, he wore “multiple hats,” maturing alongside the internet. He watched the era of the home PC give way to the era of the Cloud, and the era of social media transform into the era of the “Growth Loop.”

A big shift for Mario came when he realized that being a “great engineer” was no longer a moat. In the mid-2010s, he saw the agency model fracturing: clients didn’t want to buy “code” or “HubSpot workflows” anymore—they wanted to buy revenue.

This led to the transformation of DevriX from a technical shop into a high-level Revenue Operations (RevOps) firm. He stopped speaking the language of “features” and started speaking the language of the CRO.

Edge

Mario’s differentiator is his refusal to get distracted by “trendy” terminology.

Whether people call it “Smarketing,” “The Flywheel,” or “RevOps,” Mario views it all through the lens of Value Creation. His edge lies in the Agentic Layer, using AI not just for chat, but as a systematic infrastructure that connects marketing leads to sales data to customer retention.

Mario made the contrarian move to bring his team fully in-house in Sofia. He recognizes that while digital talent is globally mobile, “desk job” work is becoming a commodity. By maintaining a physical headquarters, he creates a “security moat” for enterprise clients. Data doesn’t leak between fragmented VPNs across dozens of countries; instead, it lives in a controlled environment where peer review and collective “hacking” happen in real-time. This physical proximity transforms “consulting” into a high-security, high-reliability operation that remote-only agencies struggle to match.

Mario is a Vibe Coding practitioner. He uses tools like Cursor and Google’s Anti-gravity to build prototypes in hours that previously cost $80,000 and took months. He recently rebuilt his company’s entire accounting system from scratch because off-the-shelf SaaS tools like Xero couldn’t provide the granular data he needed—specifically, gross profitability per team and real-time bank statement “leakage” analysis. He didn’t wait for a vendor; he built a local, secure SQLite-based software on a Saturday.

Mario’s differentiator is his recognition of physical bottlenecks.

He points out that while you can use AI to plan a construction project 40x faster, you still need a human to lay the bricks, a government official to sign the permit with a “wet signature,” and a supply chain to ship the materials. His edge is knowing exactly where the digital world hits the brick wall of reality.

Future

Mario isn’t buying into the singularity hype just yet. His perspective is rooted in a sobering economic reality: Efficiency is not the same as growth. While social media and Reddit threads hum with predictions of overnight transformation, Mario looks at the structural bottlenecks that AI simply cannot solve with code alone.

Citing Satya Nadella, Mario argues that for a technology to be truly revolutionary, it must drive at least 10% GDP growth year-over-year. Currently, we are seeing “incremental improvements.”

Businesses are using AI to optimize internal processes—making a team of 4 able to do the work of 5—but they aren’t necessarily creating new markets:

• If every design firm uses AI to work 40% faster, the market doesn’t suddenly need 40% more designs. Instead, the service becomes a commodity, the price drops, and the “pie” remains the same size.

• Real growth requires new revenue streams, not just cost-cutting. Until AI can fabricate new clients or solve the “physical constraints” of production and logistics, it remains an operational tool rather than an economic savior.

One of Mario’s most grounded insights is the persistent friction of the Public Sector and Physical World. We live in a “duplex” reality: our LLMs move at light speed, but our institutions move at the speed of paper.

Mario predicts it will take decades for the most impactful changes (like robotics in construction) to hit critical mass, also due to regulatory resistance. Whether it’s the banking sector’s refusal to trade 24/7 or the government’s requirement for a physical signature on a permit, human systems are designed for stability and safety, not pure digital efficiency.

As AI commoditizes “average” work, Mario predicts a brutal thinning of the herd:

• The bottom 50% of performers in “desk jobs”—those who look for safety and work-life balance without exceptional output—will find their roles evaporated.

• Whether your craft is microbiology, logic, or communication, being “good” is no longer enough. To be safe, you must be in the Top 1%. This is the only level where human intuition and complexity still outpace the machine.

If Mario could travel back to 1999 Bulgaria, he wouldn’t tell himself to learn a specific language; he would tell himself to prioritize Adaptability over Habits. He admits to having “missed the boat” on certain leaps by sticking to old narratives for too long.

In a recession or a tech-led disruption, the first people let go are those who aren’t “helpful.” Mario’s advice is simple: be the person who is used to grinding, staying helpful, and evolving faster than the framework you are currently using.

Grounding and Legacy

Mario stays grounded through a “high-gravity” family life.

Despite managing global time zones and 25+ investments, he treats family time as the primary purpose of his work.

He workouts 3x a week with his partner—a ritual that serves as both a physical regime and a relationship anchor. He stays humble by opening X (formerly Twitter):

“You see everyone doing exciting stuff, and you realize it’s time to get back to work.”

If resources were unlimited, Mario would launch a Proprietary Data Powerhouse.

In a world where AI has scraped the entire “public” internet, the only remaining moat is private, high-fidelity data. He would hire 20 world-class journalists to go into the field and extract the “internal secrets” of the private markets, creating a data source that no LLM can replicate because the data doesn’t exist online.

How cool!

🔹 What you can steal

Mario’s approach can be articulated in 3 high-level tactical concepts:

1. The “Saturday Prototype” Rule: If you have an idea for a tool that would save your team 5 hours a week, don’t put it in a Jira ticket for next quarter. Use Cursor or Replit this Saturday to “vibe code” a proof of concept. If you can’t build a clickable version in 4 hours, your idea is too complex.

2. Audit Your Moat: Ask yourself: “Am I doing work that depends on a desk and a VPN?” If yes, you are competing with the entire world’s talent pool and AI. Find a way to tie your work to local compliance, physical assets, or high-trust relationships.

3. The Language Shift: Stop selling “services” (e.g., “I do SEO”) and start selling “Value Creation” (e.g., “I optimize the marketing-to-sales data bridge to increase EBIDTA”). Move your narrative from the How to the CFO’s bottom line.

   

🔹 Maurizio’s Take

Mario Peshev is the “Engineer-Philosopher” we need in 2026 because he refuses to play the game of digital make-believe.

My conversation with him left me with a sharp realization: We are currently building Ferraris (AI agents) to drive on dirt roads (the physical and regulatory world).

If you use AI to do your job 40% faster, but the physical world (permits, construction, supply chains) doesn’t accelerate at the same rate, you haven’t created growth, you have only just created idle time. In a capitalist system, idle time without new revenue leads to one thing: commoditization.

If everyone is 40% more efficient, the market value of that work simply drops by 40%.

This is where Mario and I align most closely.

The “middle” is a dangerous place to be. If your job is a “desk job” that relies on general knowledge, you are competing against an LLM that has read the entire internet. Mario’s strategy of using AI to build highly specific, proprietary tools is a smart way to stay ahead.

The most contrarian takeaway from our talk was his “Legacy Project.”

While everyone else is trying to build the best prompt, Mario wants to hire journalists to find data that doesn’t exist online yet. In an age of infinite synthetic content, truth and proprietary data are the only currencies that won’t inflate to zero.

To survive the next decade, you have to build the proprietary data layer and the high-trust physical presence that makes the funnel irrelevant. If your value can be summed up in a prompt, you have already lost.

👀 Where to find more about Mario

• LinkedIn

• X (formerly Twitter)

• DevRix - RevOps consulting

• Growth Shuttle - async advisory for SME executives

• Growth Shuttle Insider newsletter

• Mario’s Website

If you enjoyed today’s conversation and read Consulting Intel, please do me a favor: share this post, spread the edge.

👋

⚠ Check these links out

• I have shared a paper by Anthropic’s researchers Alex Tamkin and Judy Hanwen Shen (How AI impacts skill formation) in one of my recent LinkedIn posts. You can click the image below (and don’t forget to connect with me, I always appreciate it!!):

  

• My first book Beyond Slides became a #1 Amazon Best Seller in the USA, UK, Australia and Italy;

• The Leaders Toolkit is a deck of 52 tools, frameworks and mental models to make you a better leader (use code CONSULTANT10 for 10% off);

• The Consulting Intel private Discord group with 250+ global members is where consultants meet to discuss and support each other (it’s free).

As Jim Barksdale, the former CEO of Netscape, famously said: “There are only two ways to make money in business: bundling and unbundling.”

Perhaps the most famous example of unbundling in internet history is Craigslist.

In the late 90s, Craigslist was the ultimate bundle.

It had everything: jobs, apartments, used cars, personals, and tickets, all on one text-heavy website.

Entrepreneurs, however, realized they could build a better experience by picking just one section of Craigslist and making it a standalone company:

• Airbnb unbundled “Short-term rentals”;

• Zillow unbundled “Real estate”;

• Indeed/LinkedIn unbundled “Jobs”;

• StubHub unbundled “Tickets”.

These companies focused on a specific niche, and managed to provide significant more value than the generalist “bundle” ever could.

A decade ago, in the banking sector, monolithic legacy systems handled everything from core ledgers and CRM to payments and billing under one (often clunky) roof.

Then, the fintech revolution arrived.

We noticed that a specialized platform (like Stripe for payments or Salesforce for CRM) could outperform a generalist suite every time, and we decided to unbundle the bank.

The “Cable TV” unbundling of media and entertainment is playing up right now.

For decades, the Cable Package was the king of bundling. You paid one monthly fee to Comcast or Time Warner and got 200 channels, even if you only watched five of them.

At some point, services like Netflix, Hulu, and Disney+ allowed us to “cut the cord”: we unbundled the channels and paid only for what we wanted.

Today, because consumers are tired of managing 12 different subscriptions, we are seeing “bundles” return through services like Disney+/Hulu/ESPN+ or Apple One.

Bundles offer convenience; unbundling offers choice.

In 2026, we are witnessing a new, more profound type of unbundling, the one happening to us. AI is currently in the “choice” phase: breaking jobs down into specific, high-performance tools.

The great job unbundling

With Generative AI, we are (re)discovering that a “job” is really just a bundle of tasks.

Some of these tasks require deep human empathy and strategic intuition, while others are repetitive, data-heavy, administrative, and very boring.

According to Gartner’s 2026 predictions, 40% of enterprise applications will feature task-specific AI agents by the end of this year. This means the tools for unbundling are no longer experimental but (kind of) the new standard.

As AI matures, we are seeing the emergence of two distinct groups of knowledge workers. Your position in the next three years depends entirely on which group you choose to join today.

Group 1: The Augmentoooors (The “10x” Workers)

This group views their job description not as a static title, but as a collection of modular tasks. These people are actively unbundling their own roles to see what AI can handle.

They experiment relentlessly. They don’t just “use ChatGPT”; they build custom GPTs for their specific workflows, use Perplexity for deep-dive research, and automate their meeting notes with tools like Otter.ai or Fireflies.

According to a study by Harvard and BCG, consultants using AI finished 12.2% more tasks on average and completed them 25.1% faster, with 40% higher quality results than those who didn’t.

Their productivity skyrockets because they offload the “drudge work” and have more time for high-level creative thinking.

Group 2: The Traditionalists (The Vulnerable)

This group sees the pace of innovation as a threat or a distraction.

They feel that their “style” of working is what makes them valuable, and they resist adapting their workflow to new tools.

By refusing to unbundle their tasks, they remain tethered to low-value activities that AI can now do in seconds!

Research from Goldman Sachs suggests that generative AI could automate up to 300 million full-time jobs globally. However, “automation” rarely means a robot takes your seat; it means your tasks are absorbed by someone more efficient. PwC’s 2026 predictions note that leadership is shifting toward top-down AI programs that target high-value workflows.

If you are not the one identifying these opportunities in your role, your organization likely will…

I still think AI won’t steal your job (but there is a catch)

There is a popular phrase circulating: “AI won’t take your job, but a human using AI will.”

While it sounds like a LinkedIn cliché, the mechanics of it are quite cold. If an “Augmentoooor” can perform their own tasks plus 60% of yours because they have automated the baseline work, the economic rationale for keeping both roles vanishes. Your tasks don’t disappear per se, but they converge into the workflow of the more productive person.

Example: The Content Marketer

A Traditionalist content marketer spends 4 hours researching, 4 hours drafting, and 2 hours formatting a single blog post. Total: 10 hours.

The Augmentoooor content marketerer uses AI to scrape research data, generates 5 distinct outlines, uses a LLM to draft sections, and uses AI-driven SEO tools to optimize. Total: 2 hours.

It is clear to me that the second person can produce 5 times the volume at the same (or higher) quality.

The Traditionalist is both slower and economically non-viable.

The 2026 “Task Audit” Checklist

I believe the great unbundling of work is inevitable: we are moving toward a future where “role” matters less than “output efficiency.”

I routinely ask myself a very simple but powerful question:

Which of my daily tasks are “low-hanging fruit” for AI?

If you don’t unbundle them and automate them yourself, eventually, the market will do it for you, and it might give those tasks to someone else.

To help you move from Group 2 to Group 1, run this audit on your workweek:

1. Identify the “Loops”: Which tasks do you do at least three times a week? (e.g., status updates, data cleanup, email triaging, etc). These are prime candidates for Agentic AI.

2. The “2-Minute Rule” in Reverse: If a task takes you 30 minutes but involves 0% original thought (like summarizing a meeting), it should be unbundled. Now!

3. Tool Mapping:

   1. For Coordination: Use Motion or Reclaim.ai to automate your schedule.

   2. For Synthesis: Use Otter.ai or Fireflies to unbundle “note-taking” from “listening.”

   3. For Creation: Use Jasper or Copy.ai or WisprFlow to handle the “blank page” problem.

4. Skill Gap Check: Do you know how to “orchestrate” an agent? If not, spend 1 hour this week on a prompt engineering or AI orchestration tutorial. Then, listen to these 2 interviews (and, in general, everything produced by to be in the middle of the AI conversation):

   Dwarkesh Podcast

   Elon Musk — "In 36 months, the cheapest place to put AI will be space”

   Listen now

   2 months ago · 298 likes · 138 comments · Dwarkesh Patel

Dwarkesh Podcast

Andrej Karpathy — AGI is still a decade away

Listen now

6 months ago · 347 likes · 17 comments · Dwarkesh Patel

We have some work to do, folks!

As usual, if you enjoy reading Consulting Intel, please do me a favor: spread the word and share this post.

👋

👀 Links of interest

A few corners of the internet you may find interesting:

• My first book Beyond Slides became a #1 Amazon Best Seller in the USA, UK, Australian and Italy. This is a message I received the other day from a new reader:

  

• Have you looked into the Leaders Toolkit? It is a deck of 52 tools, frameworks and mental models to make you a better leader (use code CONSULTANT10 for 10% off);

• The Consulting Intel private Discord group with 250+ global members is where consultants meet to discuss and support each other (it’s free).

Big podcasts and large publications chase Bezos-level names who talk about strategy from 30,000 feet: it’s inspiring, yes, but useless if tomorrow you are walking into a meeting with your client and a deck to defend…

EDGE, a format by Consulting Intel, is where I sit down with world-class operators, consultants, and investors working between business, tech, and AI… and where I distill what I learn in something you can read in ~7 minutes.

LFG! 🔥

You are likely feeling the weight of the digital world: too much noise, too many buzzwords, and too few people willing to call out the obvious absurdities of modern business. That’s why I sat down with Tom Goodwin, one of the industry’s most influential, and deliberately contrarian, voices.

His philosophy is simple: most companies are built on flawed, historical assumptions, and they are simply not customer-centric.

Tom Goodwin is a highly sought-after writer, keynote speaker, and consultant.

Starting his career studying architecture and structural engineering, he spent a decade in major advertising agencies (including a role in “amateur futurism” sparked by a Nokia client) before setting up his own ventures. He is known for his ability to synthesize complex technological shifts into simple, provocative truths, often challenging the dominant narratives in marketing, technology, and organizational design.

Let’s jump into the conversation!

Origin Story

Tom’s career path was less a straight line and more a series of accidental shifts driven by innate curiosity… He started in structural engineering and architecture, a logical choice for someone that “always had a very curious mind.” When he graduated, he failed culturally in interviews for the typical high-status paths like investment banking and management consulting.

“I would look around the room and I would look at the people there, and I remember thinking these were not people that I would enjoy spending time with.”

He was advised to work in advertising, an industry he had never considered, and he quickly found his footing. Over time, his role became the one nobody else wanted: “I got given more and more weird jobs. So, my jobs became about doing the things that no one else knew how to do.”

The turning point was a huge miss. Frustrated that the best ideas developed for clients were outside the CMO’s power to execute, he naively left advertising to set up a consultancy called Tomorrow. It was focused on ambitious problem-solving for senior executives but “failed spectacularly” due to a lack of clients and credibility.

His core belief that emerged from this:

Curiosity is the engine, but public reputation is the fuel.

His writing, which started as a side-muscle on sites like Quora, gave him the credibility to return to the industry as a sought-after voice, transforming failure into a powerful new foundation for his personal brand.

Edge

Tom’s unique edge is his commitment to rethinking assumptions, a practice he defines as the opposite of contrarianism.

His writing process is informal, fueled by the “irritation” he feels when he hears a common industry claim that he knows to be ridiculous (e.g., “no one watches TV anymore”). He deliberately avoids a rigid framework for the world to maintain an open perspective.

His work consistently centers on a critique of what he calls “company-centricity.”

“The opposite of customer centricity is being ‘company centric’... rooted in the industrial revolution’s focus on manufacturing efficiency, repetition, and internal KPIs.”

He argues that most companies treat customers with “disregard,” prioritizing internal process over the customer experience.

This explains why something as simple as buying a printer is an impossible task of navigating confusing nomenclature like “LFP 54 ZJ” vs. “LFP 93 PFQ.”

In his work, he sees himself as the necessary voice of the customer, introducing possibilities and imagination beyond a company’s past performance.

He collects his stimulus informally (e.g., voice notes while walking his dog, photos of signs, scribbles in a physical notepad) then waits for the ideas to “coagulate together” to form an article.

Future

When discussing AI, Tom affirms its transformative potential, but cautions that it’s currently “extremely badly defined.”

He insists that its adoption will follow three stages, moving from simple acceleration to true transformation:

1. Easier and Faster (Next 2 Years): AI will be used to make small parts of existing jobs and processes faster and cheaper.

2. Better (2–4 Years): Companies will “re-orchestrate how they work,” restructuring and improving processes and software to achieve better ERP systems or different ways of handling invoices.

3. Different (Long-term): This stage involves a fundamental rethinking where processes are eliminated entirely. “Maybe we won’t send invoices anymore. Maybe people won’t be on as many meetings.”

He stresses that companies must not delay: every company needs to develop a formal AI strategy through a Global Head of AI or a task force, and every individual must be actively experimenting with the technology.

When asked for advice to his 19-year-old self, he gave a simple, profound prescription for overcoming the paralysis of a curious mind:

“Think a little bit less and do a little bit more.”

Grounding and Legacy

Tom is not a man of formal rituals, but rather a “way of being.”

This includes actively seeking out things that make him uncomfortable, buying magazines he normally wouldn’t, and doing a lot of writing daily. This lack of rigid routine is itself a reflection of his philosophy: a desire to maintain an open perspective and continuously challenge his own assumptions.

If given unlimited time and resources for a project outside his current work, Tom would tackle the problem of environment and well-being.

He would love to design and build “contemporary homes that are somewhat affordable and somewhat modular,” based on his belief that a healthy, green living space is “almost like a human right.”

This ambition reflects his core desire to be a voice for what the customer (or the citizen, in this case) truly needs, blending his initial roots in design and engineering with his developed passion for human-centered problem-solving.

🔹 What you can steal

Tom Goodwin’s approach is a toolkit for action in a confusing world. I will try to dissect it in three steps:

1. Start with Irritation: Instead of waiting for a breakthrough idea, let your writing or problem-solving process be fueled by a clear, specific annoyance at a common, lazy industry claim. Use that energy to question the status quo.

2. Be the Voice of the Customer: When reviewing any internal process or product, ask yourself: Where are we being company-centric? Look for the equivalent of a confusing printer name or a frustrating check-in process. That gap is where your real value lies.

3. Action over Analysis: If you find yourself in the same analysis loop, stop. Take Tom’s advice and “think a little bit less and do a little bit more.”

   Action, even small, imperfect action, creates momentum and prevents the stagnation of over-thinking.

🔹 Maurizio’s Take

Tom’s true gift is his structural mind - honed by engineering - applied to creative problems. He doesn’t critique per se, he dissects the faulty wiring of organizational systems.

While Tom is skeptical that curiosity can be trained from scratch, he stresses it must be nurtured. Modern life, routine, and corporate dogma all work to “beat curiosity out of people”, so I agree that a good way to maintain it is to seek out what makes you uncomfortable and consume diverse, contradictory information to keep the muscle alive.

The most important takeaway, I believe, is this: Tom has built a career not on finding the “right” answers, but on consistently asking the better questions. Your future as a thought leader and a successful professional is not about what you know, but about your willingness to say: Wait a minute, I don’t think that’s true.

Most companies confuse being customer-responsive with being customer-obsessed.

They design processes to respond to immediate issues and feedback, but they fail to build a system where the customer’s logic is the primary source of design, not the secondary correctional input. This leads to the baffling, frustrating products and processes we all experience daily, where a company’s inability to change is packaged as “just how things are.”

Tom has the sharpest eye to detect such inconsistencies.

👀 Where to find more about Tom

• LinkedIn

• X (formerly Twitter)

• Nowism newsletter

• Tom’s book: Digital Darwinism: Surviving the New Age of Business Disruption

• Tom’s Website

If you enjoyed today’s conversation and read Consulting Intel, please do me a favor: share this post, spread the edge.

👋

⚠ Check these links out

• My first book Beyond Slides became a #1 Amazon Best Seller in the USA, UK, Australia and Italy;

• One of my recent posts on LinkedIn did a lot of views as I offered my views on how I think banks will have to change in the AI era. You may be interested:

  

• The Leaders Toolkit is a deck of 52 tools, frameworks and mental models to make you a better leader (use code CONSULTANT10 for 10% off);

• The Consulting Intel private Discord group with 250+ global members is where consultants meet to discuss and support each other (it’s free).

If you are not visible, you are invisible - and most firms are currently ‘Ghost Brands’: they have 5,000 employees but only one authorized voice (the corporate PR account).

The hypothesis behind this article is that the firm’s logo has become a secondary asset in 2026: the primary driver of brand equity in the next 5 years will be the Collective Intellectual Authority of its visible experts.

To succeed as a Founder Intellectual or Executive Celebrity, you must transition from being a “manager of a brand” to being a trust broker, a human proxy who bridges the gap between corporate complexity and individual resonance.

I noticed a lot of interest around one of my recent posts on X, so I decided to put together this article to highlight core ideas of my research:

Everything discussed in here is something I am personally testing through my public media outlets:

• My book Beyond Slides (a #1 Amazon best-seller in UK, US, Australia and Italy, published in June 2025)

• This newsletter (free to subscribe, started in 2024)

• My LinkedIn profile (always happy to connect - I have been posting regularly since June 2025, after a decade and a half of lurking)

For context, you may know I am a corporate executive (specifically, I am a partner at a large management consulting firm), but I do expect much of what I discuss in this article to apply to most startup founders and corporate executives in most industries across most developed western countries.

Surely, there’ll be case-by-case considerations to make, but I hope this detailed guide gives you some practical ideas for you to take forward.

In the next sections, we are going to go into specific tactics and, at the end, I will also leave 32 weblinks of articles/reports that were part of my research.

Let’s start.

The macro-environmental catalyst: the “insularity mindset”

Global trust is shifting.

What began as a crisis of grievance has evolved into a crisis of insularity, where people are retreating into smaller, more comfortable circles. This explains why they now place more trust in figures they know, favoring “My CEO” (trusted by 60%+, as per the Edelman Report) and their coworkers over traditional institutions like the media or government.

This environment creates a powerful opportunity because the traditional, faceless approach of B2B marketing is no longer working. In response, high-performing firms are scaling up their investment in human-led insight, treating marketing as a core growth function and increasing its share of revenue from 10% to 12% in 2026.

The overarching strategy is clear: executive visibility should not be about promotion.

Instead, executives must be positioned as “Category Explorers,” using social platforms to navigate plus provide knowledge and sense-making in their industry’s real-time ambiguities.

As institutional trust wanes, the visibility of individual executives on digital platforms has therefore become a critical asset.

Research led by Professor Ann Mooney Murphy at Stevens Institute of Technology demonstrates that social media has created a new pathway for achieving executive celebrity, independent of traditional media gatekeepers.

This “social media celebrity” becomes a strategic tool that correlates with firm reputation, mainstream media visibility, and even executive compensation.

When institutions are mistrusted, the logo becomes a barrier. To break through, we must dismantle the black box of the firm and replace it with a visible intellectual trail.

This begins with Phase I: The “Proof of Thought” protocol.

Phase I: The “Proof of Thought” protocol

Visible authority is not built through “best practices,” but through Evidence-Based Intelligence, defined as distinctive, research-backed insights that provide the inspiration to act.

A. Strategic Vulnerability & The Practicality Effect

The “cringe tax” associated with early-stage personal branding is actually a trust signal.

“Perfect” corporate claims trigger skepticism, however, the Practicality Effect proves that when a leader acknowledges a minor weakness or an unfinished thought, their subsequent expert claims are perceived as significantly more believable.

The Tactic: Share the “v0.1” of a mental model or a project struggle. Occasionally posting a hypothesis you aren’t sure of proves you are working at the cutting edge, not just recycling the past.

B. The curator’s edge

In a world of information overload, the executive’s value is as a “High-Pass Filter”.

Curation is communal labor that builds interpersonal trust. By showing how you know what you know, you form para-social relationships: these are emotional bonds with followers that correlate with increased firm reputation and executive compensation.

The Tactic: Publicly share your browser tabs, obscure whitepapers, or niche data sets that shape your thinking. Your value is not just what you know; it’s how you filter the world.

Sharing what you read is only the first layer of authority.

While your information diet proves you are informed, clients ultimately pay for your execution. To bridge the gap between thinking and doing, we move to Phase II: Operational Transparency (showing the work).

Phase II: Operational Transparency (showing the work)

Intellectual authority must be backed by Operational Transparency, the deliberate disclosure of internal processes to reduce knowledge asymmetry.

94% of consumers are likely to be loyal to brands that offer complete transparency. In professional services, “a delay explained is a delay forgiven,” whereas silence is perceived as a failure mode.

The Tactic: Redact and publish internal strategy memos or “behind-the-scenes” videos of problem-solving sessions.

Phase III: The Polyphonic Leadership Model

The greatest risk of the Celebrity Executive is Key Person Risk, which can discount a firm’s market valuation by 10% or more if all authority is centralized in one star.

A common objection here is: “If we make our partners celebrities, what happens if they leave?”

This is a valid risk assessment, but the solution isn’t to keep them invisible, but rather to institutionalize their brilliance.

Strategic risk management requires a shift from a monophonic (single voice) to a polyphonic (multiple voices) communication model, with the goal to multiply the firm’s surface area for trust.

By cultivating personal brands for multiple senior leaders and experts, the organization ensures that credibility is distributed rather than centralized:

1. Succession planning and apprenticeship: Grooming potential replacements and investing in their training to reduce dependency on a single visionary;

2. Strategic documentation: Formalizing business processes and relationship management within a CRM to move ownership from the individual to the organization;

3. Executive Duo Leadership (EDL): A model gaining popularity in finance and technology, where two leaders of equal status jointly manage the company, providing protection against burnout and executive isolation.

Perhaps paradoxically, “de-branding” the individual means ensuring that multiple experts represent the firm in podcasts, articles, and videos.

Tactical implementation for 2026

The move toward individual celebrity does not mean abandoning formal assets like white-papers; rather, it changes how those assets are distributed and perceived.

Modern B2B strategy requires a balance between Individual Resonance (reach and trust) and Institutional Authority (validation and conversion).

Some ideas to explore:

The Reach vs. Conversion paradox

The most common mistake is assuming that high engagement on social media automatically equals sales. Data suggests a distinct split in how personal profiles and company pages perform on platforms like LinkedIn:

1. Personal Profiles: Typically generate 10x more reach and 5x more engagement than company pages. They are the primary engine for “Proof of Thought” and for building the top-of-funnel para-social relationships that make an executive a “celebrity” (which we discussed above);

2. Company Pages: While reach is lower, they often drive 6x more conversions per impression. Serious B2B buyers use the company page as a “digital shopfront” to validate legitimacy and research the team before signing a contract.

The “Hub-and-Spoke” content model

To balance formal research with free-flowing thought, the most effective executives use a Hub-and-Spoke strategy:

• The Hub: A high-value, formal “hero asset” (like a research-backed white paper on letterhead). This provides the evidence-based intelligence that 73% of B2B buyers trust more than marketing materials.

• The Spokes: 10–15 pieces of “free-flowing” informal content derived from the hub. This includes contrarian takes on LinkedIn, “walking to a meeting” videos, and screenshots of browser tabs.

The strategy is to use the informal posts to talk about the industry in general without mentioning the company. This builds your identity as the “favorite teacher” in the industry: only after you have built this trust do you point them toward the “Hub” for deeper insight.

Tactical suggestions for senior teams

To avoid the “cringe” of over-promotion, senior colleagues should adhere to a structured content mix (this is, incidentally, roughly what I am also personally doing on my LinkedIn profile for example):

1. The 4-1-1 Rule: For every six posts, four should be valuable/educational (no mention of the firm), one should be “gentle branding” (e.g., a team culture highlight), and only one should be a direct call-to-action (e.g., “Download our new white paper”).

2. The 70-20-10 Rule: Allocate 70% of content to education (solving the client’s “problem of the week”), 20% to personal connection (sharing a struggle or curious observation), and 10% to self-promotion.

3. The Zero-Link Strategy: Posts without external links (pure text or image galleries) generate 60% more engagement than those that try to drive traffic away from the platform. Share the insight in the post itself; don’t make them click a link to “learn more”.

Note that the 4 (value) and 70 (education) above should never mention the firm. In my experience, this is the hardest part for executives to grasp. You will want to “soft sell”, but if you mention the firm in the value phase, you have broken the spell of the human proxy.

To be explicit, this approach is not yet the gold standard in corporate communication (large enterprises move slowly and are late adopters of new trends), but all research points to this as the general direction of travel.

An executive team starting now has the opportunity to create an entire category, and acquire a lead in the market perception which will be hard to bridge for competitors.

Navigating the “cringe tax”

The term corporate cringe describes messaging that tries to appear “cool” through forced emotional appeals.

To avoid this “cringe tax”, I finally recommend five actions:

1. Kill the Jargon: use plain English and a conversational style rather than corporate jargon. Followers value leaders who relate on a personal level and look like “one of us”, not senior leaders who over-complicate their prose because of their hidden desire to sound intelligent;

2. Strategic Vulnerability: If you look like a “LinkedIn Bro,” acknowledge it. Admitting the awkwardness of the platform actually increases your E-E-A-T (Experience, Expertise, Authoritativeness, Trustworthiness) signals and, ultimately, will benefit you;

3. Human Over AI: While 74% of teams use AI, content labeled as AI-written can halve engagement. Your human watermark is your unique, fallible point of view: why would you give that away?

4. Who cares?: most founders/executives are paralyzed by status anxiety, ie, the fear of looking silly to their peers. But your peers are not your customers! Your competitors will call you “cringe” because your visibility highlights their invisibility. If the people you are competing with don’t like what you are doing, you are winning.

5. Outcome over Optics: Frame your mindset as a business calculation. Would you rather have a “perfect” reputation among 100 peers who will never hire you, or be “a bit much” for 10,000 prospects who now see you as the only authority in the room?

The bottom-line ROI

Let’s be honest: the first time a Senior Partner posts a raw, unedited video of themselves “thinking out loud” about industry displacement, their peers will snicker. There will be comments about “vanity projects” and “LinkedIn influencers.”

Ignore everything.

By the time your competitors realize that this isn’t a fad, you will have built an Intellectual Infrastructure: you will have a library of your thoughts, your mistakes, and your curiosities that works for you 24/7.

This is about sales velocity.

Data from IBM and Oxford Economics has shown that high-quality thought leadership delivers a ROI of 156%. Why? Because it short-circuits the sales cycle.

When an executive is a “Visible Expert,” the prospect doesn’t spend the first three meetings vetting the firm’s competence: they have already spent six months “thinking with” the executive online!

The trust is pre-baked, and research shows these prospects move through the pipeline 35-40% faster.

In 2026, systems win and hustle loses.

By building an Intellectual Infrastructure around your key people, you move from a commodity service provider to a category-defining authority.

Are you ready to start your journey to become a Founder Intellectual / Executive Celebrity?

As usual, if you enjoy reading Consulting Intel, please do me a favor: spread the word and share this post.

👋

Works cited you can further review

1. 2025 Edelman Trust Barometer, https://www.edelman.com/trust/2025/trust-barometer

2. 2026 Edelman Trust Barometer | Edelman, https://www.edelman.com/trust/2026/trust-barometer

3. Edelman Trust Barometer 2026: 70% retreat into insularity - HRZone,

   https://hrzone.com/2026-01-edelmann-trust-barometer-2026-insularity/

4. 2025 Edelman Trust Barometer | Edelman, https://www.edelman.com/au/trust/2025/trust-barometer

5. Study Reveals How CEOs Become Social Media Celebrities, https://www.stevens.edu/news/study-reveals-how-ceos-become-social-media-celebrities

6. The influence of CEO and CFO media visibility on the market value of the firm | Corporate Governance | Emerald Publishing, https://www.emerald.com/cg/article/doi/10.1108/CG-10-2024-0542/1278945/The-influence-of-CEO-and-CFO-media-visibility-on

7. The New Rules Of Reputation And Brand Equity In An AI-Driven Future - Forbes, https://www.forbes.com/councils/forbescommunicationscouncil/2026/01/07/the-new-rules-of-reputation-and-brand-equity-in-an-ai-driven-future/

8. The psychology of trust: Why customers believe some brands over others (with examples),

   https://www.agilitypr.com/pr-news/branding-reputation/the-psychology-of-trust-why-customers-believe-some-brands-over-others-with-examples/

9. Thought Leadership as a Platform for B2B Marketing ROI – TopRank...,

   https://www.toprankmarketing.com/blog/thought-leadership-platform-b2b/

10. Measuring the ROI of Thought Leadership | Cindy Anderson and Anthony Marshall,

    https://thoughtleadershipleverage.com/measuring-the-roi-of-thought-leadership-cindy-anderson-and-anthony-marshall/

11. The ROI of Personal Brands and Thought Leadership - Roloff Consulting,

    https://www.roloffconsulting.com/the-roi-of-personal-brands-and-thought-leadership/

12. The impact of thought leadership in the B2B decision-making process - The SEO Works,

    https://www.seoworks.co.uk/downloads/impact-of-thought-leadership-in-b2b-decision-making-process/

13. Professional Services Marketing Trends for 2026 - Milvanta, https://www.milvanta.com.au/post/professional-services-marketing-trends-for-2026

14. How Can Vulnerability Affect Brand Connection? - Lifestyle → Sustainability Directory, https://lifestyle.sustainability-directory.com/question/how-can-vulnerability-affect-brand-connection/

15. The 9 Psychological Tactics Companies Use to Win Your Trust: Inside the Science of Brand Credibility - Status Labs, https://statuslabs.com/blog/psychological-tactics-companies-use-to-win-your-trust-inside-the-science-of-brand-credibility

16. Tuning Your Voice: Trends in Brand Language - Antidote, https://www.antidote.info/en/blog/reports/trends-in-brand-language

17. Corporate Cringe - Doctor Spin, https://doctorspin.net/corporate-cringe/

18. The Psychology of Trust | Brandtrust, https://brandtrust.com/blog/the-psychology-of-trust/

19. How To Create Behind-the-Scenes Content That Builds Trust and Transparency,

    https://ronntorossianupdate.com/how-to-create-behind-the-scenes-content-that-builds-trust-and-transparency

    2

20. Operational transparency: The new currency of trust - Retail Banker International, https://www.retailbankerinternational.com/comment/operational-transparency-new-currency-of-trust/

21. Human-Centric Content at Scale: Balancing AI Efficiency with Authentic Storytelling, https://www.ndash.com/blog/human-centric-content-at-scale-balancing-ai-efficiency-with-authentic-storytelling

22. Content Marketing in 2025: Authenticity vs AI? : r/DigitalMarketing - Reddit,

    https://www.reddit.com/r/DigitalMarketing/comments/1nwt316/content_marketing_in_2025_authenticity_vs_ai/

23. AI Content vs Human Content: What Actually Wins in 2025? - Grafit Agency,

    https://www.grafit.agency/blog/ai-content-vs-human-content

24. The 2026 B2B Content Strategy Most Marketers Miss, https://theb2bplaybook.com/b2b-content-strategy-2026

25. Four Ways to Manage Key Person Risk - Brady Ware, https://bradyware.com/manage-key-person-risk/

26. Managing Key Person Risk - BusinessRiskTV.com, https://businessrisktv.com/managing-key-person-risk/

27. Monophony and Polyphony - Doctor Spin, https://doctorspin.net/monophony-and-polyphony/

28. Assessing the impact of key person risk on business valuation - William Buck Australia, https://williambuck.com/news/ex/general/assessing-the-impact-of-key-person-risk-on-business-valuation/

29. THE POTENTIAL OF THE EXECUTIVE DUO LEADERSHIP - DSpace,

    https://dspace.ut.ee/bitstreams/add6a22f-48ed-4271-8bc7-f3637cb8b250/download

30. B2B content distribution strategy for demand generation that drives engagement - ViB Tech, https://vib.tech/resources/marketing-blogs/dp-b2b-content-distribution-strategy-for-demand-generation/

31. B2B Marketing Strategies For 2026 | AI, Alignment & Personalization,

    https://viragomarketing.com/b2b-marketing-strategies-2026/

32. Professional Services Marketing: Must-Know Trends For 2026 - ON24,

    https://www.on24.com/blog/professional-services-marketing-must-know-trends-for-2026/

👀 Links of interest

A few corners of the internet you may find interesting:

• My first book Beyond Slides became a #1 Amazon Best Seller in the USA, UK, Australian and Italy;

• Have you looked into the Leaders Toolkit? It is a deck of 52 tools, frameworks and mental models to make you a better leader (use code CONSULTANT10 for 10% off);

• The Consulting Intel private Discord group with 250+ global members is where consultants meet to discuss and support each other (it’s free).

Big podcasts and large publications chase Bezos-level names who talk about strategy from 30,000 feet: it’s inspiring, yes, but useless if tomorrow you are walking into a meeting with your client and a deck to defend…

EDGE, a format by Consulting Intel, is where I sit down with world-class operators, consultants, and investors working between business, tech, and AI… and where I distill what I learn in something you can read in ~7 minutes.

LFG! 🔥

Imagine betting over 50% of your personal portfolio on a single, highly-controversial stock, only to see it crater… and then double down.

That is the philosophy of Arnaldo (Arny) Trezzi, a contrarian investor (and a fellow Italian) who sees market panic as his primary hunting ground.

Arny’s entire investment framework is built on a single, surprising claim: The obsession you develop for a company is your single greatest competitive advantage.

He believes traditional financial analysts are often “fools” for relying solely on quantitative models, missing the fundamental edge that comes from understanding a business’s culture, leadership, and underlying narrative better than 99% of the market.

By the way, using NotebookLM I have created a 4-minute video that visually explains the key concepts of my conversation with Arny: have a look!

Arny Trezzi is an independent investor and the founder of popular newsletters Palantir Bullets (focused exclusively on Palantir) and Arny Trezzi (more recent, covering other high-conviction theses). With a background in Investment Banking and as a generalist equity analyst at the start of his career, he is an admitted obsessive-compulsive who operates outside the traditional fund structure, focusing on a few companies he knows so well he can preemptively debunk every bear case.

Let’s jump into the conversation!

Origin Story

Arny began his academic journey in Italy studying Economics and Commerce, later switching to Banking and Finance, driven by a fascination with the psychological component of the stock market: the panic, the emotion, and the opportunities that arise when others are losing their calm.

The major turning point came after his undergraduate degree when he read The Intelligent Investor. The book shifted his focus away from portfolio management and quantitative risk models toward an entrepreneurial approach to investing, rooted in deep business analysis - a skill he realized he sorely lacked despite graduating with honors.

A key failure that cemented his conviction was his attempt to open an investment holding company with a partner, which failed due to “personal incompatibilities.” This left him unemployed with a resume that traditional financial institutions viewed as too rebellious.

When COVID hit, freezing hiring, he faced a fork in the road.

Instead of despairing, he chose to reorient himself during the market crash, seeing the widespread fear as an opportunity to test his newfound conviction by aggressively buying into companies like Amadeus and Apple, whose stocks were hit by short term narratives.

The belief that emerged from these experiences is that true Margin of Safety is not just a mathematical concept but an informational asymmetry you create. He focuses maniacally on “capturing the asymmetry” between the depressed or misunderstood market narrative and the positive reality of the underlying business.

Edge

Arny’s investment style is defined by an obsession with depth over breadth.

He fundamentally rejects the structured process of a traditional fund manager, which aims to find a good idea. Instead, he starts with a few select companies he is passionate about and wants to study - his “basket of high-quality eggs.” His goal is to deepen his “circle of competence” to the point where he can confidently say he is in the “top 1 percentile of business understanding” for those companies.

His philosophy was forged in his investment in Palantir, an obsession that still constitutes over 50% of his portfolio and generated him over 20x return in three years. He initially heard of Palantir when it was private but went “all in” when the stock dropped below $10 amidst peak pessimism. He shared his research online, receiving torrents of criticism, which he used as fuel.

“You’ve truly understood a company when you are able to take every possible criticism and, rationally and calmly, demonstrate how that criticism is actually a non-existent point.”

For Arny, this was a moment of “unhuman asymmetry.”

He had accumulated so many hours of study that he saw the positive, accelerating developments in the business that the market narrative was completely missing. He wasn’t looking for a quick flip: he was accumulating conviction to hold through volatility.

His approach has succeeded in finding value in both Palantir and Robinhood , companies where the stock was depressed despite strong underlying business developments and culture.

Robinhood, Arny’s second biggest position after a 10x return, followed a similar initial recipe: loved by customers, hated by Wall Street. Arny believes his concentrated approach could be expanded to private markets, where he invested as an angel investor in Pillar, vertical SaaS for Real Estate, and participated in the latest round of Bending Spoons, the Italian first decacorn.

However, he emphasizes the limit of quantitative models: while the DCF model is useful for “testing your awareness,” it must never be mistaken for reality (citing his early mistake with Tesla , which he recognized as a powerful business but felt was “unbuyable” based on his rigid model).

He must also always be aware of the Bear Case, but only invests when he is certain the risks are already incorporated into the price.

“I don’t invest in 100,000 things. I take a basket, a few eggs that I know are of maximum quality, and I follow them like a maniac.”

Future

Arny views the explosion of AI and Large Language Models (LLMs) as a major filter for the investment world. He believes LLMs are just a tool that can facilitate counter-thesis research, but they don’t change his structural approach.

Arny’s investment thesis on Palantir is centered on the concept of Ontology. He sees Palantir not as a services company, but as a product company that used 20 years of services experience to build the world’s most powerful software platform.

His key prediction is: Palantir is the “operating system for using AI” in the enterprise, and the LLMs themselves are a commodity (the fuel). The real value is Palantir’s Ontology, which provides a holistic, digital twin understanding of the entire company, turning all the outputs of the LLMs into actionable knowledge that compounds within the firm.

He is concerned that LLMs will create a “false sense of confidence,” allowing people to generate investment theses in three hours instead of two weeks.

This shortcut is dangerous because, in his view, it takes a month to truly start understanding a company, and months more for those ideas to “ferment” and overcome confirmation bias.

Grounding and Legacy

Arny’s primary practice for mental clarity is intense physical exercise - specifically, calisthenics 2-3 times a week, and most crucially, “pushing himself to the limit in the mountains” (he is based near the Italian city of Lecco). He finds that this intense physical necessity forces his mind out of negative thought loops and restores the mental lucidity he needs as an investor.

Asked what project he would launch with unlimited time and resources, Arny admits he is currently in a position where the financial urgency is gone.

His priority has shifted to the personal realm: figuring out how to structure his life and compound value outside of just the financial channel.

This answer reflects his philosophy that once a certain financial threshold is crossed, the true value moves to time and experiences.

He notes the importance of “compounding in real life” and ensuring a stable personal foundation before tackling large entrepreneurial endeavors, citing the need to have a “fixed life” to be able to fully engage in an entrepreneurial “new leg.”

🔹 What you can steal

Arnaldo Trezzi’s philosophy offers powerful, actionable lessons for investors and business people alike. Let me summarize my key take-aways:

1. Inverse Your Research Framework: Stop trying to find the best idea by following a structured process. Instead, choose the two or three companies you are genuinely passionate about and whose developments you are excited to follow. Let your passion dictate your focus; the competence will follow.

2. Analyze the CEO and Culture Before the Numbers: Do not lead with the spreadsheet. Focus on understanding the CEO and the company culture first: Arny has met Palantir employees who accepted substantial pay cuts to work there (he also bumped into Alex Karp a couple of times in some Palantir events in the USA). Culture determines success, business translates culture into numbers, and numbers are the last piece of the puzzle .

3. Become Your Own Bear Case: Use criticism not as an attack, but as a roadmap. Actively seek out the strongest counter-arguments against your thesis. You must be able to rationally and calmly dismantle every single one to achieve true conviction and be confident that the risks are already incorporated into the stock price.

🔹 Maurizio’s Take

Arny is not a value investor in the traditional sense. He is an Information Arbitrageur.

In my view, his “obsession” is simply the modern-day moat for a solo investor. In a world saturated with financial data and models, the only way to gain a true informational edge is through sheer, cumulative time spent on a single target. He has successfully taken the consultant’s lens - prioritizing leadership, culture, and holistic business process (the Ontology) - and applied it to generate alpha where quantitative analysts, who are paid to look backward, fail.

The deepest takeaway is that your investment conviction is only as strong as the work you put in to defeat the bear case. If you let an LLM write your thesis in three hours, your conviction will evaporate in three minutes when the market panics.

This is true in investing, but I will leave it as an exercise for the reader to come up with an equivalent analogy in your professional field of play: it won’t take long.

The greatest risk in the age of AI isn’t not using the new tools, but using them to substitute the important, time-intensive process of truly digesting a company.

👀 Where to find more about Arny

• LinkedIn

• X (formerly Twitter)

• Palantir Bullets newsletter

• Arny Trezzi newsletter

If you enjoyed today’s conversation and read Consulting Intel, please do me a favor: share this post, spread the edge.

👋

Disclaimer: The views and opinions expressed above are current as of the date of this document and are subject to change without notice. Materials referenced above will be provided for educational purposes only. None of the above will include investment advice, a recommendation or an offer to sell, or a solicitation of an offer to buy, any securities or investment products.

⚠ Check these links out

• My first book Beyond Slides became a #1 Amazon Best Seller in the USA, UK, Australia and Italy;

• The Leaders Toolkit is a deck of 52 tools, frameworks and mental models to make you a better leader (use code CONSULTANT10 for 10% off);

• The Consulting Intel private Discord group with 250+ global members is where consultants meet to discuss and support each other (it’s free).

Excel: the disruptor of the “human calculator.”

I was a little too young, but somehow I can imagine the intellectual class of the 80s predicting the end of the accounting profession, seeing a 1:1 replacement with human beings.

If a machine can sum a column in a microsecond, why would we need the man who took an hour?

Today, 36 years after this commercial, we have more accountants, more analysts, and more “Excel Ninjas” than the 1990 mind could grasp. Excel eliminated the drudgery of the task, which in turn lowered the marginal cost of calculation, which (by the laws of Lindy and economic expansion) exploded the demand for complexity.

Today, 36 years after this commercial, we are hearing the same hysterical refrain regarding Generative AI: “This time is different” (but whenever someone tells you this time is different, they are usually trying to sell you either a doomsday bunker or a subprime mortgage).

From arithmetic to architecture

When the spreadsheet arrived, the “arithmetic” skill became a commodity, and the value shifted to Information Architecture. Nobody cared about who could add the fastest, but you surely had an edge if you could build the best model.

We are seeing the same inversion now:

• 1990: The cost of calculation went to zero.

• 2026: The cost of “first-draft” content and coding is going to zero (rapidly).

Does this mean the Consultant, the Lawyer, or the Engineer is obsolete? Well, only the ones who define themselves by the “arithmetic” of their trade.

If your value is merely generating a standard contract or writing a boilerplate script, you are a manual ledger in a 1990 world.

A spreadsheet can give you a P&L, but it cannot give a leadership team the vulnerability required to admit their strategy is failing. An AI can draft a “Mission Statement,” but it cannot sit in a room and forge the “Five Disfunctions”-proof bond that makes a team actually execute.

The “spreadsheet-era” demonstrated that as tools become more powerful, the bottleneck becomes human interpretation, understanding, empathy, EQ, etc etc

And so, are we indeed witnessing the end of work, or are we witnessing the end of boring work?

The “smart guys” of 1990 thought they were all losing their jobs when, in reality, they were being promoted to a higher level of abstraction.

The same is happening today.

Your job is not to fight the AI, but to become the person who knows what to ask it, how to vet its “hallucinations”, and how to apply the result to solve a human problem.

History is a great teacher for those who don’t think they are smarter than it:

• The spreadsheet created the Analyst, it didn’t kill the Analyst!

• AI won’t kill the Partner either. It will finally demand that the Partner actually partners, focusing on discernment, ethics, sense-making, leadership rather than the “arithmetic” of the slide deck.

• In the 1970s and 80s, “Legal Research” meant sitting in a basement for 40 hours, manually cross-referencing leather-bound books to find a single precedent. When LexisNexis and Westlaw digitized the law, the “researcher” role was effectively automated, and the legal profession exploded.

• For a century, a doctor’s primary value was their “internal database”, ie, remembering symptoms and matching them to diseases. Today, AI-powered imaging and diagnostic tools can out-read a radiologist and out-diagnose a generalist in specific pattern-matching tasks. This is the best thing to happen to medicine (!): it frees the physician from being a sub-optimal “search engine” and allows them to return to the Healer role.

A pattern emerges: technology always attacks the routine-analytical and the routine-manual, leaving behind a “human residual” (actually, the most valuable part of the job).

Will this time be actually different?

Let me know in the comments…

As usual, if you enjoy reading Consulting Intel, please do me a favor: spread the word and share this post.

👋

👀 Links of interest

A few corners of the internet you may find interesting:

• My first book Beyond Slides became a #1 Amazon Best Seller in the USA, UK, Australian and Italy;

• I had the opportunity to be an advanced reader for the book by my friend Kevin Ertell The Strategy Trap. He has done an excellent job at simplifying an otherwise complex subject, that people with decades of experience still do not understand. The book is well researched (which I like) and full of relatable stories. Follow Kevin Ertell and his newsletter The Strategy Trap Newsletter!

  

• Have you looked into the Leaders Toolkit? It is a deck of 52 tools, frameworks and mental models to make you a better leader (use code CONSULTANT10 for 10% off);

• The Consulting Intel private Discord group with 250+ global members is where consultants meet to discuss and support each other (it’s free).

Big podcasts and large publications chase Bezos-level names who talk about strategy from 30,000 feet: it’s inspiring, yes, but useless if tomorrow you are walking into a meeting with your client and a deck to defend…

EDGE, a format by Consulting Intel, is where I sit down with world-class operators, consultants, and investors working between business, tech, and AI… and where I distill what I learn in something you can read in ~7 minutes.

LFG! 🔥

Brian O’Connor thought he understood how business worked.

Six years in Deloitte. Ops boot camps. Growth and corporate strategy inside Monitor. Multi-hundred-million-dollar programs where a single slide could move a market.

Then a partner told him he had “single-handedly turned around” a $200M+ Paycheck Protection Program project… and handed him a gift card.

That was the moment the glitch appeared in the matrix.

“If I can create this much value under someone else’s logo,” he thought, “I need to know what happens if I try to capture even one percent of that for myself.”

Today Brian is a fully nomadic founder and operator. He runs a recruiting and staffing agency that places remote talent into US businesses, with 115+ placements and a pipeline that throws up 3,000 applicants per role. He and his partner have already built an AI recruiter that screens and interviews candidates, and they are now pushing into “AI After Dark” – AI customer support that takes over when the human clock hits 5pm.

It took some courage: Brian walked away from a high-margin solo CMO / advisory business that was making him very good money, to build a harder, lower-margin, more operationally painful agency… because he cannot stand living in the “advisor only” layer. He wants to build, not just point.

And he thinks most white-collar careers are far riskier than people want to admit in the age of AI.

Origin Story

Brian Fernando O’Connor Gonzalo Rubio grew up in Boston, in a Latin household with a banker father.

Dad was not just “in finance”, he used to talk strategy, balance sheets and deals at the dinner table. Brian jokes that he had corporate finance piped into the womb.

He was addicted to business early: high school and college were already full of small startup attempts. The obsession was there, the direction less so…

His first “real” job was in commercial banking: he thought he was going into investment banking because he did not fully understand the difference (Wolf of Wall Street fantasies, commercial banking reality).

From there he joined GE Capital, underwriting aircraft debt and working through a rigorous finance training program, aiming to sell aircraft debt and leasing. When GE Capital was sold, the program vanished and so did the job, and that forced a choice.

On one side: an investment bank interview in a dingy office with water literally dripping from the ceiling, two computers with no mouse, and an interviewer asking, “How do you feel about sleeping under your desk?”

On the other side: a Deloitte floor full of bright lights, color, twenty-somethings solving problems together. The feeling that “if you are smart and have a personality, you go here.”

He chose Deloitte.

The first three years were an operations boot camp: target operating models, big transformations, messy execution, the next three became a strategy boot camp: growth, corporate and competitive strategy inside Monitor. Brian came out with a very particular blend: half “how to run a business,” half “how to grow a business.”

The turning point, though, was not a promotion. It was that PPP project during COVID.

A major US bank was failing to get PPP loans out the door, and Deloitte’s name was on the line. The project was on fire, so Brian was parachuted in as “the strategist who can actually turn things around.”

They fixed it. Hundreds of people on the project. At the end, the partner pulled him aside and said: “Brian, you single-handedly turned this project around. Thank you.”

Then handed him a gift card. The cognitive dissonance did the rest…

He did not suddenly become “confident.” He was already overconfident by his own admission, but what changed was the question in his head:

If I can create this much value in someone else’s system… can I do it outside the umbrella? Or am I only valuable with a big logo behind me?

That question has been driving him ever since.

Edge

Brian’s edge is simple to say and hard to live:

He is obsessed with solving hard problems, not with preserving his comfort zone or maximizing short-term margin.

He believed, naively but usefully, that if he could operate inside giant complex organizations, then small businesses would be easier.

“These companies are so complex, they must be the hardest things to build,” he thought. “If I can do this, a small business must be easy, right??”

Wrong.

He discovered that his “how to run a business” skills translated well. Systematizing processes, designing operating models, thinking in people / process / tech – that stuff ported nicely.

His “how to grow a business” skills did not translate at all.

In big-corp strategy, growth questions sound like:

• “Do we launch an investment bank in Brazil?”

• “Which products do we roll out in Mexico?”

• “Do we build or buy?”

You think like an investor. You allocate capital. You speak in markets, curves and scenarios.

In a small business, growth sounds like:

• “How do we get someone to click this ad?”

• “How do we build the first funnel that actually converts?”

• “Which channel do we test this week with fifty bucks?”

You think like a scientist in a lab. You run experiments. You learn tactics that no boardroom ever mentions.

Brian discovered he knew nothing about that layer and had to learn from zero.

He also learned how deeply “brand permission” matters. Strategy is interesting to founders only after they hit roughly eight figures. Before that, they do not want your slide about UBS; they want someone who can get leads in the door. His early positioning as “growth strategist” did not resonate. To many small businesses, “strategy” is a luxury item.

In parallel, he accidentally built a high-margin solo business: CMO-style advisory for companies big enough to care about proper marketing systems. Three clients, ten hours a week each, $10k–$20k per month per client, and the rest of the time spent on marketing and content. Very good money for a very light calendar!

But it did not scratch the itch. He wanted to build something real, with people, processes, tooling, and compounding assets, so he leaned into the emerging second business: a recruiting and staffing agency that helped companies find remote talent – customer support, customer success, project managers, and so on. Lower margins. Much more operational headache. Far more scalable. And far more satisfying to him.

The agency now gets ~3,000 applicants per role, has placed 115+ people, and is layering AI across the funnel: from resume screening to an AI interviewer that speaks with candidates and shortlists them.

His girlfriend (and co-founder) is the CTO and builds the AI systems. Brian designs the systems and the offers and then sells them.

He is consciously choosing the harder route.

“If I wanted to make the most money, I would focus on the CMO work. But I had to know if I can build, not just advise. I am making less money doing this than I did in marketing, and I still do not regret it.”

Where does this approach hit limits?

When you confuse mental models from phase three (big corporates, maintain and optimize) with phase one (find product market fit). When you start by building the website instead of talking to the customer. When you assume the “smart slide” is enough, instead of learning how to write a brutal, ugly ad that actually converts.

Future

Brian sees AI not as magic, but as a pipeline with 3 stages:

1. Human takes real-world context and asks the AI a question.

2. AI produces an answer.

3. Human verifies, interprets and connects that answer back into the real world.

AI will dominate stage two. Stage one and three are where humans still matter. Which means the “translation layer” job becomes even more important.

That is the same job the best consultants already do.

He remembers a classic boardroom scene in a big bank during one of his projects. Fifteen executives shouting across the table. Everyone talking past each other. A partner walks up to the whiteboard, draws three boxes, and says:

“You are all talking about this. We actually need to solve this.”

Silence. Alignment. Movement.

The value is not the slide! It is the ability to name the real problem.

Brian’s view is that banking executives who are brilliant at credit cards business but average at problem framing will ask AI the wrong question, in the wrong way, at the wrong time. They will get answers that are precise, fast, and useless.

Consultants are, in his words, the translation layer between subject-matter experts and clarity. And between messy organizational politics and clean decisions.

He sees AI accelerating execution work in consulting – research, modelling, standard analysis – but not replacing the framing and synthesis. If anything, the bar goes up: when research becomes cheaper, you run more tests, you validate more options, and the expectation for quality rises.

On white-collar work more broadly, he is blunt. He likes the framing of AI as “Amplified Intelligence”:

If you are already sharp and high agency, this is an incredible time. The tools give you more leverage than ever. The gap between thought and reality shrinks. You can think something in the morning and have a working version in the afternoon.

If you are average, AI will make you average at scale.

If you are bad at what you do, you are finished.

He also thinks the classic “safe” corporate path is much riskier than it used to be: roles that felt solid can dissolve under you.

If he had to advise his younger self, he would not say “skip college” in some generic hustle-porn way (he knows he needed structure and consulting to learn how to problem solve), but if the goal was entrepreneurship, he would not tell 20-year-old Brian to “go start something from scratch.”

He would tell him to go and work for one rock-star entrepreneur. Hitch himself to someone exceptional, learn at high compression, and build skills, network and resources before striking out.

Grounding and Legacy

Brian’s lifestyle looks chaotic from the outside: fully nomadic, new country every one to two months, no fixed home base, Mexico, Rome, Sicily, Sydney, Tokyo are all just coordinates in a calendar.

His day, however, is brutally simple.

• He wakes up as early as he can.

• He gets to work as fast as he can.

• He works until his energy drops.

• Then he walks, lifts, or stares at a problem until he finds a way through.

• Then he gets back to work.

He is not trying to minimize working hours. He is trying to maximize time spent wrestling with hard problems.

He uses the gym as a 3pm reset button. When his output drops, he moves his body to recharge his brain. He walks to consolidate ideas. He uses music intentionally as a state-changing tool: high-energy when he needs to push, focus tracks or binaural beats when he needs to dive deep.

At night he reads in Italian until he falls asleep, because he plans to go back to Rome and actually hold his own at the dinner table.

He jokes about solving problems in his sleep, but beneath the joke is a serious pattern: his life is built around mental challenge, and the geography is just a backdrop.

When asked what he would do with unlimited time and unlimited resources (a question I always like to float), he does not say “start a fund” or “buy a sports team.”

He wants to attack a hard social problem with the same caliber of talent that currently swirls around hedge funds and big tech.

Violence in South Side Chicago. Food deserts and hunger. Civic problems that have chewed through committees and foundations for decades.

What bothers him is not the lack of money, but the lack of concentrated IQ and problem-solving intensity dedicated to these issues. He would like to bring a band of killers together (the smartest operators and problem solvers he knows) and aim them at one of these problems until it cracks.

He is self-aware enough to know he is not ready yet. He wants more skills, more network, more reps before he jumps in, but the direction of travel is clear: build real businesses now, so he can redirect those muscles later to something beyond his own bank account.

🔹 What you can steal

Treat yourself as the translation layer.

Your job is not to worship AI’s output. Your job is to take messy, contradictory real-world context, compress it into the right question, feed that into the machine, and then judge the answer against reality. Start every AI prompt with “What is the real problem here?” rather than “What can this tool do?”

Know which game you are playing.

Are you in phase one (find product market fit), phase two (scale what works), or phase three (maintain and optimize)? In phase one, you are a scientist in the lab, running cheap experiments and learning tactics. In phase three, you are an investor allocating resources.

Build at least one thing where the work compounds.

Advisory work is fine. It pays well. But copy Brian and choose at least one arena where you are building a system, a product, or an asset that you can improve every day and stand on tomorrow. Even if it is harder. Especially if it is harder. That is where your edge forms.

🔹 Maurizio’s Take

I like people who are slightly wrong first and then relentlessly right later…

Brian misjudged how hard small businesses are. He assumed a smaller version of a thing must be easier. He discovered that small business is a different physics, not a different scale.

He also refused to stay where life was maximally comfortable. He had a sweet setup as a high-margin advisor with light hours and good cash, and voluntarily walked into the operational meat grinder of an agency because he wanted to build something that exists when he is not on the call.

His edge is not “Deloitte background plus Spanish plus nomadic Instagram life.” His edge is the willingness to keep putting himself in rooms where he is under-skilled for the problem and then grind until he is not.

On AI and consulting, he lands very close to my own view.

Consultants who behave like deterministic machines are dead. Analysts who think their job is “running the template” are dead. The people who survive are the ones who can look at a room full of executives, a heap of data and a manic AI assistant and say:

“No. The real question is this.”

The more AI we get, the more that skill matters.

If you take one idea from Brian, let it be this: in a world of amplified intelligence, the only safe seat is at the problem-framing layer. Everything else can, and will, be automated, arbitraged or annihilated.

The rest is commentary.

👀 Where to find more about Brian

• LinkedIn

• X (formerly Twitter)

• TalentHQ - Brian’s resourcing and recruitment agency

If you enjoyed today’s conversation and read Consulting Intel, please do me a favor: share this post, spread the edge.

👋

⚠ Check these links out

• My first book Beyond Slides became a #1 Amazon Best Seller in the USA, UK, Australian and Italy;

• I recently met with , writer of the newsletter, for a long chat on a bunch of topics, from parenthood to career. If you are interested, have a look at the post!

  Decks and Diapers

  The Coffee Chat (#102)

  Welcome to the new subscribers who have joined us since the last post. Today this email is going out to 2,035 amazing individuals…

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  3 months ago · 2 likes · 4 comments · Rashi

• The Leaders Toolkit is a deck of 52 tools, frameworks and mental models to make you a better leader (use code CONSULTANT10 for 10% off);

• The Consulting Intel private Discord group with 250+ global members is where consultants meet to discuss and support each other (it’s free).

Typically, my heart rate would climb, and I would feel quasi-paralyzed by the fear that if I speak up, I will be “found out.”

It is a lonely, frustrating feeling that makes me feel like an idiot.

Have you been there too?

Judging by the amount of questions I get about this topic, the answer must be a resounding yes.

In the scenario I just described, you are standing at a fork in the road. You have a choice:

1. Stay silent: Protect your ego in the short term, but risk a costly, high-stakes mistake later because you didn’t truly understand the mission;

2. Speak up: Lean into the discomfort, reclaim the narrative, and steer the conversation back toward something clearer.

Successful operators know that asking for clarification is an important tool of high-level execution: when you ask the question everyone else is too afraid to ask, you are both helping yourself and leading the entire conversation.

This ability is, by the way, entirely learnable.

To help you navigate these moments with total confidence, I have curated 51 powerful questions categorized into 7 strategic frameworks.

You might already be asking a few of these questions as part of your regular style. Others are worth experimenting with in your next meeting. A few may simply point you in a direction that feels interesting or useful and, from there, you will likely end up crafting a version of the question that fits your own context better.

It’s all fine.

Use these ideas as you please: they may change the trajectory of your future meetings.

LFG!!!

Feel free to print the image below if you want to have all the questions in one place

1. The “Wide Lens” (General Clarification)

Pick one of these questions when the overall concept feels fuzzy and you need a high-level reset.

1. Could you say a bit more about that?

2. I’m not sure I follow. Could you recap that last point?

3. Could you elaborate on what you mean by [Term/Phase]?

4. I want to make sure I’m on the same page. Could you repeat that?

5. Could you provide an example of how that would work in practice?

6. Is there another way to describe that concept?

7. I think I missed a step there. How do we get from A to B?

8. Could you break that down into smaller parts for me?

9. Is there a visual or a diagram that helps explain this?

2. The “North Star” (Goals & Objectives)

Pick one of these questions when you understand what is being done, but not why it matters.

1. What is the primary problem we are trying to solve here?

2. How does this align with our overall goals for the quarter?

3. What would a “win” look like for this specific project?

4. Are we prioritizing speed, quality, or cost in this scenario?

5. What is the single most important takeaway from this discussion?

6. What are the “must-haves” versus the “nice-to-haves”?

7. Who is the ultimate decision-maker on this specific point?

3. The “Translator” (Technical & Jargon)

Pick one of these questions when the “alphabet soup” of industry speak is blocking the message.

1. For those of us less familiar with the technical side, how would you explain that?

2. Does [Jargon Term] mean the same thing as [Simple Term] in this context?

3. What does that acronym stand for?

4. Is that a standard industry term or something specific to our internal process?

5. Could you define how we are using the word [Term] today?

6. Is there a non-technical metaphor that describes this process?

7. What is the “layman’s terms” version of that requirement?

4. The “Mirror” (Confirming Understanding)

Pick one of these questions when looking for the most effective way to ensure your mental model matches theirs.

1. So, if I’m hearing you correctly, you are saying...?

2. Just to confirm, is the main point that...?

3. My understanding is [X]. Am I off base?

4. Are you saying that [Option A] is better than [Option B]?

5. If I were to explain this to my team, would it be accurate to say...?

6. Let me see if I’ve got this: [Brief Summary]. Is that right?

7. To clarify, you are asking me to [Action Item], correct?

5. The “Watchtower” (Risks & Constraints)

Pick one of these questions when you need to surface the hidden dangers in a plan.

1. What are the potential roadblocks we should be aware of?

2. Are there any dependencies we haven’t mentioned yet?

3. What happens if we don’t meet this specific deadline?

4. Are there budget or resource limitations I should keep in mind?

5. What is the biggest risk associated with this approach?

6. Is there a “Plan B” if this doesn’t go as expected?

7. What is the one thing most likely to derail this plan?

6. The “Architect” (Next Steps & Accountability)

Pick one of these questions when the meeting is ending, but nobody knows who is doing what.

1. What are the immediate next steps after this meeting?

2. Who is responsible for [Action Item]?

3. When is the hard deadline for this deliverable?

4. How will we measure the success of these actions?

5. What do you need from me/my team specifically?

6. When should we expect the next update on this?

7. Is there a shared document where these tasks are being tracked?

7. The “Deep Diver” (Context & Background)

Pick one of these questions when you need to know the “story” behind the decision.

1. What led us to this specific conclusion?

2. Have we considered how this will impact [Other Department/Project]?

3. What is the history or context behind this decision?

4. Are there any alternative options we have already ruled out?

5. Who else needs to be informed about this before we proceed?

6. How does this change our current workflow?

7. Is there any background reading you recommend so I can get up to speed?

The Golden Rule (if you are still not convinced): If you are confused, at least 3 other people in the room are too!

All the best. Share this post with a friend or a colleague who may need it, and go practice!

As usual, if you enjoy reading Consulting Intel, please do me a favor: spread the word and share this post.

👋

👀 Links of interest

A few corners of the internet you may find interesting:

• My first book Beyond Slides became a #1 Amazon Best Seller in the USA, UK, Australian and Italy;

• I had the opportunity to be an advanced reader for the upcoming book by my friend Kevin Ertell The Strategy Trap. He has done an excellent job at simplifying an otherwise complex subject, that people with decades of experience still do not understand. The book is well researched (which I like) and full of relatable stories. Follow Kevin Ertell and his newsletter The Strategy Trap Newsletter!

  

• Have you looked into the Leaders Toolkit? It is a deck of 52 tools, frameworks and mental models to make you a better leader (use code CONSULTANT10 for 10% off);

• The Consulting Intel private Discord group with 250+ global members is where consultants meet to discuss and support each other (it’s free).

Big podcasts and large publications chase Bezos-level names who talk about strategy from 30,000 feet: it’s inspiring, yes, but useless if tomorrow you are walking into a meeting with your client and a deck to defend…

EDGE, a format by Consulting Intel, is where I sit down with operators, consultants, and investors working between business, tech, and AI… and where I distill what I learn in something you can read in ~7 minutes.

LFG! 🔥

Venture capital looks glamorous until you notice the people doing the real work: the ones who do not confuse power with wisdom.

Tak Lo is one of those people.

From the U.S. Army into defense consulting, then a MBA at London Business School, Techstars London to the Zeroth AI accelerator, to then end up running multiple funds across AI and crypto, and finally working as a teacher of kids and MBAs.

The resume is long, and the philosophy is sharper.

The contrarian hook for you: Tak treats founders not as “customers,” but as assets you must steward exceptionally well, while recognizing the actual customer is the LP. And he believes the best VC help is 1% well-timed framing… and 99% getting out of the way.

He is, in his words, a financier and a teacher. That pairing, capital allocation with ethical scaffolding, turns out to be rare, and useful.

Let’s jump into the conversation!

Origin Story

Born in Hong Kong, raised across the U.S. and Asia, Tak started in the U.S. Army, shifted into defence consulting, then jumped the fence into startups via LBS and Techstars.

The Army gave him discipline and a blueprint for leadership under uncertainty; consulting gave him the habit of turning chaos into frameworks.

The turning point was not a single blow-up but a slow realization: power warps judgement. In venture, lines blur at late dinners, hot rounds, thirsty egos. Without boundaries, the job will bend your ethics and your calendar until both snap.

That is when he chose a different posture: measured, coach-like, harder to corrupt.

The belief that stuck: intellectual work > interference.

You do not rescue entrepreneurs by becoming their part-time COO. You strengthen them by helping them see, decide, and own.

Edge

Tak’s edge is deceptively simple: allocate capital; allocate attention even more carefully.

He optimizes for two scarce resources in startups:

1. founder focus;

2. ethical clarity.

The first is protected by eliminating performative “value-add”, the second is protected by hard personal rules about time, settings, and power dynamics.

He is blunt about it: the startup founder is not the customer. The LPs who supply capital are. The founder is the asset (the horse you train, care for, and keep healthy) because without that, there is no return.

Confusing the two creates distorted behavior: overhelping, overpromising, or worse, forgetting who actually pays the bills.

His second differentiator is a refusal to operate.

Many VCs drift into acting like part-time executives. For Tak, that is a trap.

99% of the time, the right move is to get out of the way. The 1% is about timing: a frame at the right moment, a push when a founder is on the cusp, an introduction that shifts probability. He tells the story of a peer who held weekly check-ins lasting only 15 minutes, asking two questions: “Did you move the needle?” and “What were your 10x decisions?”

That is the essence of his method: cut through the noise, surface what matters, and walk away.

The discipline comes from the Army (“calm in the fog of war”) and consulting (“frameworks that simplify the mess”). The empathy comes from coaching over a hundred founders across geographies and industries.

His edge is not sector depth, but breadth, resilience, and consistency. He is not the guy who claims to know SaaS sales better than you; he is the guy who will stand in your corner when your world is falling apart, unshaken, asking sharper questions than you dare ask yourself.

Where it succeeds: with resilient CEOs who need a steady hand and a reframed question, not an extra operator in the room.

Where it fails: in companies where the business model itself needs surgery. Tak will not be your interim CRO, and he is fine with that.

Future

On AI, Tak is boring in the best way: ubiquity beats hype. Like the calculator and the PC, AI will be everywhere, but the marginal impact is bigger, faster, and riskier.

He compares it to the printing press and the computer, but with one critical difference: the slope of change is steeper. Generative AI is “the Internet’s knowledge at your command.”

That is power, and danger.

What worries him is not the technology but how humans use it. He teaches AI at schools and universities, and even to his kids’ classmates. His focus is on helping young people learn how to work with AI without outsourcing their thinking to it.

“The Economist wrote that Gen Z can’t think without AI,” he says. “That is the danger. If kids start every question with, ‘Let’s see what AI says,’ then they stop exercising their own mental muscles.”

He argues for installing ethical principles and approaches early. Just as it took 15 years to regulate social media, we cannot afford to sleepwalk into the same mistakes with AI. His mission is to buffer kids’ minds so they can harness AI, but with skepticism, patience, and sovereignty.

Who thrives: operators who can hold two truths at once: use AI relentlessly, but retain independent thinking.

Who disappears: those who abdicate all cognition to prompts.

I always ask a question to my guests. What would you suggest to your younger self? Tak answer is remarkably cool: be ferocious on the daily, but relaxed on the arc.

“Bring effort daily. Zoom out monthly. Let it all work out.” He borrows from football to illustrate: players cut at 12 who rejoin the team at 25, because grit plus time eventually repays.

His own career, jagged as it looks, is proof of that rhythm.

Grounding and Legacy

Sundays in the Lo household are sacred: no nanny and no plans! Boredom is intentional.

There is rugby in the morning, board games, and an Italian kitchen in the afternoon: pomodoro (tomato sauce, for the uninitiated) simmering, guanciale on standby, baked pasta that would pass in Palermo.

Weeknights aim for family dinner, debriefs of high/low moments, and the kind of repetition kids turn into roots.

If Tak had unlimited time and capital, he is very clear on what he would do. He would own a sports team, either an innovative new-sport franchise or a community club in Italy!

Not just for football. For community as a practice: showing up, building belonging, earning dinners. This is the through-line: teach, anchor, compound.

Wealth as stewardship plus power with boundaries.

🔹 What you can steal

First, adopt the 15-minute needle test.

Weekly, ask yourself or your team: “What truly moved the needle? What were our 10x decisions?” Then stop talking. If you cannot name them, you did not have them.

Second, separate customer from asset in your world.

Who actually pays you? Who must be stewarded? Treat both with respect, but optimize for the right one. That single clarification eliminates half of your political confusion.

Third, install ethical guardrails before you need them.

Decide in advance which meetings you will not take, which hours you will not cross, which behaviors trigger a hard stop. Boundaries are easier to keep when they are written, not improvised.

🔹 Maurizio’s Take

Tak’s edge is restraint with teeth.

In a scene addicted to hands-on meddling and “value-add performance”, he chooses calm framing, hard triage, and moral hygiene.

It resonates with my own view of leverage: real leverage is removing noise, not adding interventions (when in doubt, always go via negativa).

What I find powerful is how his approach in venture capital mirrors what good consultants do in boardrooms. The best consultants do not try to run the client’s business for them. They frame problems sharply, and leave the ownership where it belongs. Tak has simply carried that operating logic into venture.

The other thread worth noting is his obsession with teaching. Whether AI to 10-year-olds or frameworks to CEOs, the through-line is the same: give people mental frameworks, not answers. That is rare in finance, an industry that often rewards opacity. His edge is to make things clearer, not more complex.

There is also something refreshing about his candor on ethics. Many investors talk about returns, few talk about self-awareness at 2am dinners. Tak does. In a field that excuses questionable behavior in the name of deal flow, that matters. He is right: without hard boundaries, power will warp even the most principled operator.

For me, the takeaway is important: the more powerful your tools (capital, AI, title), the more disciplined your boundaries must be. Otherwise the tool starts using you.

One thing I will take with me from the conversation with Tak is that, in a world racing to do more, the scarce advantage is the leader who knows exactly when not to touch the system, and can prove it with outcomes.

👀 Where to find more about Tak

• LinkedIn

• X (formerly Twitter)

• The Automated newsletter

• Tak’s book: I, Leader: Leadership Philosophy from the Army and Startups for the Age of AI

• Website

If you enjoyed today’s conversation and read Consulting Intel, please do me a favor: share this post, spread the edge.

👋

⚠ Check these links out

• My first book Beyond Slides became a #1 Amazon Best Seller in the USA, UK, Australian and Italy;

• I had the opportunity to be an advanced reader for the upcoming book by my friend The Strategy Trap. He has done an excellent job at simplifying an otherwise complex subject, that people with decades of experience still do not understand. The book is well researched (which I like) and full of relatable stories. Follow and his newsletter !

  

• The Leaders Toolkit is a deck of 52 tools, frameworks and mental models to make you a better leader (use code CONSULTANT10 for 10% off);

• The Consulting Intel private Discord group with 250+ global members is where consultants meet to discuss and support each other (it’s free).

Big podcasts and large publications chase Bezos-level names who talk about strategy from 30,000 feet: it’s inspiring, yes, but useless if tomorrow you are walking into a meeting with your client and a deck to defend…

EDGE, a format by Consulting Intel, is where I sit down with operators, consultants, and investors working between business, tech, and AI… and where I distill what I learn in something you can read in ~7 minutes.

LFG! 🔥

If you have ever sat through a “strategic re-org” that felt like a very expensive reset button, this one is for you.

Mitch Morris argues you can build a company that never needs that ritual, not because everything gets fixed magically, but because you wire learning into the bones from day one.

That claim grabbed me.

I wanted a practitioner, not a theorist. Mitch has rebuilt universities’ tech stacks, shut down and sold companies, and spent decades in the weeds.

He is suspicious of performative acts, allergic to bureaucracy, and oddly serene about complexity, because he treats it as a system, not a story.

Here is the hook: three pillars to run any organization, a continuous loop that prevents periodic implosions, and a ruthless focus on throughput over optics.

If you lead a team, advise one, or aspire to, you will walk away with a lens you can deploy immediately, and a contrarian idea worth testing: perhaps re-orgs are a tax you pay for not iterating fast enough.

Set-up.

Mitch is a principal advisor at Conrad Alois, ex-CIO, serial founder (8 companies; 4 active), angel since ’98, adjunct professor at Cal State San Bernardino, and co-founder of Inkind Thrift, a thrift store and sustainability venture funding a local nonprofit foundation in Chino, California.

His thing: operational simplicity, continuous improvement from day one, and frameworks that actually work because they start from first principles.

Let’s jump into the conversation!

Origin Story

Mitch did the time in the trenches: PC technician to CIO, then founder.

Some wins, some shut-downs, one very expensive lesson in 1997 that cost him $50K to close. He says it taught him more than his MBA ever did. It also shaped a simple belief that runs through everything he does: operations rhyme across industries. The product changes, but the load-bearing processes do not.

That view translates into how he teaches.

He is the “unlearning” professor, taking students from tidy lecture-hall linearity to the confusing and chaotic execution.

Strategy, for him, is not a slide but a loop: start → learn → adjust → continue. If you do that from the beginning, you do not need yet another re-org at $10m, $50m, $250m, or whatever milestone. You just keep evolving the organism.

Edge

Two frameworks sit under his work: Foundational Thinking and the SIMPL method.

Foundational Thinking

At its core this is Mitch’s attempt to translate first‑principles thinking into the complex world of business operations.

Instead of treating strategy as a grand linear plan, he frames it as an iterative cycle: you start, you encounter friction, you adjust, you continue. That cycle is the foundation.

In practice, it means getting brutally clear about the problem at hand, naming the work that must be done, and breaking it into milestones that can be started immediately. Progress then becomes an act of disciplined iteration rather than waiting for a perfect plan.

His contention is subversive: if you wire this continuous learning process into the company from day zero, you do not need to periodically rip out and rebuild the organization at every growth stage. The re‑org, in his eyes, is a symptom of neglecting iteration.

Foundational Thinking demands humility (the willingness to admit you do not know everything upfront) and merciless follow‑through, because business will always expose new checkboxes that spawn more work.

The framework insists you move anyway, compounding small corrections rather than freezing for the illusion of certainty.

The SIMPL Method (Simple Innovation Management Practice for Leaders)

Not yet fully published, but the bones are clear. A CEO should have only three direct reports, mapped to three irreducible pillars:

1. Brand (including Sales & Marketing),

2. Operations (finance, tech, the plumbing),

3. Product/Service Delivery (even services treated like products).

Strip away the ornamental boxes, and design to reduce ambiguity. Build an organization that is “always sufficient and responsive.”

Where this gets interesting is failure.

Mitch does not pretend frameworks are autopilot. The failure mode is seldom the model but the manager.

Two firms, same product, can yield diverging outcomes because the executive’s judgement, appetite for reality, and willingness to loop fast are different. The work, then, is as human as it gets: establish a common language (“where are we, where do we want to be, what is the gap?”), reduce fear by making progress legible, and keep it moving.

He illustrated this with concrete stories at both ends of the spectrum.

On one side, a retail-service startup led by two brilliant scientists (a psychologist and a bioengineer) with almost no business acumen. They had ambition and budget, but no frame for how to start. Mitch broke it down into visible steps, forcing them to think five years ahead while still acting today.

On the other side, a $200m company where the CFO controlled five departments and choked the flow of information to the CEO. There, Mitch reframed the conversation for the board, built a common language, and mapped the gap between present state and desired future state.

Different scale, same playbook: create clarity, expose the gap, decompose the work, iterate. He is allergic to theater. He is addicted to throughput.

On specialist vs generalist, we sparred.

I argued specialists still need the same meta-skills (eg, framing, persuasion, translation). He agreed the market punishes narrow technicians who cannot explain or own consequences. He has seen too much of the cleanup work from “smart” specialists who yank one lever and break three others...

Future

We had to talk about AI.

Mitch’s view is blunt: it will vaporize the regurgitators. In SMB land, that is most of the “consulting/coaching” market, people who sell compiled internet advice. That tier becomes a commodity bot.

The winners - he believes - will be practitioners with real scars who can (1) query machines well, (2) fuse best-practice with belief, and (3) show up for implementation.

He predicts a return to old‑school consulting, with sleeves rolled up, embedded and accountable.

In his view, AI will wipe out the tier of advisors who simply recycle frameworks and produce decks, because clients will get that from machines at zero marginal cost. What cannot be automated is the credibility and stamina required to sit in the trench with a client and shepherd the execution. That is what old‑school meant: partners who did not just advise from the sidelines, but who carried risk, fixed the plumbing, and saw the plan through to impact.

If he were 22 today, he would join a boutique under a killer operator and learn by exposure, instead of spending three years buried in a 50-person workstream. He recalls that his own career accelerated because a mentor threw him into client meetings at 24, let him make mistakes, and forced him to own them in front of executives.

That exposure (ie, the apprenticeship model) is what he believes will matter even more in the AI era, when analysis and decks are commoditized.

Grounding and Legacy

Mitch spoke to me about the years he spent in martial arts (everything from Tai Chi to full‑contact MMA) and how those disciplines left him with injuries that now prevent sparring but gifted him something more enduring: the internal practices.

Daily meditation, slow intentional movement, and the focus on breath: these, he says, keep him grounded. The manual projects (fixing cars, laying tile, lifting weights) are not just hobbies but counterweights. In consulting and executive work, outcomes can take quarters or years; in manual labor, you see the result instantly.

That fast feedback loop is an antidote to the glacial pace of organizational change, and a reminder that progress can still be tangible, immediate, and personal.

If time and money were unlimited, he would build trade‑school‑style entrepreneurship schools where tuition doubles as seed capital and learning happens by shipping.

Mitch described a vision where students would pay $20,000, and instead of it being sunk tuition, that sum becomes their starting capital. The program would throw them into the act of building (not only theorizing) supported by mentors who had actually done it before. The school would combine the grit of a trade program with the creativity of a startup accelerator.

For Mitch, this is about access more than pedagogy. He wants people who believe entrepreneurship is “not for them” to experience that it is! It blends his philanthropic streak (already visible in his thrift‑store foundation model) with his obsession for practice over theory.

His ideal classroom is not a lecture hall but a workshop where students learn by risking, doing, failing, and adjusting in real time.

🔹 What you can steal

Ship your own Foundational Operating Loop.

Day one of any engagement:

Start by naming the present as it really is. Then name the desired state in words the board can actually repeat without jargon. Expose the gap between the two in plain daylight, and convert that gap into a visible worklist with owners and feedback cadence. Then move. Quick progress creates belief, and belief is the only currency that buys you the next lever.

Simplify your org lens to three pillars in discovery and exec comms: Brand, Ops, Product/Service. If an issue does not map to one, you are probably naming symptoms, not causes. This also kills vague debates. “Is this a sales problem?” becomes “Is this a Brand problem (positioning/pipe), an Ops problem (pricing/finance/tech), or a Product problem (quality/fit/cost-to-serve)?”

Treat soft barriers like any other risk, and operationalize everything: “What is the fear/assumption? Where are we now? Where do we need to be? What is the smallest action that tests the fear?” Put that in the tracker like you would a tech dependency. Humans move when the next step is real and safe.

And if you manage people: think of three directs as a feature. Anything you cannot place under Brand, Ops, Product is either duplication or drift.

🔹 Maurizio’s Take

Mitch’s edge is discipline.

Where many consultants try to dazzle with clever slides and intellectual fireworks, he insists on operational gravity, which is the force keeping the rocket on trajectory when the launch hype has faded.

That distinction is very important: novelty fades quickly in boardrooms, but discipline lasts for far longer.

His frameworks are not designed to impress but to survive in the complex realities he has lived through. They are useful only if they accelerate decision‑making, when managers are stuck between imperfect choices. In my reading, SIMPL and Foundational Thinking pass this test because they reduce degrees of freedom and remove options: in that reduction lies speed, clarity of execution, and resilience over the long haul.

The contrarian bit I loved: the claim that if you wire continuous improvement from day zero, you may never need the dramatic “new org design” performative acts.

That goes against the deeply embedded religion of the periodic re-org, where leaders perform a ritual reset to signal control or progress.

Mitch’s argument is more intelligent: most of those sweeping redesigns are nothing more than a very expensive way to admit you stopped learning along the way.

In his view, and it matches what I have seen, every “big-bang” transformation is a hidden tax on leadership attention and organizational trust, basically a giant detour that could have been avoided with smaller and more disciplined adjustments.

The cost is in money, momentum, morale, and credibility.

Continuous iteration may not be as glamorous, but it keeps the company alive and adaptive without the disruption exercise that eats years of progress.

👀 Where to find more about Mitch

• LinkedIn

• X (formerly Twitter)

• Foundational Thinking method

• The SIMPL method

• Conrad Alois

• Website

If you enjoyed today’s conversation and read Consulting Intel, please do me a favor: share this post, spread the edge.

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⚠ Check these links out

• My first book Beyond Slides became a #1 Amazon Best Seller in the USA, UK, Australian and Italy;

• The Leaders Toolkit is a deck of 52 tools, frameworks and mental models to make you a better leader (use code CONSULTANT10 for 10% off);

• The Consulting Intel private Discord group with 250+ global members is where consultants meet to discuss and support each other (it’s free).

Valuations are clearly running ahead of realized value: anyone who has lived through dot-com, Web2, crypto, or even the early cloud years can smell that part from a mile away.

Capital always arrives before productivity shows up on the P&L.

However, I believe another thing to be also true: calling it just a bubble misses what is being built underneath.

If your only exposure to AI is ChatGPT as a clever autocomplete machine, I understand the skepticism. ChatGPT does feel incremental, cute even, a nice productivity hack more than a civilizational shift.

The picture looks very different once you see agents wired into real systems: databases, browsers, internal tools, Auth, workflow engines. Engineers playing with these setups already know the bottleneck is no longer “can the model do this?” but “are we brave enough to give it access?”

That is an important distinction, and it also explains why the commercial story looks confusing right now.

Microsoft has reportedly cut sales targets for its agentic AI software by as much as 50%. Copilot, despite the distribution advantage, is struggling to convert curiosity into conviction. Internal tests earlier this year showed AI agents failing to complete tasks up to 70% of the time.

While I do not necessarily see that as hype collapsing, I do think this is immaturity being exposed.

When agents sit at the edge of the system, failure is annoying, but when they sit inside the system, failure is existential, and so no CIO is going to green-light broad access when error rates still look like that.

This, inevitably, also shows up in market share.

ChatGPT commands roughly 61% of usage. Google’s Gemini sits around 13%, but is growing fast. Microsoft’s Copilot is hovering around 14%, despite being embedded everywhere from Outlook to Teams.

Distribution alone seems not to be enough. Reliability and trust matter more.

We are in an awkward in-between phase: capabilities are compounding (very) fast, infrastructure is being laid even faster, but value creation always lags, because organizations (especially large ones) are social systems, not codebases. Trust, security, governance and incentives move at human speed, not GPU speed.

History is boringly consistent on this point.

Banks, for example, still run on COBOL (there are still an estimated 220,000,000,000 lines of COBOL in use worldwide): this happens not because COBOL is a particularly elegant language, but because IT WORKS, and the downside risk of change is asymmetric.

Large institutions optimize for survival first, innovation second. “If it ain’t broke don’t fix it” is not stupidity but basic risk management.

Adoption will be uneven, slower than Twitter thinks, but faster than most executives expect.

I am not convinced we are staring at mass unemployment tomorrow. In my view, the more interesting question is whether expectations for products and services simply explode. If every firm can build 3–4x more, does that mean fewer jobs… or just a much higher bar for what “good” looks like? Are we staring at the modern instance of Jevons paradox, as I discussed in this LinkedIn post?

My instinct is that we will automate away mediocrity long before we eliminate ambition.

Average, low-leverage roles will feel the pressure sooner than people want to admit, while highly capable operators will be asked to do far more.

That gap matters.

The real constraint right now is permission, secure access, enterprise-grade guardrails, comfort with delegation to machines. Those things take time to socialize, standardize and regulate, but when they fall into place, value creation will catch up with valuations.

Not all at once. Not evenly. But decisively.

There is froth. There always is.

However, beneath it, something structural is happening, and once you see agents doing real work inside real organizations, it becomes very hard to dismiss this as just another hype cycle.

We have seen bubbles before.

We have also seen what survives after they burst.

As usual, if you enjoy reading Consulting Intel, please do me a favor: spread the word and share this post.

👋

👀 Links of interest

A few corners of the internet you may find interesting:

• I have been working on a small project……. EDGE, a format by Consulting Intel, is where I sit down with operators, consultants, and investors working between business, tech, and AI… and where I distill what I learn in something you can read in ~7 minutes.

  

  IT IS COMING SOON on Consulting Intel!

• In this post on X (which kind of went “viral” and got over 1,000 bookmarks), I articulate 5 actionable tips to uplift your communication and presentation skills:

  

• Have you looked into the Leaders Toolkit? It is a deck of 52 tools, frameworks and mental models to make you a better leader (use code CONSULTANT10 for 10% off);

• The Consulting Intel private Discord group with 250+ global members is where consultants meet to discuss and support each other (it’s free).

“How do you find the time to write so much on LinkedIn?”

What surprised me the most was not the curiosity per se, but the fact that people assumed it takes ages.

It does not!

It’s embarrassingly quick: the secret is not talent or discipline, but having the right operating system.

I post twice a week, Tuesday and Thursday at 8pm, and everything is scheduled in advance. On Sundays I’ll sit down for an hour and write four or five pieces, plus, when inspiration hits during the week, I top up during the commute or (weirdly) while lying in bed before falling asleep.

I always keep a queue loaded in the scheduler, so there is no “Oh god I need to post today” panic. When my posts go live, I am neither physically nor mentally there.

That’s why I say that posting is the easy part - the actual work happens before the writing.

I have built a note-taking and thinking architecture over the years. Without that, I’d be dead, but with it, writing feels like breathing.

(FYI - I have discussed this topic also in this post where I explained the process I followed to write and publish “Beyond Slides”)

Two tools run my whole system: Readwise Reader and Obsidian.

1. Reader is where every interesting piece of content goes: podcasts, YouTube videos, articles, books, newsletters, anything. I batch-read early mornings or evenings, usually 30-minute chunks, and while I read, I highlight aggressively. Everything I highlight automatically gets exported into Obsidian.

2. Obsidian is the brain that includes rough drafts, spontaneous thoughts, scribbles, quotes, hooks, this Substack draft started there. From that mess, the posts organise themselves.

Once you have a steady stream of insights flowing into your system, writing turns into connecting dots. It becomes memory retrieval and processing.

Now… if you combine that with a natural inclination for thinking and writing, you suddenly look prolific when, really, you are just very methodical.

When my colleagues asked, I decided to time the posting process.

How long does it take to write, clean, and schedule two posts on LinkedIn?

Less than 30 minutes. Total.

I was myself surprised!

LinkedIn right now feels like an untouched goldmine: I still don’t know what the gold is exactly, but it’s there. If I mine it for 30 minutes a week, and people tell me “You’re everywhere in my feed”, I’m starting to sense there is some leverage to get extracted from this platform.

OK, maybe I’m lucky.

I just don’t have the “Netflix and collapse on the couch” gene. My relaxation is reading and writing: this is simply what calms me down. ChatGPT has made everything faster: grammar cleanup, articulating half-formed thoughts, sanity checks and all. I use it as a companion rather than a crutch.

What I have realised is that writing benefits me externally, yes, but also sharpens my thinking, makes me better at my job, forces reflection and, perhaps most importantly, slowly builds an incredible global network of like‑minded people who think, read, and create in ways that resonate with me. I cannot articulate exactly how, but I feel this is an asset in the making.

(After all, it cannot be simply by chance that Leonardo, Seneca, Machiavelli, Benjamin Franklin, Isaac Newton, and so many more brilliant thinkers where also writers!)

If you want to write more, don’t start by forcing yourself to stare at a blank screen. The goal should not be to “find time”, but to remove friction so ideas flow on demand.

Build a system that feeds your brain.

Clear writing is clear thinking, and clear thinking is your competitive edge in the industry.

Let me put it bluntly.

Public writing is asymmetric leverage, because it manufactures surface area for opportunities while building you intellectual equity.

And while I cannot yet put numbers on it, I already see it: unexpected relationships, deep conversations with people I would have never met, invitations for collaborations, messages from partners across continents.

Tiny ripples that hint at tectonic shifts.

We are moving into a world where reputations matter more than résumés, where networks exceed hierarchies, and where signalling clarity becomes a career accelerant. Writing forces you to confront your own mind, and the world rewards people who think in public.

Here is the only real call to action I have for you:

Try writing 100 words this week.

Not for likes, not for validation, not for “brand”.

Do it for your own clarity.

As usual, if you enjoy reading Consulting Intel, please do me a favor: spread the word and share this post.

👋

👀 Links of interest

A few corners of the internet you may find interesting:

• I have been working on a small project…….

  Big podcasts and large publications chase Bezos-level names who talk about strategy from 30,000 feet: it’s inspiring, yes, but useless if tomorrow you are walking into a meeting with your client and a deck to defend…

  EDGE, a format by Consulting Intel, is where I sit down with operators, consultants, and investors working between business, tech, and AI… and where I distill what I learn in something you can read in ~7 minutes.

  

  IT IS COMING SOON on Consulting Intel!

• Have you looked into the Leaders Toolkit? It is a deck of 52 tools, frameworks and mental models to make you a better leader (use code CONSULTANT10 for 10% off);

• The Consulting Intel private Discord group with 250+ global members is where consultants meet to discuss and support each other (it’s free).

Then my hair started thinning. It sounds stupid, but it changed something.

There is a moment (every man knows it) when you see more scalp than you are ready for. That moment humbles you, and it forces you to rethink how you move through the world.

At first it made me self-conscious. Then it made me intentional. Later on, it rewired how I speak.

Today, before I say anything - especially in negotiations, partner meetings, or tense client moments when someone throws a little jab masked as “feedback” and you want to punch that person in the face - I pause and ask myself a boring (but lethal) question:

“Would the comment I am about to say help me get what I want from this conversation?”

Most people speak to protect their ego or to score points, or perhaps because they cannot tolerate the empty space between their ears. Funny enough, I used to be one of them, until I realized that people win arguments and still screw up outcomes all the time.

When King Pyrrhus of Epirus defeated the Romans at Heraclea and again at Asculum, his generals praised him. They said he had outsmarted Rome, humbled them, proven his strategic genius.

Pyrrhus famously replied:

“Another such victory and we shall be utterly ruined.”

He had won the argument (twice, actually), but each win costed him the very things he ultimately wanted: power and survival.

It is the old version of what we see every day in boardrooms and inboxes:

People who would rather win the point than win the outcome, people who cannot leave a comment unanswered (even when victory is already secure), people who keep talking until they lose what silence would have protected.

Pyrrhus defeated Rome on the battlefield (you may have heard of the saying “Pyrrhic victories”), but ultimately Rome defeated Pyrrhus in the long run, because Rome knew when to shut up, regroup, and play the game that actually mattered.

Countless times, I have witnessed consultants and clients “win” a debate and lose the sponsor. I have watched managers prove a point and burn goodwill they spent six months building. I have done it too, many times.

The older I get, the more I see this pattern everywhere: the conversation is already going your way… and then you spoil it by adding a comment that is clever but destructive, true but unnecessary, emotionally satisfying but strategically idiotic.

I once worked with a guy who simply could not help himself: he needed the last word, every time. In conversations, in meetings, and even worse, over email.

As his manager, I would get copied into threads where the other person had already agreed to exactly what he wanted: the outcome was locked in! And yet he felt compelled to nitpick some irrelevant detail, just to feel 100% right.

Why would you sabotage a win like that? When did “being right” become more important than getting what you came for?

These days, I run a simple algorithm in my head:

Is my comment necessary? Will this move me closer to the outcome I want? Do these words actually need a reply, or am I just trying to be right?

Nine times out of ten, the answer is no: silence would be a cheaper option that would keep the door open.

It took me a decade and a receding hairline to understand this. And, if that is not enough, this helped me also to notice that the less I speak, the more people listen.

If you want to become better at influence, at negotiation, at consulting, at parenting, or pretty much anything that involves humans and egos, try this:

Do not say the thing just because it feels good. Say the thing only if it helps you get where you want to go.

As usual, if you enjoy reading Consulting Intel, please do me a favor: spread the word and share this post.

👋

👀 Links of interest

A few corners of the internet you may find interesting:

• I recently met Deri from to have a chat on my book Beyond Slides.

  It was a wide-ranging conversation where we unpacked a few skills every consultant needs if they want to stop being a slide-maker and actually master the profession, and why deliberate practice matters so much more than “experience” when it comes to communication, influence, and framing.

  
  Deri shared a few war stories from his Bain days, and we also answered some great audience questions (eg, how do you gain confidence with senior clients, how to interpret a 1-1 vs a formal governance session, how to build trust, etc)

  
  The webinar is now out, you can watch the whole thing below: enjoy!

  

• Have you looked into the Leaders Toolkit? It is a deck of 52 tools, frameworks and mental models to make you a better leader (use code CONSULTANT10 for 10% off);

• The Consulting Intel private Discord group with 250+ global members is where consultants meet to discuss and support each other (it’s free).

Crowds packed the grandstands to wager and witness the strange alchemy between animal, rider, and ground. Trainers and jockeys knew their horses intimately: how they breathed, how they carried weight, how their stride changed when the soil was damp or when the wind came sideways off the Downs.

Some horses flew down long, dry straights where the earth was firm and clean.

Others only came alive on tight, twisting circuits where timing and agility mattered more than brute force.

And some horses, despite being magnificent in appearance, collapsed into mediocrity at the first hint of mud.

After decades of watching champions rise and fail, a pattern became undeniable for jockeys and trainers: no horse could dominate every track, because the ground itself chose the winner.

Horses for courses.

The horse was not intrinsically “good” or “bad”, it was simply suited to certain terrain. And if you put the wrong horse on the wrong course, it didn’t matter how strong or beautiful or expensive it was. It would lose.

Over time, the horses for courses saying slipped into everyday English, especially in business and politics. It became a memento for something we forget far too easily:

Success is not only a function of capability, but also a function of context.

You have to know the environment you are in, the conditions you are running under, and the way the race is actually being contested.

Because the terrain chooses the winner.

(as an attendee to both the Ascot Race in the UK and Melbourne Cup Day in Australia, I can attest the horse-racing hype is still real to these days!)

The AI confusion

This is where we go wrong in today’s conversation around AI.

Just as trainers and jockeys learned that performance depends on matching the horse to the track, white collar professionals, and especially consultants, must now understand that their value depends on the context in which they apply their skills.

Everywhere I look, the debate is polarized between:

“AI will replace consultants!”

and

“AI makes everyone 10x!”

Both positions are so obviously lazy I cannot even believe those statements are actually being made. Both misunderstand the terrain.

The reality is, I think, simpler, but also more interesting:

• AI is brilliant when the work is structured, documented, repeatable, and language-based;

• AI is terrible when the work is ambiguous, relational, political, or dependent on courage and “common sense”.

What course are you running on? And is that the course you should be on?

If your day is filled with grinding through decks, writing documents, rewriting documents, summarizing documents, making spreadsheets, hunting for reference slides, doing desk research, responding to emails as fast as possible… You are running on the AI-friendly flat track.

On this track, the machine is already faster than you.

If you stay there, you will get commoditized. I cannot tell you exactly when, but I can exactly tell you it is going to happen. It does not matter if you are smart, or hardworking, or capable: you are racing on a ground where speed is the only metric, and (assuming Nvidia will keep delivering its chips) your competitor does not sleep.

The ending is predictable.

There is another track

Now imagine you choose a different terrain, for example a meeting room where people breathe, hesitate, reveal things without meaning to...

You begin spending more time there, as the person who draws the real questions to the surface.

You stop treating work as a sequence of deliverables to be produced and instead treat it as something to be understood.

You resist the reflex to respond immediately, and instead you sit with the discomfort of not knowing.

You ask the person across from you what they are actually worried about. You listen for the thing said indirectly, flinched at, softened, avoided.

Slowly, almost imperceptibly, the terrain changes beneath your feet!

The ground is no longer flat. It tilts and bends. Incentives pull in different directions. Personal histories shape what is possible. A single pause in the room carries more meaning than five pages of notes.

You begin to see how decisions are really made: in the space between people.

On this terrain, you rapidly realize that what matters is your ability to sense what is actually happening: WHO is protecting WHAT, where the fear sits, which outcome feels dangerous, and which one feels like relief.

This is not intuition in the mystical sense, nor is it calculation. This is not some fake guru stuff...

I am describing the practiced ability to read a situation in motion, to understand what cannot be openly stated, and to act in a way that changes the outcomes rather than just describing it.

A machine cannot do that!

We may even say that machines are intelligent (intelligence is cheap now), but machines have never been in meetings where the stakes were personal, where silence spoke louder than dialogue, where the decision could lead to some shift between people.

(PS: these are the types of skills I discuss in Beyond Slides, my #1 Amazon Best Seller book that includes 39 exercises you can train on — end of the ad 🤣)

What to do to become the right horse

This is where this reflection becomes practical, and please allow me to give you a few ideas you can start using straight away.

When you are handed a piece of work, don’t stop at delivering it.

Ask: “Why does this matter? Who actually cares about this? What would break if we got it wrong?”

You’d be surprised how often the sponsor doesn’t even know!

When you are in a meeting, stop trying to sound impressive. Instead, try naming the thing nobody is saying.

“The hesitation here is not about the cost. It’s about who ends up owning the outcome if this fails. That’s the real tension, isn’t it?”

That one sentence can be worth more than 200 slides.

And when you work with clients, do not jump into frameworks but rather begin with curiosity.

“What is the emotional cost of this decision for the people who will have to live with it?”

Now you turn into something more than a dealer of methodologies.

You become a trusted interpreter of reality, and AI cannot compete with that.

With this, I don’t mean to say AI is “dumb.” It is not. But AI has never sat in a room where the CFO’s face tightens when the CEO says ‘cost reduction,’ and you suddenly understand the stakes are not financial but personal.

The machine lacks exposure.

It lacks scar tissue.

It lacks context.

My recommendation is to stop asking how to outrun the machine, but instead start choosing terrain where being human is the advantage.

That means 4 things:

1) Spend more time in conversations than in documents;

2) Spend more time framing the work than producing it;

3) Spend more energy understanding incentives than analyzing data;

4) Spend more courage saying the uncomfortable truth early, rather than perfecting it on your own.

This is how you become the right horse, by placing yourself where your way of seeing the world is actually valuable.

Your strengths start to compound when you work in environments where your presence influences the conversation, where people speak differently because you are there, where decisions that were murky become clearer.

Where presence matters. Where the real work happens in the glance and the hesitation before someone speaks.

Where the ability to recognize what is shifting beneath the surface is worth more than any metric of efficiency.

As usual, if you enjoy reading Consulting Intel, please do me a favor: spread the word and share this post.

👋

👀 Links of interest

A few corners of the internet you may find interesting:

• I recently spoke with Kenny Alami on a broad range of topics: from what I think AI will do to consulting, to how I use AI tools every day to increase productivity. This was a good conversation, so have a look if you are keen!

  

• Also, I am meeting and Deri Hughes on the 20th November for a LinkedIn Live session! Broad topics below:

  

• Have you looked into the Leaders Toolkit? It is a deck of 52 tools, frameworks and mental models to make you a better leader (use code CONSULTANT10 for 10% off);

• The Consulting Intel private Discord group with 250+ global members is where consultants meet to discuss and support each other (it’s free).

The dot-com mania was in full swing, with consultants and entrepreneurs swearing the old world was about to vanish. Everyone believed the future was being rewritten in code: faster analysis, cheaper slides, smarter models. We spoke in buzzwords, convinced we were surfing history.

Then, as always, the tide receded, and the future arrived a bit slower than we expected.

That memory haunts me now every time I hear the same breathless tone around AI, the same conviction that “this time it’s different.”

It never is.

Jeff Bezos said something in an interview at a business forum reflecting on Amazon’s early strategy, that has stayed with me ever since.

He explained that people always asked him what would change in the next decade, but rarely what would not change.

His answer revealed a deep truth about time and focus:

“You can build a business strategy around the things that are stable in time.”

For Amazon, that meant anchoring around the simple, eternal truths of customer behavior: people would never want slower delivery, higher prices, or a smaller selection.

It was a meditation on permanence disguised as business advice.

And that’s why it resonates with me now: because in every period of technological upheaval, future success comes sometimes from predicting what will shift, but always from understanding what will stay still.

I have been thinking about that line a lot lately.

AI has turned consulting into another hype cycle… a familiar one. ERP, outsourcing, digital, agile, blockchain, now AI. The names change, the pitch decks update, the fundamentals remain rooted.

What matters is not predicting every disruption but seeing what endures beneath them.

The constants I see

I still remember my European years commuting between London and Milan every single week.

I would wake up on Monday morning at 4am for my 6am flight out, and take the Friday 8pm flight back. Same suitcase, same coffee at the British Airways lounge at Heathrow, same rush to Piazza del Calendario in the heart of Milan.

It was exhausting but also satisfying.

I learned that clients never really cared how advanced my frameworks were. They cared if they could trust me in meetings with their bosses. They cared if I could help them see the problem clearly, define a credible path to a solution, and then follow through.

That has never changed. And I doubt it will going forward.

Clients will never ask for advice they can’t trust. They will never say, “Please, confuse me with more options.” They will never prefer a consultant who can crunch the data but can’t read the room.

Charlie Munger had a mental trick for this: invert, always invert.

Instead of asking how AI will change consulting, ask:

If AI rewired everything, what would still survive?

AI won’t replace the credibility that gets you invited into the meeting in the first place.
It won’t walk into a hostile steering committee and de-escalate politics.
It won’t sense that the same framing lands one way in London and another in Hong Kong.

It may get faster, more articulate, and more context-aware, but it will never carry moral authority, political intuition, or lived experience.

What is the human moat, then?

Consulting is not just an information business: it is the governance of decisions.

Decision calculus is therefore not taste or style, but the hard work of specifying the objective function, choosing the loss you are willing to tolerate, and sequencing interventions that can survive an organization’s immune system.

Models compute. Humans decide what “good” means.

If there is a human moat, let’s name it precisely.

Is it “interpretation”? Maybe, but I think it’s more arbitration among conflicting incentives and constraints.

In a bank, for example, the “right” answer must thread capital requirements, union agreements, brand risk, regulator mood, and the unwritten rules of status. None of that lives cleanly in your dataset.

AI doesn’t replace consultants, but it certainly removes alibis. It collapses the cost of manufacturing plausible plans, so scarcity shifts from answers to alignment. The edge lies in killing 90% of the options for reasons no model can see, and then standing behind the remaining 10% with your name on the line.

Here’s an uncomfortable truth: when you “explain the model,” you are manufacturing shared acceptability so that accountable humans can sign their names to a decision.

That’s the layer AI cannot touch: setting decision rights, shaping incentives, designing irreversibility carefully, and distributing blame and credit in ways that keep the system stable while it changes.

So, the trillion-dollar question: what remains scarce when compute is cheap?

At least 4 things, and I am going to name them.

1. Trust. Trust as a track record of exposure means you made calls under uncertainty, were transparent about risks, and owned the consequences. Trust is a lagging indicator. AI can draft arguments, but it can’t take risk; therefore, it can’t accumulate trust.

2. Problem framing. As the marginal cost of generating options approaches zero, the marginal value of pruning them rises sharply. Framing is the discipline of naming the objective, constraints, and acceptable loss so that the vast majority of the solution space is eliminated before anyone opens a slide. Models enumerate; framing economizes attention.

3. Stakeholder alignment. Implementation is distributional: every decision allocates pain, status, and budget. That’s why most “right” answers fail in the wild. Alignment is a credible deal among actors with conflicting interests, and no model optimizes for that equilibrium by itself.

4. Accountability and ownership. Advice without ownership is performative. Someone must specify decision rights, design irreversibility carefully, and set escape hatches when reality pushes back (and reality is right, but only 100% of the times…).

AI can accelerate thinking, but it can’t accept liability, navigate status games, or translate local constraints into credible commitments. It can propose, but not persuade. It can simulate empathy, but not earn it.

The job, then, is to use AI as a lever to reclaim time and reinvest it in the only scarce assets that make us go exponential: trust, framing, alignment, and ownership.

The tools will evolve. The buzzwords will change. But the essence of consulting (ie, the craft of helping humans make consequential choices under uncertainty) will not.

And that is why I believe this profession will still matter.

As usual, if you enjoy reading Consulting Intel, please do me a favor: spread the word and share this post.

👋

👀 Links of interest

A few corners of the internet you may find interesting:

• As the inspiration for this post today was a quote from Jeff Bezos, I thought it’d be good for you to have a look at this post by from :

  Sketchy Ideas

  7 mental models Jeff Bezos uses to run Amazon

  As I write, Amazon is the 5th most valuable company in the world with a market cap of 2.3 trillion dollars…

  Read more

  8 months ago · 137 likes · 22 comments · Chris J Wilson

• Have you looked into the Leaders Toolkit? It is a deck of 52 tools, frameworks and mental models to make you a better leader (use code CONSULTANT10 for 10% off);

• The Consulting Intel private Discord group with 250+ global members is where consultants meet to discuss and support each other (it’s free).

If there is one universal truth in those environments, it is this: credibility is binary. A single wrong number can undo months of effort, derail billion-dollar programs, and permanently stain reputations.

This is why I am baffled when I see so many GenAI products trying to prove themselves in areas where precision is non-negotiable.

Drafting legal clauses.

Building financial models.

Producing compliance artefacts.

They pitch the promise of speed, but the hidden cost is trust.

70% accuracy is not “better than nothing” in domains that demand perfection. It is useless. In fact, it is worse than useless because it lulls you into a false sense of security.

A financial model that is 70% correct is like a bridge where 30% of the beams are missing: it might look impressive from a distance, but you would never dare walk across it. And yet, I see executives trying to walk across those bridges every day, convinced that GenAI has given them an edge.

The reality is that if I cannot predict where the errors are, I am forced to check everything.

Fix one formula, and another hallucination (a more-or-less fancy word for “invented number”) pops up. I end up shifting my human effort from construction to auditing, while the actual modelling muscles of the team slowly atrophy.

To anchor this scientifically: large language models are statistical sequence predictors. They optimize for plausibility, not verifiability. Their accuracy distribution follows a long‑tail error curve: most outputs are “good enough,” but the unpredictable outliers are catastrophic. In probabilistic terms, variance is high even when mean performance looks acceptable.

In deterministic domains like finance or law, these rare but severe errors dominate the risk profile. This is akin to Nassim Taleb’s concept of “ruin risk”: one failure, no matter how infrequent, can erase the entire upside.

In this LinkedIn post I discussed the case of a Big4 consultancy that delivered a LLM-generated $439K artefact to a government agency in Australia, with significant reputational repercussions.

Where AI should play

We said that GenAI is a probabilistic machine. It thrives in the fog. Its native domain is ambiguity, not arithmetic.

When I sit with a client and face a blank slide, the hardest part is not perfecting the numbers, but framing the problem, surfacing the unspoken assumptions, testing hypotheses, exploring scenarios.

This is where “70% right” is gold. Because 70% is enough to expand thinking, provoke discussion, and unlock new angles.

The smart play is to redeploy GenAI into ambiguity, creativity and iteration speed. Let me explain:

• Ambiguity: In practical terms, this means helping consultants detect the subtle coalitions, unspoken fears, and implicit trade‑offs that often derail programs more than any technical issue. GenAI can process thousands of emails, meeting transcripts, or feedback threads and cluster themes we would never spot manually. The output is not deterministic, I get it, but it acts like a cognitive radar, showing where the fog is thickest and where attention should go.

• Creativity: Human teams often converge too quickly on the first idea that sounds credible. A probabilistic engine resists that premature closure: it generates divergent options, metaphors, and framings that stretch the conversation. Neuroscience shows that creativity emerges from recombination more than invention; LLMs are powerful at recombining, surfacing analogies across domains in seconds. This accelerates the “adjacent possible”, solutions just one step beyond what we already know.

• Iteration speed: Strategy lives in iterations, not in single shots. With GenAI, we can explore multiple narrative arcs (eg, a cost story, a risk story, a growth story) and stress‑test them with stakeholders before committing. This is some sort of rapid prototyping of mental models. By burning through cycles faster, we compress the learning loop, which is the essence of competitive advantage in fast‑moving environments.

In these domains, being “almost there” is a catalyst.

About 15 years ago, I remember working on an investment accounting transformation in Asia, surrounded by twenty consultants who were burning 80 hours a week for almost two months straight.

The modelling had to be flawless. Every journal entry had to reconcile, every test had to tie out, every decimal point mattered. In that crucible, a 70% solution would have been laughed out of the building.

But later, when we needed to present options to the executive board (should we replatform?, should we buy a vendor?, should we build in-house?) that was where ambiguity reigned. That was where we needed to explore confusing “what ifs.”

An AI tool that could spin scenarios and reframe arguments quickly would have been worth its weight in gold. It would not have replaced the accountants and the finance experts, but it could have accelerated the consultants.

My takeaway

Executives who jam GenAI into deterministic work are committing a category error: they are treating a probability machine as if it were a calculator.

But a calculator is deterministic (2+2 is always 4) whereas an LLM generates outputs by sampling from probability distributions. This fundamental mismatch means leaders are betting deterministic credibility on stochastic processes. And in doing so, they risk both productivity and trust, because every unnoticed error compounds into reputational fragility.

The smarter use of GenAI is not to force it into the world of zero tolerance but to unleash it in the world of multiple possibilities.

What differentiates a consultant is, after all, not how quickly they can crunch numbers: machines will always outpace us there! Our edge is turning political minefields into solvable equations, or crafting a story so crispy it forces a decision.

Numbers only carry weight when someone has the guts to interpret them, defend them, and weaponize them into a tangible Outcome. That is the work that bends billion‑dollar outcomes.

And that, I believe, is where GenAI can finally shine… not a modern shortcut to a broken spreadsheet.

As usual, if you enjoy reading Consulting Intel, please do me a favor: spread the word and share this post.

👋

👀 Links of interest

A few corners of the internet you may find interesting:

• I have started to be more active on LinkedIn in the last month. Would be awesome to connect with you over there as well. Feel free to follow or connect with me!

  

• The Leaders Toolkit is a deck of 52 tools, frameworks and mental models to make you a better leader (use code CONSULTANT10 for 10% off);

• The Consulting Intel private Discord group with 250+ global members is where consultants meet to discuss and support each other (it’s free).

For days, I kept thinking of the post. More came to mind, and so I decided to write a long-form piece.

I linked the original post above, but I will also leave a screenshot here:

Look at those ship-log maps again.

Thousands of tiny coordinates, each meaningless on its own, become a sketch of the world when placed together.

The Atlantic emerges. Trade winds appear as if drawn with charcoal. Even small islands show up as bright knots of traffic.

It proves two things at once:

1. Data can reveal structure that nobody explicitly encoded.

2. The picture remains partial because the data was collected for shipping, not for cartography.

As Alfred Korzybski warned first in 1931, “the map is not the territory.” And as George Box added some 45 years later, “All models are wrong, but some are useful.”

Both quotes fit perfectly here!

Having worked as a management consultant for the past couple of decades with large enterprises in 10 countries, I realized that big organizations have oceans of data… and a surprisingly small shoreline of use.

It is almost a tragedy.

Petabytes flow through warehouses and lakes, dashboards multiply, a new platform arrives every budgeting cycle, yet the insight that actually changes decisions is thin.

The reason is rarely a shortage of effort or talent. Often, it is a shortage of context.

Data is collected to run operations, settle invoices, comply with regulation, and click-stream a website. Later, executives ask this operational exhaust to answer strategic questions it was never designed to answer, which is why the insights often fall short.

The result looks like that ship map: suggestive, sometimes beautiful, but missing whole continents of meaning.

There is another pattern.

The conversation starts with the data that exists: “What model can we train with what we have?”

That framing feels pragmatic but can quickly become expensive. You end up bending the question to the data rather than shaping the data to the question.

The information paradigm flips this: “What decision do we need to make? What information would de-risk it? What data, with what traceability and structure, would produce that information reliably?”

The difference sounds semantic only, but it is instead HUGE!

Internal teams live inside the firm’s gravity: processes, incentives, and history pull every initiative into familiar orbits.

Backlogs are very full. Compliance is very real. Politics are the very operating system.

So, people optimize for what they can control: building pipelines, cleaning tables, hardening dashboards. All important work, for sure, but without an external forcing function, the hard questions often go unasked:

• Are we answering the right problem?

• Is the cost of precision greater than the value of the decision?

• Which data is missing because nobody owns it?

High-quality data is not yet information!

Information is data given context relative to a decision. You can have exquisite accuracy and still be wrong for the task, like using ship logs to draw mountain ranges.

We may need consultants after all

This is where experienced external advisors earn their keep. They are probably not smarter than your people, but they do come unburdened by your history and armed with patterns from other places.

Breadth matters.

Someone who has seen insurer claims, retail replenishment, credit risk, mining maintenance, and airline scheduling notices recurring structures: queues, thresholds, matching problems, leakage loops, signal-to-noise constraints.

They carry “priors” about where value typically hides and where data usually lies to you. They know which questions are worth paying for, and which are false precision. They recognize when your map is drawn from one kind of ship.

Advisors also recalibrate scope.

They start with the decision and design the smallest trustworthy data product that moves it: the Minimum Viable Dataset. Then they layer context (eg, definitions and lineage) so the output survives contact with reality.

They help you separate governance that safeguards value from bureaucracy that suffocates it.

Most of all, they shorten the distance between discovery and action.

In my experience, this is the sequence that works inside complex enterprises. I will give it to you in 4 nice and simple steps.

1. First, enumerate decisions. “Approve this loan at this price.” “Reposition these store inventories.” “Escalate this claim.”

   Tie each decision to a measurable consequence.

2. Second, ask what information makes that decision better by a specific margin. Not perfect. Better.

   The pursuit of perfect information in corporate life is the most expensive hobby (almost like marriage, as a former boss of mine once put it to me 😁).

3. Third, engineer the minimum data with the right context to produce that information repeatedly. You discover quickly that some of your most valuable inputs do not exist yet: labels for edge cases, human feedback loops, ground-truth audits, or even third-party datasets you never considered procuring.

4. Finally, close the loop! Measure whether the decision actually improved outcomes in the wild and feed that learning back.

   Without the loop you have analytics, but you don’t have intelligence.

Every wave of technology kills a layer of consulting and creates a new one.

Spreadsheets removed armies of number-crunchers and birthed model builders.

ERPs killed manual reconciliations and created process designers.

Cloud ate server rooms and created migration factories.

AI will automate report writing and slide drafting (maybe… one day… or maybe not!), and in doing so it will push consultants toward the work that only humans can do, like, for example, framing ambiguous problems, stitching together context across silos, negotiating trade-offs, designing governance that balances speed with risk, and building information supply chains that are resilient to noise and drift.

New tech also introduces new failure modes.

Model collapse from contaminated feedback, provenance disputes, privacy thresholds, subtle forms of bias, cost-to-serve surprises, hallucinations that look persuasive, regulatory regimes that evolve mid-project: these are only some of them, and someone has to design around these.

Someone has to hold the client’s constraints in one hand and the state of the art in the other, then craft the path through.

Consulting renews itself by moving up that curve, from deliverable factories to decision-architecture partners.

Where am I going with this?

None of this is an indictment of your teams. This is an invitation to treat your data with more dignity (is this the right word?).

Data becomes an asset only when it is coupled to questions that matter. That care produces information. Information, when wired into decisions and incentives, produces outcomes. Outcomes are a flywheel.

Bring in breadth when you lack it, but at the same time let outsiders hold the mirror, name the missing context, and help you choose what not to compute. After that, make the capability your own. A good advisor should design themselves out by leaving behind architectures, skill paths, and operating cadences that continue to pay dividends after they leave.

My summary is that enterprises often fail because they lack the right information at the moment of choice, despite having a lot of data. The shortest route from data to information is context, and context is hard to see from inside the jar.

That is why experienced, cross-industry advisors remain valuable. And that is why consulting will not die in the age of AI; it will simply change clothes and move closer to the frontier where new problems appear.

The ship-log maps are a gift.

They show that models can be useful long before they are perfect, and that purpose matters. Ask your data to draw the map you actually need, not the one that happens to emerge.

Build for information, not accumulation. When the picture remains foggy, invite a navigator who has sailed other seas to help you find the signal, and then to help your organization learn how to pull the signal out for itself, again and again.

Keen to hear what you think in the comments…

And, as usual, if you enjoy reading Consulting Intel, please do me a favor: spread the word and share this post.

👋

👀 Links of interest

A few corners of the internet you may find interesting:

• My favorite author and thinker Nassim Taleb just released a new article on Medium (a lecture at the Annual Meeting of the Ron Paul Institute), and I think you should read it. A great quote from the article:

  “The final point is that scale matters when it comes to governance. I have an aphorism phrased by friends as follows: I’m a libertarian at the national level, a Republican at the state level, a Democrat at the municipal level, and a communist at the family level.”

• The Leaders Toolkit is a deck of 52 tools, frameworks and mental models to make you a better leader (use code CONSULTANT10 for 10% off);

• The Consulting Intel private Discord group with 250+ global members is where consultants meet to discuss and support each other (it’s free).