Le Veneur

20/05/2026

"What kind of company do you want to be?"

This is one of the strategic questions that precedes the deployment of AI.

Why:

AI can help you on your journey. But it needs to know the direction. There’s a difference between wanting to be Harrods or Lidl. For example, how do you expect AI to handle pricing, margins, hiring, or even visuals if you don’t know who you want to be?

Imagine if Lidl or Harrods asked AI the question: "How can we attract better employees?" Just like that, without proper instructions, without a lot of data, without in-depth prompting.

They’d end up with some generic AI nonsense that they likely wouldn’t be able to apply for the most part.

Only when you give the AI enough data and clearly describe who you are and who you want to be will you receive answers of vastly higher quality.

That’s why clarifying your strategy is so important.

14/05/2026

Yesterday, we recommended that a client implement a CRM system that is estimated to be the 15th largest in the rankings. Why did we rule out the 14 larger ones and the 5 smaller ones?

When choosing an IT system, CRM, ERP, sales framework, management framework (e.g., OKR, BSC, Scaling Up), etc., it’s important that the system feels right to you.

Tension arises during the selection and implementation process—and that’s completely natural. On the one hand, the system imposes constraints—which is good, because it means order. But it mustn’t be an order that constrains you to the point of destroying you.

Selecting a quality system, therefore, means first and foremost understanding how you work and think. Because it makes absolutely no sense to implement a framework or IT system that your work style or mindset won’t accept.

On the other hand, it is essential to have a very deep understanding in advance of the limitations of each system. Limitations can be both an advantage and a trap. This is a common mistake made by companies that do not know the systems thoroughly—and allow a vendor to impose something on them. After a year of work and numerous paid invoices, they discover that the system does not suit them—and cannot be changed.

We, for example, address this by offering the client three to five options out of perhaps 20 possible CRMs, ERPs, or strategic frameworks. And we re-examine and discuss which one will be most beneficial for the client.

"On the other hand again," as I like to say, it is very often necessary to customize the system a bit. But it mustn’t be too much. The logic of a given system—in the case of good systems—is usually very well thought out. And very often, requests for excessive customization reveal long-standing unresolved issues within the company rather than the company’s specific needs.

The em dashes (—) are a stylistic choice, not—in my case—the result of AI.

13/05/2026

Many corporate initiatives, whether market expansions, IT overhauls, or new Go-to-Market strategies, do not fail because of poor ex*****on.

They fail because the foundational thesis was flawed from day one.

Your teams will burn the midnight oil optimizing the mandate. They will deliver exceptional work. But often, no one in the room has the authority, or the courage, to stand up and say:

"This entire premise is capital destruction."

Imagine a board approving a budget to sell footwear to penguins in Antarctica. The corporate machinery immediately grinds into gear:

Supply chain establishes a logistics hub on the ice.

Marketing deploys an aggressive awareness campaign.

R&D meticulously measures webbed feet to optimize product-market fit.

Twelve months later, the initiative is bleeding cash.

The C-suite demands answers: "Was the ad spend inefficient? Is our sales team underperforming? Is the pricing architecture wrong?"

The problem was not the marketing. The problem was not the sales team.

The problem was in the boardroom. The initial brief was a hallucination.

It's boring, unpleasant, and obvious, but before you approve any major investment, whether it’s CapEx or even OpEx, rigorously stress-test the core thesis.

And don't trust Excel. If you try hard enough, Excel can calculate the Free Cash Flow even for selling shoes to penguins in Antarctica.

04/05/2026

One of the most common mistakes in business is generalizing experiences, whether positive or negative.

Imagine that you succeeded at something in the past. Now you tell yourself: “We succeeded at X in the past. So let’s try it again now, and it’s sure to be a success.”

Typical examples might include:

“At Company X, we tried A and it worked. Let’s try it here.”

“In the past, we did B and it worked. Let’s try it again.”

The problem is that business isn’t a single-player game. Market conditions are constantly changing, and more importantly, your opponents are changing too.

From a game theory perspective, your past success worked because it was the best possible response to the market and competition at the time.

But the competition learns. If you won last time with tactic A, other players have adapted. Or perhaps entirely new players have entered the game. The market equilibrium has shifted, and you’re now playing a completely new game.

Why is this “copy-paste” approach harmful?

1.) You’ll spend a lot of money on a solution that no longer works in the new payoff matrix.
2.) It will take you a lot of time.
3.) You’ll lose out to the competition.

Your opponents likely already know your old strategy and have a counterstrategy ready for it. You’ll end up investing resources and energy into a predictable and ineffective solution.

What’s a better approach? Don’t blindly copy the action; instead, examine WHY it worked in the past and map out the current game plan. Ask yourself:

* Are we playing with different players now? (New competition, different customer expectations)

* Have the rules of the game changed? (New technologies, different legislation)

* Have the payouts changed? (Is this solution still as profitable?)

And most importantly: How will the other players react if we make this move today?

From a certain perspective, the ability to seek solutions may become more important than experience.

Don’t play yesterday’s game with today’s opponents.

— Robert A. Le Veneur

08/04/2026

Germany is reeling from UniCredit’s bid to take over Commerzbank. How did it come to be that Italian banks are buying up German ones?

The German banking sector is fragmented among 1,254 banking institutions, the vast majority of which are prohibited from growing.

Robert A. Le Veneur presented an analysis and solution in Le Temps
Les banques allemandes doivent fusionner, sous peine d’être évincées par la concurrence étrangère - Le Temps

OPINION. L’OPA sur Commerzbank le montre en creux: même si maintenir des centaines de banques flatte l’ego local, l’Allemagne doit d’urgence se mettre aux économies d’échelle dans son secteur bancaire, obsolète et dispersé, écrit le conseiller en stratégie Robert A. Le Veneur

24/02/2026

The more I use AI, the less I trust it with complex things

By Robert A. Le Veneur

AI is certainly great for simple things and can save a lot of time. But with complex things, even if I enter a prompt the length of a short article, it still can't grasp the complexity of the world. It simplifies it terribly.

For example, I'm currently looking for a new supplier. I know about 30 possible suppliers in this area, I have written to at least 20 of them, and I have personally negotiated with about five. I wondered if Gemini 3.1 Pro Deep Research would surprise me.

The results were appalling. If I didn't have in-depth knowledge of the field, the result would have looked "impressive." But because I do have that knowledge, I often see "fluff" in the AI output.

Despite a very detailed prompt, the AI was unable to perceive the complexity of the situation and subtle nuances. When I told it that it was wrong and entered Deep Research a second time, it adjusted the result a little, but it was still at a level of, say, 5 out of 10.

The reason I'm lowering the score so much is that it didn't "think" about the results, even though I told it how to think. It's like asking a junior secretary to make you a list of suppliers.

She will make it for you. But only a senior person will be able to cross it off immediately. For example, the AI described that one supplier has a certain advantage - which in reality is an immediate elimination rule.

Only when I divided the big task into small subtasks did it start to become really useful. But it was very one-sided.

Don't be fooled by various official tests of different AI models. Their weakness is that they have a clear-cut solution to evaluate. But reality sometimes has ambiguous solutions. Or hidden solutions. Or no solution at all. Or it requires solutions for which we have no data. And as soon as AI has no data, it fails.

We all know from high school that parallel lines will intersect at some point. But we can't point to where. AI tends to show you that point.

AI developers are, of course, well aware of this problem. That's why they don't give you the ideal or optimal result, but the closest possible approximation, which is also limited by computing power.

I have also noticed that it very often plays it safe. Instead of recommending a risky maneuver, it discourages you from certain moves. But you can't do business without taking risks.

AI is also unreliable because it often uses Google searches in its work and only looks at the main results. But you have to look for the best suppliers on, say, the fourth page of Google, where the robot will not go in the vast majority of cases.

At our strategic consulting firm, Le Veneur Sàrl, we repeatedly test whether AI is suitable for drafting contracts. It saves time, but it cannot replace a senior or even a mid-level lawyer.

In one of our tests, we asked it to create general terms and conditions using a long prompt. The first result was quite general, despite the amount of data available to it. The problem is that by default, it generates a contract that is perhaps two pages long. But what if you need something more detailed?

Only after many iterations and several hours of telling it, "You forgot this and you forgot that," was the result excellent.

So yes, in the end, it was able to create excellent general terms and conditions and save 60 to 70% of the time. But only because it was managed by a senior person who still had to slightly adjust the result.

That's why I'm not at all concerned that it could replace people who work with high complexity.

Is it suitable for obtaining certain information? Absolutely yes. Is it worth listening to? Absolutely yes. Should you trust it and blindly follow it? Absolutely not.

I recently tried to vibe code a solution for emails. Programming advanced solutions for emails is very demanding.

After many hours of futile attempts to debug the code with ChatGPT, Gemini, and Claude, I finally bought a ready-made solution for $15.

And one last example to finish. Gemini Pro 3.1 recommended that we drive to Castillo de Almodóvar del Río with our young children rather than walking, as the climb would be too difficult for them.

The AI had information about the children's ages, their physical abilities, and what they enjoy and don't enjoy.

The children decided to ignore the AI's recommendation and raced up the steep paths, pretending to conquer the castle.

04/02/2026

Immunize your intellectual propery (IP) against the CLOUD Act.

Is your proprietary data exposed to US jurisdiction?

If your vendors are US-based, the answer is "Yes"—regardless of where the servers physically sit. To help you mitigate this risk, we have updated the Le Veneur Sovereignty Stack. This is our independent index of digital infrastructure providers vetted for two non-negotiable criteria:

1.) Zero US Nexus: Headquarters and data residency strictly outside the reach of the CLOUD Act.

2.) Operational Excellence: We do not recommend "alternatives." We recommend upgrades. Every tool listed has survived our internal stress testing.

The February Update includes: Proton Docs and Sheets: A sovereign alternative to the Google Workspace ecosystem. Domain Governance: New registrars that decouple your web identity from US oversight.

Stop building your company on rented land. Build on sovereign territory. Achieve European digital sovereignty:

https://cdn.leveneur.ch/insights/le-veneur-digital-sovereignty-eu-companies-february-2026.pdf

03/02/2026

🌊 The Mirage of the "Blue Ocean": 🌊

A client recently approached us with a bold thesis. They identified a market sector dominated by a single player and saw it as a classic Blue Ocean opportunity.

Their logic was seductive: "With only one competitor, we have unlimited room for exponential growth."

We immediately initiated a market due diligence process. The Findings: The sector was not empty. It was crowded. While there was indeed one giant, the "empty space" was actually filled with thousands of micro-players who had been stagnating for a decade.

The market wasn't a Blue Ocean; it was a Winner-Takes-All ecosystem. 🦈

Before allocating 💰 CAPEX, you must answer the uncomfortable question: "Why have 1,000 others failed to scale against the incumbent? What specific structural advantage do we possess that they lacked?"

This is the difference between optimism and strategy. Sometimes, the highest ROI we deliver is stopping you from entering a 🦈 "Red Ocean" 🦈blind.

We don't audit your ideas to kill them. We audit them to ensure that when you do pull the trigger, the math works in your favor.

Don't guess. Stress-test your thesis. 🔦

26/01/2026

The US Government (and your IT Admin) can access your Gemini chats.

If you are deploying Gemini within your corporate Google Workspace, you need to understand the governance risks immediately.

The "Delete" button is an illusion

In a corporate environment, you cannot simply micromanage data deletion within Gemini. You are bound by rigid Retention Policies.

Typically, an Admin possesses only blunt tools: they can set a global expiration date for everyone, or they can wipe company-wide datasets (i. e. for all at the same time). They cannot easily perform surgical deletion of a single sensitive conversation.

The Risk: Jurisdiction & Privacy

1. The US Reach: Google is a US entity. Under the CLOUD Act, data stored by US providers can be subpoenaed by US authorities, regardless of where the server physically sits.

Even if you pay for "Business Plus" and set your Data Region to Europe (which I highly recommend you verify immediately), do not be naive. For the AI to function (inference), data packets often must travel to where the compute power is located. Frequently, that means crossing the Atlantic.

2. The Internal Liability: While retention is active, your administrators technically hold access to individual employee chats. So, anything you write in the Gemini chat on your company account can be seen by someone else in the company.

The Le Veneur Recommendation:

1. Automate the Purge: Stop using the default setting of "Never." Enforce a strict retention window (e.g., 3 months). Limiting the timeline reduces your surface area of risk. Do not hoard data you do not need.

2. Segregate Sensitive Data: Do not feed strict intellectual property (IP) or client secrets into a public cloud LLM. Use a private, ring-fenced instance (like Vertex AI) with explicit legal guarantees, not the standard Gemini chat interface.

3. Think: Think about what you write in Gemini.

Convenience is not an excuse for compromising compliance.

09/01/2026

Are your Standard Operating Procedures (SOPs, the "company rules") killing your agility?

Thick rulebooks give employees and companies a false sense of security. We see this constantly: Companies creating thousands of internal policies to "prevent errors."

The result is not perfection. The result is paralysis.

You end up with staff who function like robots: optimizing for compliance rather than profitability.

When an employee’s primary goal is to "follow the manual" to avoid being fired, they stop looking at the market. They stop seeing risks. They stop seizing opportunities. They are not managing assets; they are managing their own liability.

This is a hidden tax on your EBITDA. Every minute spent documenting compliance with a nonsense rule is a minute stolen from value creation.

I do not advocate for anarchy. Even our strategy consulting firm Le Veneur utilizes frameworks and corporate wikis.

However, there is a critical distinction between a Process and a Crutch. If you try to govern dynamic situations with static rules, you lose speed. In the current market, speed is the primary driver of ROIC.

Consider the alternative mechanism: Replace rigid controls with direct exposure to outcomes. When an employee faces both significant upside potential for success and real downside risk for failure, their awareness shifts immediately.

They stop auditing their own compliance and start auditing the REALITY around them. They recover the necessary bandwidth to generate genuine customer value, which is the only sustainable driver of long-term margin.

The Challenge: Shift from a culture of "Permission" to a culture of "Accountability." The former protects the status quo. The latter drives the P&L.