I recently had the opportunity to read a draft paper by Matt Grawitch , Steven L. Winton, and Srikanth P. Mudigonda titled “AI-Assisted Decision Making as a Sequential Judgment Process”.
One distinction in the paper stayed with me. The authors separate perceived expertise from confidence in a current judgment. Perceived expertise concerns whether people believe they possess the knowledge and capability required to make an effective decision in a particular context. Confidence in a judgment concerns whether they believe that the particular conclusion they have reached is correct [1].
The two are related, but they are not the same. I can believe that I am generally capable of navigating a difficult situation while remaining uncertain about the answer in front of me. I can also possess limited relevant expertise while feeling extremely confident that my current answer is right.
The draft examines this distinction in the context of AI-assisted decision-making. People do not receive an AI recommendation with an empty mind. They have already formed an initial judgment, assessed their own capabilities, and developed some degree of confidence in their answer. These self-assessments influence whether they reconsider their position, engage critically with the recommendation, or dismiss it before examining what it might contribute [1].
Research supporting this wider argument shows why calibration matters. People who overestimate their own performance can under-rely on correct AI advice, while people who underestimate themselves may place too much weight on external recommendations. The objective is therefore not maximum trust in AI or maximum human independence, but appropriate reliance: knowing when one’s own judgment deserves to prevail and when it should be reconsidered [2].
While reading the draft, however, I was not thinking only about AI.
I was thinking about founders and corporate innovation leaders. I was thinking about the venture teams I have worked with, the projects I have analyzed, and the many arguments I have had after returning from the market with information that did not support what the founder or the team wanted to believe.
Ventures operate in a forest that rewards bold trees
A founder or corporate innovation leader needs confidence long before the evidence is complete.
Founders must persuade investors to provide capital for a business that does not yet exist in a reliable form. They must convince talented people to leave secure positions, persuade potential customers to spend time on an unfinished proposition, and repeatedly explain why an uncertain future deserves attention now. Corporate innovation leaders face a different version of the same challenge. They must compete for executive sponsorship, defend budgets, create internal legitimacy, and communicate enough direction that a steering committee will continue protecting the initiative.
There is not much room in these environments for leaders who appear “weak”.
A founder who repeatedly emphasizes everything that remains unknown may struggle to raise capital. An innovation leader who openly presents every uncertainty may be judged as someone who lacks a strategy. Investors expect conviction, employees want direction, sponsors need a story they can repeat, and the wider entrepreneurial culture tends to celebrate people who appear to have recognized the future before everyone else.
I understand why bold egos emerge in this environment. Confidence is not merely a personality characteristic. It can become an occupational requirement.
I am a long term Capoeirista and remembered a capoeira master participating in an event with many other bold masters once said something to me that I have never forgotten. Translated loosely, it was:
It is difficult to remain a humble, learning tree in a forest of bold trees competing to appear the strongest, especially when everyone expects a forest to look that way.
That metaphor captures the pressure well. When every tree is trying to appear certain, strong, and unmovable, humility can be interpreted as weakness. Changing direction can look like failure. Admitting that an assumption was wrong can appear to disqualify someone from leadership.
The answer, however, is not to become the least confident tree in the forest. It is to redefine what strength means.
Confidence becomes dangerous when it changes its object
The problem does not begin when a leader believes in their own capability. That belief may be essential.
It begins when confidence in the ability to navigate uncertainty quietly becomes confidence that the current interpretation of the opportunity must be correct.
The leader starts with:
I believe I am capable of finding a way through this uncertainty.
That is healthy confidence in capability.
Over time, it can become:
I believe the way I have already chosen is the right one.
That is confidence in a particular judgment.
The distinction in Grawitch, Winton, and Mudigonda’s draft becomes important here. A founder may have valid reasons to believe in their resilience, intelligence, experience, network, or capacity to assemble a strong team. None of these qualities proves that the current customer, problem, solution, price, channel, timing, or business model is right [1].
Confidence in the leader is not evidence for the venture hypothesis.
Studies of AI-assisted decisions show a related pattern. In research involving logical reasoning tasks, participants who overestimated their own competence tended to rely less on AI advice, which could prevent them from benefiting when the system was right [2]. Research involving chess players similarly found that greater expertise was associated with stronger self-confidence, lower trust in the AI system, and more self-reliance. That critical stance can protect people from incorrect recommendations, but it can also make them less receptive to correct advice [3].
The same tension can appear in venture leadership without AI being involved. Leaders who perceive themselves as capable may engage critically with new information, which is useful. They may also become so confident in their current interpretation that contradictory evidence no longer receives a fair hearing.
The issue is not confidence alone. It is whether confidence remains calibrated by what the market is teaching the team.
I went looking for resonance and often returned with conflict
I have experienced this more times than I can count.
In several startups and corporate innovation projects, part of my role was to go outside the building and look for resonance with the original belief behind the venture. I spoke with potential users, buyers, partners, industry participants, and other relevant stakeholders. I tried to understand whether the struggle described inside the venture was also visible outside it, whether it mattered enough to influence behavior, and whether the proposed business had commercial ground beyond the enthusiasm of the team.
Sometimes I returned with encouraging evidence. The problem was recognizable, people had already tried to solve it, and the current alternatives created meaningful cost or friction.
At other times, what I heard was less comfortable. The problem was not as important as we had assumed. The urgency was missing. The user experiencing the problem did not control the budget. The switching costs were greater than the value we could offer. The market liked the idea in principle but was unwilling to change behavior, allocate money, or accept implementation risk.
I brought those findings back because I understood that to be the work.
I also brought back questions, because field evidence is rarely a clean verdict. It needs to be interpreted, compared, and challenged. A few customer conversations do not prove a market, but they can reveal that the assumptions carrying a venture are weaker than the team believes.
I cannot remember how many internal arguments followed.
Instead of discussing the quality of the evidence, the participants we had selected, or the implications for the business model, the conversation often shifted toward my commitment to the idea. I was told, directly or indirectly, that I did not believe strongly enough in the venture.
My response was usually that this was not about whether I liked the idea. It was about whether facts outside the room resonated with the assumptions inside it.
Anyone can have ideas. Generative AI has made producing more of them easier than ever. What remains scarce is evidence that one particular idea deserves years of human life, investor capital, organizational credibility, and the opportunity cost of not pursuing something better.
Nevertheless, once an idea has become connected to the identity of the leader and the team, evidence against it can feel like disloyalty. The person returning from the market is no longer treated as someone helping the venture learn. They become the person who does not believe.
That is a critical moment because the social meaning of evidence has changed. A market signal is no longer simply information about an uncertain hypothesis. It has become a test of membership and commitment.
A team can argue constantly and still protect the important assumptions
Venture teams often describe themselves as open, direct, and willing to debate. Many of them are.
They may argue intensely about features, technology choices, brand positioning, campaigns, pricing presentations, sales processes, and delivery priorities. This can create a convincing appearance of intellectual openness.
The more fundamental assumptions may nevertheless remain protected.
Does the customer struggle matter enough to cause action? Are we working with the right segment? Does the person experiencing the problem have access to a budget? Is the current workaround genuinely inadequate, or merely inelegant? Will the customer accept the cost, risk, and politics of switching? Does this venture deserve to continue?
A team can debate everything downstream while treating these upstream assumptions as settled.
Research on psychological safety offers a useful lens. Amy Edmondson defined team psychological safety as a shared belief that a team is safe for interpersonal risk-taking. In her study of 51 work teams, psychological safety was associated with learning behavior such as discussing errors, asking for help, seeking feedback, and experimenting [5].
Psychological safety in a venture should therefore not be assessed only by asking whether colleagues are friendly or whether meetings feel inclusive. The more consequential test is whether someone can introduce evidence that threatens the strategy, the leader’s judgment, or the venture’s shared identity without paying a social price.
Can someone say, “The market is not supporting what we currently believe,” and remain a trusted member of the team?
When the answer is no, the venture may possess a bold culture, but it does not possess a strong learning culture.
The execution-defense loop
One pattern appeared repeatedly in the teams I observed.
When market results failed to support the original expectations, the explanation moved toward execution.
The product was right, but sales could not sell it. The market existed, but marketing had failed to communicate the value clearly. Customers needed the solution, but they were not sufficiently educated. The strategy was sound, but the organization was moving too slowly. The pilot would have succeeded if the business unit had supported it more strongly. Adoption would arrive after another feature, a sharper pitch, a different salesperson, or a more aggressive campaign.
Any of these explanations can be correct.
Innovative products can be sold badly. Marketing can obscure a valuable proposition. Customers may need help understanding a genuinely new category. Internal politics can destroy an otherwise promising corporate venture. Poor execution is real.
The warning sign appears when every contradictory market signal becomes an execution problem.
When positive results demonstrate the brilliance of the idea and negative results always demonstrate the weakness of sales, marketing, product, or operations, the original judgment has become impossible to falsify. Whatever happens, the idea remains right.
This is more than a cognitive bias. It becomes an organizational allocation mechanism.
If the leader’s interpretation is protected, the search for the cause moves downward. Salespeople receive more pressure, marketers are asked to improve the message, and product teams are told to build more. The venture becomes increasingly active while the assumption that most deserves investigation remains untouched.
People inside the organization learn from this. Bringing contradictory evidence creates conflict. Promising better execution attracts support.
The team begins optimizing for internal acceptance instead of external truth.
A learning tree is not a weak tree
The tree metaphor matters because the alternative to performative certainty is often misunderstood.
A learning tree is not passive, hesitant, or without direction. It remains highly sensitive to its environment. It responds to changes in the soil, redirects its growth when conditions change, and adapts before a less attentive tree recognizes what is happening.
Its strength comes from responsiveness rather than rigidity.
A strong venture leader should create the same capability. The leader does not have to appear certain about every answer. The leader must build confidence that the team can identify a better answer, recognize when the current one is failing, and change without treating learning as a collapse of identity.
The shift is not from confidence to doubt. It is from individual certainty to collective learning capability.
The leader moves from:
I believe I am capable of finding a way through this uncertainty.
to:
We are building the fastest-learning team in our ecosystem. We do not need to be right from the beginning. We need to understand what is true faster than anyone else.
Our advantage is not that we claim to be right first. Our advantage is that we discover what is true, what is false, and what remains uncertain before competitors, incumbents, or our own internal politics prevent us from responding.
A venture should be the fastest-learning entity in its ecosystem
An established company is primarily organized to execute what it already knows.
It has existing customers, products, channels, processes, capabilities, and sources of revenue. It still needs to learn and adapt, but much of its operating model is designed to repeat known activities reliably and efficiently.
A venture has a different purpose because the essential answers are not yet known. The customer may be wrong, the struggle may be misunderstood, the solution may not create enough value, the buying process may be inaccessible, and the economics may never support a viable business.
The venture should therefore not be understood primarily as a small company waiting to grow.
It is a temporary learning system created to discover whether a company deserves to exist.
Its job is to convert consequential unknowns into decision-grade knowledge before capital, credibility, and human energy become locked into the wrong direction. This does not mean removing all uncertainty. Some bets cannot be proven before they are made. It means identifying what can be learned, reducing the uncertainties that carry the greatest cost, and making the remaining bet explicit.
This changes the meaning of early productivity.
A prototype is useful when it helps the team examine an important assumption. An interview is useful when the team is willing to hear an answer that contradicts its expectations. A pilot is useful when it creates evidence that can change an investment decision. A roadmap is useful when it organizes learning rather than converting assumptions into promises.
The venture’s early outputs should therefore include more than products, decks, and demonstrations. They should include explicit assumptions, observations from outside the team, evidence that weakened the original view, unresolved unknowns, and thresholds for continuing, revising, deferring, or stopping.
These are not signs that the team lacks belief.
They show that the team has built a functioning learning system.
Fast learning does not mean reacting to every opinion
The fastest-learning team is not the team that changes direction after every conversation.
That would not be learning. It would be noise-driven movement.
A customer can misunderstand the proposition. A participant can be outside the intended segment. A potential buyer can reject a genuinely valuable idea because the timing is wrong. Evidence varies in strength, relevance, and representativeness, and leaders still need judgment.
Disciplined learning requires the team to make its assumptions explicit, design credible ways to examine them, evaluate the evidence carefully, and update its decisions proportionately.
Research on scientific approaches to entrepreneurship supports this distinction. In a randomized controlled trial involving 116 Italian startups, Camuffo and colleagues found that entrepreneurs trained to articulate theories and test hypotheses systematically performed better and were more likely to pivot when the evidence warranted it [6]. A later replication involving 759 firms across four randomized controlled trials found that the approach increased idea termination and encouraged a more selective pattern of strategic change rather than either never changing or pivoting continuously [7].
The implication is not that ventures should imitate laboratories or that every commercial question can be settled experimentally. It is that confidence becomes more useful when assumptions are visible, alternative explanations remain possible, and evidence is allowed to change the decision.
The fastest-learning venture is not the one that changes most often. It is the one that becomes less wrong without wasting unnecessary time and capital.
Confidence should belong to the learning system
A venture still needs confidence, but that confidence should not be concentrated in the leader’s current answer.
It should belong to the learning system.
The team should be confident that it can identify its most consequential assumptions, reach people who know more than those inside the room, distinguish polite interest from meaningful behavior, and respond when reality contradicts the strategy.
A strong leader can say:
This is our current direction. This is the evidence supporting it. This is what remains uncertain. This is what would change our mind, and this is how much we are prepared to invest before we know more.
That is not weak communication. It is a more demanding form of leadership than pretending the answer has already been earned.
It gives the team direction without protecting that direction from evidence. It gives sponsors a basis for deciding what the next budget should purchase. It also allows sales, marketing, product, and research teams to return with uncomfortable findings without being accused of lacking faith.
The team no longer has to believe in every assumption. It has to believe in its collective capacity to learn.
Sponsors create the confidence they reward
Investors, executives, and corporate venture sponsors also shape this behavior.
When they reward only certainty, teams learn to perform certainty. When they ask only for visible progress, teams present activity. When every change of direction is interpreted as evidence that the original team was wrong or weak, leaders delay admitting what they have learned until adaptation becomes expensive.
A more intelligent funding system asks what the venture believed at the beginning of the current funding period and what it understands differently now. It asks which assumptions became stronger, which weakened, and which remain unresolved. It examines what evidence arrived from outside the team and what decision will become possible after the next investment.
Budgets should be released in increments that match the maturity of the evidence.
At the beginning, a modest budget may be justified to investigate whether a sufficiently important and reachable customer struggle exists. The next increment may examine willingness to switch, budget ownership, pricing, and the buying process. Larger commitments (especially building solutions) become reasonable as the venture earns stronger evidence about demand, delivery, economics, retention, and scale.
This is not a demand for certainty before action. It is a requirement that each increase in commitment be connected to an increase in decision-grade understanding.
The venture is not funded to make the original leader look right.
It is funded to prevent the organization from remaining wrong for too long.
Our advantage is learning what is true faster
The draft that triggered this article concerns AI-assisted decision-making, not venture leadership. My extension from individual self-assessment to startup and corporate venture behavior is therefore an interpretation based on my own experience, not a conclusion the authors claim to have tested.
Yet the distinction between perceived expertise and confidence in a current judgment explains something I have repeatedly observed.
Venture leaders need confidence in their capability. They require enough resilience and ego to withstand rejection, mobilize other people, and move through environments in which the path is not obvious.
That confidence becomes dangerous when it is transferred to an untested interpretation of the market.
Once the leader’s current judgment becomes part of the team’s identity, market evidence can become a loyalty test. People who return with weak signals are accused of not believing. Sales and marketing are blamed for failing to execute a strategy that nobody is permitted to question. The venture becomes increasingly organized around defending the answer it was originally created to investigate.
The alternative is not timid leadership. It is a more ambitious form of confidence:
We are building the fastest-learning team in our ecosystem. We do not need to be right from the beginning. We want to understand what is true faster than anyone else.
The strongest venture leader is not the person who never doubts the idea. It is the person who makes it possible for the entire team to discover that the idea may be wrong without turning learning into betrayal.
We do not need to be the boldest-looking tree in the forest.
We need to understand the forest fastest.
Paid learning and application: The Fastest-Learning Venture Review
The argument becomes valuable when it changes a real investment decision. The Fastest-Learning Venture Review is designed for a startup or corporate venture requesting another meaningful commitment of money, time, people, or organizational credibility.
Its purpose is not to assess whether the leader appears confident enough. It is to determine whether confidence is attached to the team’s capacity to learn or to a current judgment that the evidence has not yet earned.
