VC is hard.

Hitting consistent top-tier returns for your LPs across multiple funds is a great achievement.

Unfortunately, for a professional, actually learning the job and improving is super tough.

For early-stage investors, feedback loops can stretch beyond a decade. By the time outcomes arrive, both you and the market have changed. The only durable record of decision quality is the investment memo and some minutes.

When you try to learn from others — asking peers, senior investors, even from those “top-tier” VCs — about their wins and losses, and you keep digging into the “why”, you often hear the same old clichés. For failures: “Bad timing”, “Just bad luck”, “The co-founder left”, and the list goes on. For successes: “I always knew they'd be huge”, “It was a no-brainer”, “We clicked with the founder from minute one”, you get the idea.

My favorite part is when you ask what it really takes to excel in this profession, and you get the response: “Find great companies, close the deals, support them, repeat”. However, when you try to dig a little deeper, you rarely hear something specific and actionable.

All this stems from a surface-level reasoning that sometimes characterizes VCs as a group. And here's another worrying thing, especially in the European VC scene that I am a part of: work evaluation and career progression seem to be misaligned with a VC’s north star, the actual returns to their LPs (DPI). It has become an open secret in the industry that to advance to a Principal or a Partner level in many firms (irrespective of tiers), you need to bring (source and close) a “hot” deal — even if “hot” really means inflated, over-diluted, and destined most probably for a write-off within a few years. Very few, if any, focus on the actual returns of the investment or the quality of an investor’s thinking.

I recently read Thinking in Bets by Annie Duke, which highlighted common cognitive biases we often face and offered practical tools to move closer to unbiased decision-making. It is shocking to consider how many investment decisions have been affected heavily by these biases and how we tend to “learn” in the industry. On the other hand, this also presents an opportunity for anyone who aspires to excel in this ecosystem in the long term.

Taking a step back, the book initially shows us through real examples how we humans tend to 'result' — the cognitive bias of judging a decision's quality solely by its outcome, failing to account for the role of luck or uncertainty. Along the way, the writer points out more biases that shape our decision-making and how we learn. It then provides techniques to unbundle the decision quality from the outcome and to embrace the uncertainty that is inherent in everything we do. Unfortunately, we cannot completely avoid biases, but by adopting these techniques and becoming 'truth seekers' - people who genuinely want to know the truth, even when it contradicts their existing beliefs or feelings — we can sustainably improve our decision-making. According to the book, every decision we make is a bet on a particular version of the future. These bets are guided by our beliefs — many of which are untested and biased.

In VC, an investment is the result of a decision — essentially, a bet on a particular version of the future we believe is highly probable. In this decision-making process, we take into account publicly available information about the market and the company, non-publicly available information about the market, our experiences and biases, and the factor of luck (uncertainty). The factor of uncertainty cannot be removed from the equation and the future outcome, and cannot be controlled. The better and more sophisticated work we put into the acquisition and analysis of relevant information and our decision-making process, the less room we leave for the impact of uncertainty.

Information Acquisition: Turning Asymmetry into Advantage

Information acquisition is paramount in our job. This information can be publicly available and non-publicly available.

The way we filter this information, cleanse the data of biases, and most importantly, synthesize them into proprietary insights, can have the biggest impact during the decision process.

Overall, the startup world is characterized by a heavy information asymmetry. The earlier the stage of the company, the greater the role it plays. This asymmetry can become either a strong competitive advantage or a key failure factor for an aspiring VC investor.

Channels for Proprietary Insights

• Portfolio Companies Monitoring: By staying close to the portfolio companies (both founders and key employees), one can get a wealth of information about industries, markets, and even new investment opportunities, among others. Most importantly, it will need to set the right framework for the quality of the acquired information.
• Data and Analytics Platforms: While not strictly non-public, some sophisticated data platforms and tools can provide deeper insights than what's commonly available. Examples include tools that track app downloads, website traffic, employee growth on LinkedIn, or even sentiment analysis from online forums and social media. The more popular the data platforms, the less non-public data you are getting.
• Customer and User Interviews: Instead of just trusting a founder's pitch, VCs need to conduct their own due diligence by speaking directly to a startup's customers or users or even potential customers (good matches of the ICP). This provides more unfiltered feedback on market needs, product-market fit, customer satisfaction, and a company's true value proposition.
• Network: A strong network is not about breadth, but quality. Access to the right operators, founders, and scouts turns relationships into proprietary insight — the true edge in early stage. The better the quality of the nodes of the network and the stronger the access to them, the stronger the competitive advantage when it comes to the information you acquire. It could consist of angel investors, other VCs, founders (portfolio and non-portfolio), industry experts, and operators in top tech companies, among others, and it could be a first, second, or even third-degree network.

Decision-Making Process: Improving the Quality of the Bets

This part focuses on improving the quality of your "bet" before committing capital. Each stage has its own unique aspects when it comes to investing, which means different adjustments are needed to the learnings from the book. Speaking from the early-stage investor point of view, the goal is to move towards a more rigorous, probabilistic process.

• Treat Your Thesis or Intuition as a Bet to be Tested: Treat intuition and investment theses as hypotheses, not prophecies. Gut instinct can be a sophisticated hypotheses generator, but nothing more; due diligence exists to stress-test these hypotheses. This process counters your confirmation bias.
  • Action: Try to challenge the intuition with specific questions.
    • Key Questions: "What evidence can we gather to confirm or deny that feeling?”, “What would have to be true for our intuition/thesis to be wrong?", "Let's assume this company fails. What specific leadership or skill-set challenge did the founder fail to overcome?"
      • Why: This exercise validates the bet on the person or the thesis by mapping their strengths against the most likely points of failure. Additionally, it prevents investors from merely falling for the founder’s charisma and forces them to validate their instincts.
• Think in Probabilities, Not Absolutes: The future is uncertain. Instead of saying “This is a no-brainer” or asking, "Will this company be a unicorn?" frame the decision in terms of probabilities and expected value.
  • Action: Turn your conviction into a probabilistic model. In the investment memo, assign probabilities to different scenarios (e.g., 10% chance of 100x return, 30% chance of 3x return, 60% chance of 0x return). This forces a more realistic assessment than a simple "yes/no." Bessemer is a well-known VC and a good example that uses a probabilistic approach in the outcome analyses of their investment memos, and they have shared a few on their website.
• Build a "Truth-Seeking" Investment Committee: Consensus is comfortable and dangerous. The best ICs are built to stress-test, not harmonize.
  • Action: You could even assign a "devil's advocate" for every deal. This person's sole responsibility is to build the strongest possible case against the investment, ensuring all critical weaknesses are surfaced. They are not on a mission to “kill the deal” but to bring truth before the decision.
• Use Mental Time Travel to Beat FOMO: The pressure of a competitive deal can cloud judgment. Creating temporal distance is a powerful antidote.
  • Action: Before signing the term sheet, you can hold a meeting and travel to the future.
    • Key Questions: "It's five years from now, and this investment has been a total write-off. What went wrong?"
      • Why: This surfaces risks (founder disputes, market shifts, technological disruption) that are often ignored in the heat of the moment.
• Use a “Pre-Parade” Check: This would help you identify the key milestones, founder actions, and firm support that would be crucial to achieving the outlier outcome and identify leverage points for proactive value creation.
  • Action: It would involve working backward from a hypothetical great outcome (e.g., a 100x exit).
    • Key Questions: “What were the key wins that led to this success?”, “What unique support did the firm provide?”
      • Why: A pre-parade forces you to identify and articulate the specific, causal chain of events that leads to a grand-slam home run. Is the entire bet based on one "miracle"? The pre-parades and pre-mortems function together as communicating vessels and help us have a more complete understanding of each case.

Post-Investment: Evaluating Decisions, Not Outcomes

This part is about learning from your decisions and actions to improve your decision-making process. The learning should be completely independent of financial outcomes, regardless of whether the investment philosophy was based purely on data, or weighted on intuition, or conviction. A great process can lead to a failed investment due to bad luck (e.g., a pandemic hits the travel startup you backed). A sloppy, FOMO-driven process can lead to a huge win due to good luck. Only by decoupling decision quality from outcomes can firms avoid learning the wrong lessons.

• Conduct Process-Focused evaluations regularly: This process can provide important learnings if we treat it carefully and decouple the decision-making process from the outcomes (the company’s state) at the time you revisit it.
  • Action: Every twelve months after the investment, review and evaluate the original investment memo as a team
    • Key Questions: "Based on what we knew at that time, was our reasoning sound?”, “Was our diligence process robust?”, “Did we ignore any red flags?", “Which founder behaviors matched (or diverged from) what we expected?”
      • Why: This allows investors to enhance the shorter-term feedback cycles and untangle the decision quality evaluation from the ephemeral ups and downs that the startups typically go through. This way, even the intuition-driven investors can distinguish bad luck from a flawed thesis, preserving their confidence to make bold bets in the future.
• Conduct Process-Focused Post-Mortems: Stay disciplined, irrespective of the result, and analyze the decision process that led you there as unbiasedly as possible.
  • Action: Every time a company exits or closes business, review and evaluate the original investment memo as a team for the last time.
    • Key Questions (Write-offs): "What were our key assumptions in the memo, and where did they prove to be wrong?", "Were there any dissenting opinions in the IC meeting that we should have weighed more heavily?"    
      • Why: The goal isn't to identify flaws in your decision-making system and not to assign blame. Rewarding an investor who ran a great process on a failed deal encourages the intellectual honesty needed for long-term success.
    • Key Questions (Positive Outcomes): "We got a fantastic outcome, but was our decision process sound?”, “Did we skip diligence steps?”, “Did we give in to hype?", “How much of this outcome was because of luck?”
      • Why: When there is a good outcome, the firm must resist the urge to simply lionize the sponsor’s "vision”. This prevents the firm from learning the wrong lessons and reinforcing bad habits that will eventually lead to losses.

Something I haven’t emphasized enough so far, but is crucial in the whole process, is clearly articulating our thought process when preparing our investment memos. The investment memos will be the single source of truth when we and our teams evaluate our decision-making process (especially during the post-mortems). Anything else is easy to change and prone to bias, and thus not suitable for use in our feedback mechanisms.

None of the above can happen consistently if we have untamed egos and prefer to bend reality to fit our beliefs rather than the other way around. It’s hard to become a truth seeker, but it’s essential to avoid the cognitive traps that often lead to real losses. Embracing luck in our work, developing a process tailored to our job needs, and focusing on that rather than just the results can help us improve our decision-making and avoid more biases.

Building an entire company of truth seekers may be difficult and even unnecessary. Though for a VC firm’s investment team, truth seekers and their values are vital to long-term success. While each of us should take responsibility for becoming truth-seeking individuals, VC firms must embrace truth-seeking as a disciplined, long-term commitment—led by strong leadership and a readiness to challenge established norms.

In a period with so much noise (once again), it is paramount for any investor who wants to keep advancing in this infinite game to stay focused. While the journey to consistent top-tier returns is tough and full of unknowns, the path forward is clear. It demands a relentless commitment to truth-seeking, a disciplined process that embraces luck and mitigates bias, and a firm culture that values intellectual honesty above all else. Implementing such a rigorous framework takes grit and a willingness to shake up old habits. Yet, for VCs committed to building enduring firms and compounding returns, decision quality is not an aspiration — it is the only durable edge in a probabilistic world.

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