Hey friend 👋

TechGames = Games x Maths x Startups.

Last week’s drop stirred the pot - our inbox has been full of people asking for both founder AND investor maths (investors won by a few votes though). So let’s get into it!

Every edition gives you:

• 👾 Incoming Games: curated tech poker, chess, Catan, and more each week

• 🧮 Startup Game Theory: maths applied to startups

• 🫂 Community Shoutouts: celebrating the crew

• 🚀 Accelerating you: asks + intros to help you win

Know any high-signal startup founders, investors, or operators? Please bring them in & let’s make that big! 🔥🙏🏼

👾 Incoming TechGames

Aug 21 | ♦️ Tech Poker Games #34 (London 🇬🇧)

A high-signal evening for top-tier founders, operators, and investors to connect, compete, and read each other like a term sheet - over high-stakes poker. APPLY here.

Sept 4 | 🐑 Tech Catan Tournament #4 (SF 🇺🇸)

Settle, trade, and outwit at the world’s largest curated Catan gathering for extraordinary tech builders, change-makers, and leaders. APPLY here.

Sept 4 | 🐑 Tech Catan Tournament #2 (Zürich 🇨🇭)

The Swiss edition of our legendary curated Catan nights. Out-trade and out-build alongside Europe’s most exceptional founders. APPLY here.

Sept 11 | 🐑 Tech Catan Tournament #2 (Berlin 🇩🇪)

Europe’s sharpest tech minds meet over roads, cities, and sheep. The most curated Catan room in Berlin. APPLY here.

Sept 19 | ♦️ The SF Tech Poker #3 (SF 🇺🇸)

Elite founders, operators, and investors face off in an evening of cards, reads, and calculated risk — poker as a founder’s sport. APPLY here.

Sep 21 | 🎮 Tech “Among Us” Games #1 (🌍 Online)

By popular demand, we’re taking TechGames online. First up: Among Us - the ultimate test of persuasion, strategy, and reading people. Relax, scheme, and laugh with fellow big-brain founders from SF, London, NYC, and beyond. As always, curated crowd only. APPLY here.

Sept 25 | ♟️ Tech Chess Tournament #3 (London 🇬🇧)

Precision, patience, and bold plays. Battle London’s top tech talent in a room where every move counts. APPLY here.

🧮 Startup GTO - Becoming a “Game Theory Optimal” Startup Investor

Forget the noise. The internet is flooded with flashy stories, recycled advice, and endless contradictions about what makes a great VC.

What follows isn’t just another opinion piece - it’s a toolkit for thinking and acting like an elite.

This week, we break down startup investing through a game-theoretical lens, laying the groundwork for how to think—and win—like a top-tier investor. We also get our first result.

1) Defining VC Investing through Game Theory

Seen through game theory, startup investing isn’t roulette or chess. It’s poker played on a stochastic board, with asymmetric payoffs and incomplete information.

• The VC investor (player) has fixed capital C

• They allocate it all into n startups {S_1, … S_n} over Y years (fixed)

• Each startup S_i has:

  • Probability of success p_i

  • payoff multiple M_i (e.g., M_i = 100 if it becomes a unicorn, 0 otherwise)

  • Investment size I_1, …, I_k

    • Note: because follow-up investments are allowed, we’ll write I_ij to denote the “j-th” investment into startup “i”, M_ij the payoff factor for that investment, and “t_ij” the times at which that j-th investment happened.

The game & how to win:

Find the combos of

• Startups S_i

• Investment sizes I_i1, …, I_ik timed at times t_i1, …, t_ik
  (under the constraint that all capital C all deployed over Y years)

to maximise the below expected payoff

where M_i & p_i are unknown.

2) Understanding the Fundamental Assumption of Venture Investing (FAVI)

There is an important assumption that comes up very often in our models & is at the origin of many of the deviations from many traditional financial mathematical results.

While an emergent property of how startups and markets behave today (2020s–2025), it’s called “assumption” because it’s not an immutable law of nature.

That’s why we call it the “fundamental assumption of Venture Investing”.

It states that the distribution of VC deal returns follows a power law.

We call cases where the exponent alpha is large “Strong FAVI” (e.g., pre-seed investing). If the exponent is small, we call such cases “weak FAVI” (e.g., growth investing).

If you want me to dive deeper into why/why not that’s the case, let me know.

3) Our First practical result: “chase the outliers”

We haven’t done much, but coupling the game definition + the FAVI is already enough to get our first insight.

We’re calling it the “theorem of venture investing”.

Basically, under FAVI, the expected payoff we defined above that the investor wants to maximize can be approximated as a sum over startups with high payoff multiples. (The stronger the FAVI assumption, the better this approximation is.)

This means that the set of optimal VC investment strategies (whatever they are) can roughly be approximated by strategies that only target startups with high M_i, we’ll call “outlier-centric strategies”.

Outlier-centric strategies just ignore any companies with a payoff return that’s below a certain threshold (we call “mu” here).

This means that to invest optimally, anything that doesn’t seem to indicate a high enough payoff return M (e.g., high TAM, growing market, etc) needs to be instantly discarded.

You’d be wasting your time considering it.

4) We opened up a treasure chest with other ones in it

We’ve just cracked open the first treasure chest—and found it’s full of more chests.

Each contains golden nuggets that get us closer to understanding how to play like the best in the world. We’ll unpack them in the coming weeks.

Questions we’re in a position to answer soon:

1. What’s the most optimal threshold mu to use & how to compute it?

   (Note: there is a way to mathematically derive it given some extra parameters that fit your situation)

2. How to go around estimating the payoff return M for a startup?
   (Note: there are multiple strategies for this, depending on which meta strategy you pick)

3. What’s the most optimal way for you to size your investments on a startup S_i if you know their payoff M_i and success rate p_i?
   (Note: there is a very precise formula we can derive)

4. As there is a time constraint on how to deploy the fund, how to balance investing versus waiting for a better deal?

   (Note: there is a very precise framework that optimally balances it.)

I’m hitting this week’s character limit for this section (I want it to be as digestible as possible for you guys & readable in 2-3 minutes).

Please tell us what you want cracked open next - just hit reply or use the survey below. We’ll build this map of venture together. 😎 

🫂 Community Shoutouts

Little throwback to a couple of months ago in SF when we ran the Tech Chess Poker tournament. Epic final between Vlad & Lukas! (So epic it got me back into practicing my chess fairly seriously for a bit 👀 )

🚀 Accelerating you

• Eito Miyamura (CEO/Founder @ Edison.watch) is looking for introductions to CISO / CCO / CRO in a fast sales cycle (<6 months) enterprise adopting AI and terrified of data exfiltration. If you know anyone, reply “EITO” to this email and I’ll connect you.
  

We’re looking into facilitating connections between you, i.e., some of you are really insane AI engineers looking for a job, while others are founders who are hiring. If you want us to put the network to your use, please fill out the form below!

💌 See you Next Week!

If you want to chat about anything, hit reply - we read everything!

Please give us your feedback below on the content - help us iterate & help you win! 🙏🏼

Also, if you know insane people who think like us here, please bring them in!

A lot of stuff is brewing, we can’t wait to announce it & build it all with you!