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Tyler Tringas Profile picture
@tylertringas
Sep 22, 2020 • 6 tweets • 1 min read • Read on X
The magic formula: a founder with
1) an unfair advantage
2) in a strong market
3) with compounding benefits
1/ Create an unfair advantage. I think of these as mostly in either the Differentiation or Distribution buckets.
Differentiation is about product. It can be:
* A deep understanding of a niche market from experience in it
* Pace: the ability individually or as a team to ship high quality + quickly
* Combining multiple areas of competency to create a world class intersection
Distribution is about reaching and convincing customers. Can be:
* An audience that trusts you and wants you to win
* Authority and brand within a space
* Expert knowledge of certain growth strategies
* World class sales competency
2/ In a Strong Market is one with demand, momentum, and growth but is best when it's slightly a secret because:
* demand is orthogonal or non-obvious
* customers are overlooked/unsexy
* you get in early
* everyone thinks it's been tested and failed
3/ Compounding benefits means your unfair advantages get stronger over time and it comes in many forms like
* Become the default brand in a niche space
* Built-in product virality
* Promulgate best practices across users
* Economies of scale
* And many more...

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More from @tylertringas

Tyler Tringas Profile picture
Apr 25
Some news: After 2.5 years and a tremendous waste of energy & money, @calmfund has resolved our litigation with SureSwift on very favorable terms.

We signed a settlement agreement that dismisses everything and a global release of claims. We refused to sign an NDA, so we are absolutely free to speak truthfully about the matter. And we didn't pay a dime of settlement money. All we agreed to was to find a buyer for their stake in our funds, something we wanted all along! (more on that soon)

I'll be unpacking this more over time, but here are a few of my biggest lessons learned from one of the most challenging periods of my life:
The Delaware legal system is totally broken for defendants. Even if you win it's extremely rare for the other side to even have to cover your attorneys' fees, much less any damages for the lost time and energy. The best case scenario is you spend a bunch of money to still be not guilty of anything.

A demand for a settlement has asymmetric downside for defendants, even if they've done nothing wrong: do you want to pay us some amount for a 100% chance of making this go away now, or spend much more with a less than 100% chance of winning at trial? This is why ~98% of civil cases in up in a settling before trial.

Understanding this ahead of time has real implications for decision-making as an entrepreneur.

For example, the actual language of a contract almost doesn't matter unless the underlying issue is worth $2-3m+. No matter how iron clad the language of a contract, the other side can always raise enough doubt or fact questions to force the matter to trial and it can cost $1m+ to litigate through trial. So contract disputes over smaller amounts mostly depend on leverage or a willingness to outspend the other side. Consider this in your future contract negotiations.

Also, I now deeply understand why so many experienced people in business have a strict "no a**holes" policy. I always thought this was throwaway marketing, but it only takes one lawsuit like this to make it clear how incredibly valuable it is to work with people you trust.
AI probably saved my company. Initially I thought the right approach was to just pay lawyers and let them handle it. But somewhere in the middle of this journey I felt our very expensive lawyers were not doing a good job and giving me only crappy options. But we could barely afford them, much less spending a fortune on a second opinion. I really felt trapped. Credit to my partner who suggested I just take charge of the situation myself.

I started using AI to review all the contract & filings and to help me understand case law and to consider courses of action. I fired our lawyers, got new ones, and started showing up to the calls with a clear point of view on our strategy. It worked, but there's no way I could have done it without LLMs getting good enough at exactly the moment I needed.

I'm convinced every entrepreneur should start using AI to help them take charge of legal issues. Contracts are language and Large Language Models are very good at reviewing them and frankly even at creating them. Use actual lawyers more like strategic consultants rather than paying them to do all the laborious work of contract review or drafting. The bonus is that radically reducing your costs in any kind of legal process is form of serious leverage if the other party is shelling out 10x more than you.
Read 6 tweets
Tyler Tringas Profile picture
Feb 20, 2023
Ok folks, Feb marks 4 years since we started investing at @calmfund and it's time for a big update thread. It's been a challenging but insightful few quarters but I'm absolutely fired up about the road ahead. I'll cover what we've been up to, our strategy & the game plan for 2023
If you're new here, @calmfund is a fund built to support founders of calm companies that are capital efficient, grow sustainably, & built for the long term. Here is an overview of our high level investment thesis (we used to be called @earnestcapital btw):
"Calm company" is both an investing strategy and a mindset for founders looking to build a company in a manner that I call "being long-term ambitious" ... here are some of the key principles to give you a sense of what it means:
Read 32 tweets
Tyler Tringas Profile picture
Feb 19, 2023
I think folks are sleeping on one of the biggest and most obvious "zero interest rate phenomena" that's going to get vaporized slowly and then all at once: Andreessen Horowitz

Here's my thesis:
In recent years a16z built an incredible machine to accumulate "assets under management" (AUM) to the tune of tens of billions of dollars. Nominally they were supposed to be doing venture capital—investing in startups and entrepreneurs—but really they were making a different play
As I laid out in 2021, they (along w hedge funds like Tiger) identified there were vast pools of capital searching for *any* returns in the zero-interest-rate wasteland and came up with a fundamentally different strategy from the traditional VC model
Read 17 tweets
Tyler Tringas Profile picture
Feb 17, 2023
Good morning, AI-based tools will be a massive opportunity for calm companies, but a dud for VC. Here's my thesis:
1/ this market map will become an iconic case study of "was a feature not a product" with all of the value ultimately being split between the actual core AI platforms in the top left corner and incumbent software tools with distribution (mostly not shown) who will add AI features
2/ It's almost a meme/joke at this point, but the vast majority of these products are just (a) an API call to GPT-3 or similar platforms and (b) a thin layer of "prompt engineering"

This is the most nonexistent moat in the history of tech waves with no clear way to improve
Read 18 tweets
Tyler Tringas Profile picture
Nov 24, 2022
✨ Cultivating a Calm Company ✨
A running thread of the most important things I have learned about building a calm company and being long-term ambitious as an entrepreneur. Let's go 🙏👇
Note: I plan to expand on each of these in short essay form. Subscribe to the @calmfund email list to receive them: tyler-tringas.ck.page/94b41c3e91
Chaos inevitably happens in business. Sometimes the answer is taming the chaos, sometimes you just need to get comfortable in the chaos.
Read 31 tweets
Tyler Tringas Profile picture
Nov 22, 2022
People keep asking me "why aren't more investors using a strategy similar to @calmfund's"... the answer is very simple: it is *unbelievably* difficult to raise capital for an early stage fund that doesn't fit the traditional VC model. That's it.
For our first 3 small funds we had to raise money from nearly 200 individuals. I had to write 200,000 words of content and build a fully automated fundraising funnel such that for Funds 2 & 3, I didn't even speak to >half of the investors before they committed.
But those funds were "sub-scale" (<$10m)... in order to really address the market need, build a fully staffed team, and get the best returns for our LPs, we need to raise substantially larger funds (like $100m... still tiny in the scheme of things)
Read 8 tweets

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