Unfortunately I read this too late. I learned the hard way that u gotta find product-PROMISE-market fit first.
The longer ur deal cycle, the costlier it gets to skip validation. Mine was 9-12 months!
2/ Be sales-driven, not product-driven.
Here's a diagram from @HuaNancy. It divides startups into 4 quadrants: hard/easy to sell, hard/easy to build.
(i.e. What type of game are u playing?)
Optimizing to win begins with knowing what game you're even playing in the first place.
Sounds duh.
But we got it wrong.
We thought we were quadrant IV (hard to build, easy to sell). We were actually quadrant I (hard both).
We were an enterprise sales company who didn't understand consultative sales.
We thought we could focus 200% on development; 5% on deal funnel.
The combo of not validating first AND not knowing how to do consultative sales was toxic. Not only did we not understand our customer demands from day #1; we made it impossible to learn over time!
Lessons:
- ask more questions; pitch less
- customize; plug-n-play is a myth in B2B
3/ Founder-market fit.
Here I was running a cyber risk modeling startup but didn't have the network of a Unit 8200 Israeli Massader.
Relative to many other cyber startups, we were massively disadvantaged in our ability to attract talent & establish industry partnerships.
4/ Co-founder fit.
There are only 2 good reasons founders should pair up: 1. personal compatibility (will stick together through big pivots) 2. business compatibility (skillsets & network are a match specific to THIS problem)
IMO, unless someone checks BOTH boxes, stay single!
Max likelihood outcome of #1 w/out #2 is you'll pivot a bunch & run slower than a team that has founder-market fit.
Max likelihood outcome of #2 w/out #1 is the company splits. Most likely ur visions aren't perfectly aligned. Imagine if your two legs each had minds of their own.
Last important note on team structure:
Having the right network but not skillset makes for a great advisor (not a great cofounder). This person may be super high-value to the company but their value doesn't increase when they stick around day to day.
5/ Division of roles.
As founders we hear all the time that u gotta "wear multiple hats." That's awesome until u come across a hat that fits 2 heads. Who takes point?
Hesitate too long and the ball ends up rolling down the middle untouched.
Or you both pounce & do double work.
I was CTO but didn't want to be.
I was doing things I wasn't awesome at, and not doing things I was awesome at.
Not leading sales gnawed at me; my reluctance made me a terrible eng manager. My team told me that trying to get big-picture context from me was like pulling teeth.
My story has a happy ending!
I'm building a new startup now-- a tool for retail traders like you and me!💗
Today's capital markets are built for hedge funds, not us individuals. Let's change this!
Expect a beta release in December! I'll be documenting pieces of my journey here!
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Each week I write a 🧵about investing, startups, or a cool market segment. All of it is knowledge my mentors & friends have taught me over the years.
🙏💗Now I'm passing it forward.
Here's a megathread of all past & future 🧵s. I'll be updating as we go. If you <3, plz share!
👇
1/ 💸 Jim Simons’ Playbook: King of Quant 💸
90% of active managers fail to beat the market, but Medallion boasts >40% annualized returns.
For the last 10 yrs, hedge funds swarmed at "alternative data" like pigeons at bread crumbs. Why? What exactly constitutes alt data & does it actually generate investment alpha?
👇
1/ What is it?
"Alternative data" is just a fancy term for data that doesn't appear on a 10-K/Q or earnings transcript.
Things like foot traffic at a retail store or credit card orders at a restaurant. Such data helps hedge funds predict earnings better (supposedly, at least).
2/ What are some common data sources?
App usage-- # of downloads over time is used to predict MAUs/DAUs & forward adoption rate; reviews also used to gauge product quality
Supply chain & logistics-- used to predict inventory & sales bottlenecks, pricing/bargaining power, etc.
In 1926 McKinsey was a small tribe of bean counters led by a nobody accounting professor James. 95 yrs later that small tribe grew to a $10B ARR behemoth w/ 90 of the F100 as clients.
How?
What was McKinsey's secret sauce to world domination?
👇
1/ Language.
She who masters language wields the ultimate power of category creation. With this, all else falls into place.
McK’s biggest secret is that it category-created "management consulting.”
Projects aren't jobs; they’re “engagements.”
McK isn’t a bizniz; it's “The Firm”
Firing isn’t firing; it’s “corporate downsizing” and “increasing the bottom line.”
These nuances may seem trivial.
But we humans are storytelling animals. Nuances drive our narratives & narratives shape our aggregate spending. Today management consulting is a $255B industry. 🙀
Ryuk is the biggest Saas unicorn u've never heard of.
$150M ARR.
3 yrs old.
Maybe it’s taboo to learn business strategy from a cybergang. But the ransomware industry-- from supply chain operations to market microstructures-- is truly genius.
👇
1/ Some Highlights
$20B is the annual cost of global ransomware
$5M was the total payout to hackers @ Colonial Pipeline
$170K is the avg payout
2020 saw a 900% growth in fileless malware
67.3M attacks detected so far can be traced back to Ryuk
Every 11 seconds is a new attack
So how much $ do tier-1 ransomware gangs actually make?
The pie chart below shows total ransom paid to the top 15 groups in 2019. By 2020, outflows increased 311% YoY to $350M. Financial success in the cyber underground is clearly top-heavy, tracing out a power law distribution.
🤫Semi-Controversial Career Advice U Don't Want to Admit But Should🤫
How many cute fortune cookie aphorisms do u tell urself to feel better: "no pain, no gain" "it's the journey that counts!" And by now, how much progress have u sacrificed just to feel better?
Let's dig in👇
1/ Close doors early.
Stop putting life on the back burner just to "preserve optionality." Some ppl go into banking/consulting b/c it keeps doors open. It's a 2yr deferred ticket to HBS where u can then continue to preserve optionality! Hooray! Ur gonna be a generalist forever!
2/ Stop being a generalist.
"I'm good @ everything!"
Well for everything ur good at Billy/Sally is AMAZING at. Don't drink the liberal arts marketing kool-aid. They need admission money so they feed you b*shit. Been there done that. I wasted too many years of life. Save urself.
🏦Fed Jargon 101: A Primer on Hawks, Dots & Monetary Policy🏦
No matter what type of trader u are —discretionary, macro, crypto, chad, virgin— everyone obsesses abt the Fed.
But why? Here's a 🧵 on how Fed moves markets, controls ur PnL & the odd lingo we use to describe it.
👇
1/ Beta
#1 reason any trader cares about the Fed is to predict beta.
What's that?
Say u made 120% returns in 2020. Are u a genius or did u just own a buncha tech stocks as #jpow cranked the moneyprinter? Beta is the overall equity market risk (aka rising tide floats all boats).
To be "long beta" means ur net long stocks. "Short beta" means ur net short.
Beta on a single asset refers to correlation to an equity benchmark (eg SPY).
β>1: more volatile than SPY
0<β<1: less volatile
-1<β<0: less volatile & anticorrelated
β<-1: more volatile & anticorrelated