Lars

[Elad Gil @eladgil]

People at major AI labs (using internal models) 3-4 months ahead of startup silicon valley engineers

SV founders/eng 3-6 months ahead of NY

NY founders/eng 6-12 months ahead of rest of world

Most people have no idea how fast AI shifting as 1-2 years behind SOTA

"The future is here, just not equally distributed" - Robert Heinlein

[Alfred Lin @Alfred_Lin]

Playbook for building a legendary company:

- Bring together an outlier team
- Have that team come up with a novel and compelling insight
- Turn that insight into a product or service offering and iterate that offering until it has a compelling value proposition
- Turn that compelling value proposition into a unique one
- Take all of those already hard ingredients and weave them into an economic engine that has a sustainable competitive advantage
- Do all the above again and again, so the company can compound growth at scale

None of these are easy. But if it was easy, everyone would do it.

[kiran @kiran1]

https://t.co/BT7oYyTJA4

[Alex Rampell @arampell]

There are effectively three kinds of SaaS and it seems the (public) markets can’t tell the difference between the three with the coming AI wave.

Group 1: Software utility is not tied to heads, or if tied to heads not based on those heads delivering an outcome WITH the software. Companies can’t cut back on Workday seats because of AI! Quickbooks is used in small businesses. These systems of record will add AI features which will be accretive to revenue — think background checks for Workday, collections for QuickBooks, etc.

Group 2: AI potentially lowers # of users of the product but potentially introduces more usage? If you need fewer graphics designers you might need less Adobe licenses, but it’s possible you need more? Or the expanded output and productivity gains of AI increases usage?

Group 3: Software utility and pricing are DIRECTLY based on heads using software, where AI directly erases heads for the vertical. Zendesk falls squarely in this category. Theoretically CRM could, too. Without a pivot to outcome based pricing, these guys are in trouble.

But there’s a huge difference between the three. The best companies often have hostages, not customers — and they will maintain pricing irrespective of AI usage.

There’s another thread of “companies will vibe code their own software” but unlikely for critical systems of record where renting is cheaper than owning (hence the shift to SaaS from On Prem starting 20 years ago!)

[Sam Altman @sama]

A thing often in common among great startup investors, founders, and researchers:

Trading making a lot of small mistakes in exchange for getting a few giant wins.

(Surprisingly many people seem to prefer a few big mistakes in exchange for a lot of small wins.)

[Y Combinator @ycombinator]

Sagaland is a UGC games platform where players create and remix games using AI.

They're starting with interactive story games and have hit $200k ARR in 4 weeks.

Congrats on the launch, @srijanyaham & @jeankaddour!

https://t.co/YaxXFAbBZq

[Jack Altman @jaltma]

I heard the term "forward deployed VC" meaning "investor who's helping a company" and now I'm logging off for the rest of the year.

[Grant Lee @thisisgrantlee]

During our seed round in 2020, an investor laughed when I was pitching, called Gamma "the worst idea I've ever heard," and hung up mid-call.

We've now raised at a $2.1bn valuation.

This is the story and every fundraising lesson I learned:

[Keith Rabois @rabois]

True, ancient Peter Thiel technique.

[Nivi @nivi]

Without a constant stream of groundbreaking new products, you have a dead organization.

[Joshua Kushner @JoshuaKushner]

people who make non-consensus decisions to join a company make non-consensus decisions at the company

[near @nearcyan]

i wish i had an agent to help me book a flight or order food, two activities i often need help with

[karbon 🐺🦊 @karbonbased]

This is another part of the broken social contract.

Boomers got to buy:
AAPL IPO at $1.8b mcap
MCD IPO at $33m mcap
MSFT IPO at $780m mcap
INTC IPO at $58m mcap
HD IPO at $60m mcap
NIKE IPO at $220 mcap
AMZN IPO at $438m mcap
EBAY IPO at $700m mcap

Average return 4175x

Looking at the "good" IPOs millennials had access to (CART, BIRK, ARM, KYVO)....
Average mcap was $20.6 B
Average return to date to 1.68%

That average is being largely lifted by ARM which did a 10x
A more median view did the other three is 1.00x (flat)
And these are the GOOD IPOs, most are down horrendously

Couple outliers
FB & TSLA
META IPO at $.104b lol (2012)
Average return 17.7x

TSLA IPO $4b mcap (2010)
Average return 422x

These few good IPO's launched in the middle of the great recession, millennials were broke and unable to find work in their field. They did not have money to invest in them, boomers were again the main beneficiaries of these opportunities.

Boomers had three decades of good IPO opportunities. Millennials had 3 good IPO opportunities over the span of 20 years.

Now the IPOs are milk, dry and inflated by giant Series G rounds before you ever get a chance to invest.

[hari raghavan @haridigresses]

Obviously Roelof's a legend and one of the smartest people in the valley, but I'd love to dissect this / add a bit more nuance to this.

I completely agree with his directional point that most of VC (everyone but top decile) sucks as an asset class. But I think the same is true of hedge funds; and the top quartile in less risky asset classes like real estate etc., too.

But the nuance is that the true "venture capital" segment (formation through ~Series A or modest Series B), is probably... $20B a year? Maybe $25B?

Because the remainder of the $250B is really "private equity" being deployed by a VC firm.

When you take it down an order of magnitude, the exit expectations make a *lot* more sense. For true VC that is (over let's say 8-10 year horizons) 4-5x, so $100-125B in investor ownership ($150-200B in exits)

For the "PE" / growth equity class: theoretically a ~1.7-2x to clear a similar return hurdle, because the hold periods are, say, 3-5 years from Series D/E etc -> $350-450B.

So the total now comes to $400-600B. Nothing to sneeze at, but not $1.5T.

And then... you don't need 50 Figmas / year, but 15.

And more importantly... if a unicorn is a home run, a decacorn is a grand slam... we're seeing more of the centicorn (which I guess might be a triple crown? analogies breaking down).

Because you could have 15 Figmas, or... literally *one* OpenAI.

I'm not saying we'll have one OpenAI per year (that would be crazy), but... could we see (per year):
— 1x Anthropic / Stripe / Databricks etc.
— 3-5x Figma-scale outcomes
— 20x+ Wealthfront-scale outcomes?

All we have to do is adjust the "there are 20 unicorns / year" for inflation, and that's very plausible, and that gets us to $400B+ in exit value. Markets are SO much bigger than they used to be (10 years ago we had zero trillion-dollar companies).

Maybe I'm just too much of a techno-optimist :).

[Ankur Goyal @ankrgyl]

talked to another great team today who ripped out their ai framework

the story is the same every time -- most of the value of an abstraction is abstracting across LLMs

the rest eventually weighs you down

[Jon Wu @jonwu_]

I am once again begging you not to squander your startup's announcements.

You only come out of stealth once.
You only launch a product once.
You only raise a Series A once.

Here's how not to fuck it up:

[Esty @sai_no_hanaya]

Everyone hiring “Head of Growth”

Nobody hiring “Head of Fixing the Broken-Ass Product That Makes Growth Impossible”

[Suhail @Suhail]

The most common mistake in the game.

[Naval @naval]

Most companies fail at product and distribution but it’s easier to blame distribution.

If you’re failing at distribution, check the product.

[Garry Tan @garrytan]

This is great until someone gives your product away for free as a loss leader

Or your worst competitor turns it into a capital game and raises from big investors

Unless your moats are unassailable or your market is too small to matter, beware this strategy