Emergence Capital

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[Emergence Capital @emergencecap]

Doomers are counting what AI will replace. The focus should be on what it can preserve: human judgment.
Emergence Founder and GP @gordonritter makes the case in @FortuneMagazine: "Your people are the only truly defensible algorithm you have." https://t.co/Ra5PRxKWu1

[Emergence Capital @emergencecap]

Our AINS Summit is at capacity. For everyone who didn't get a spot, we just launched the AI-Native Services Assessment so you can still do the work: https://t.co/Kg4z8SzVP2

[Emergence Capital @emergencecap]

Sequence matters more than most founders realize. @Carlottasini breaks down why: https://t.co/vRlaJhV1FS

[Emergence Capital @emergencecap]

Most AI services roll-up pitches have one flaw: they're solving for distribution. That's not the constraint.

[Emergence Capital @emergencecap]

And the moats you thought you were buying — relationships, process integration — are weaker than they look. AI is the first technology that gives customers a real reason to switch.

[Alex Konrad @alexrkonrad]

This is a story I've wanted to write since I first saw VC @jakesaper post about a mysterious walk with a pivoting CEO 3 weeks ago.

He's beaten the drum about AI-native services for more than a year now, and backed it up with an intro and some thoughts.

https://t.co/DrcP2w8gD2

[Newcomer @NewcomerMedia]

@agermanidis @runwayml @btaylor @SierraPlatform @AssemblyAI @graceisford @Lux_Capital .@jakesaper, general partner, @emergencecap.

All talk. All action. May 6 in San Francisco.

Apply now to join us: https://t.co/uczaY3jZfa

[Goodwin @goodwinlaw]

Before AI agents and CLM became commonplace in legal tech, @jakesaper was already placing bold bets on companies of the future. As General Partner at @emergencecap, he backed game-changers like Ironclad and SimpleLegal — long before the hype even existed.

In the latest episode, @maryshenocarro1 sits down with Jake to unpack:
🤖 What does the future of the billable hour hold?
🔁 CLM isn't dead - just evolving
🚀 How to vet startups in the AI gold rush
🎲 Where the next billion-dollar SaaS bets are being placed

Tune in to join the conversation shaping the future of legal tech.
https://t.co/2ygP7bSit9
https://t.co/pEBKibE0DF

#LegalTech #Startups #AI #SaaS

[Pascal Unger @PascalUnger]

"Finally a startup podcast where you actually learn something that matters!"

That's what I set out to do when I started having discussions with founders and operators around potentially doing a podcast.

Why?

Because most startup podcasts are basically a highlight reel that barely scratch the surface across the 20+ topics they cover. They're entertaining - but you don't actually learn anything useful.

Thus, meet the focal podcast where I go deep with some of today's best founders / operators on ONE crucial lesson they learned the hard way early on.

No fluff, just the real, actionable insights you'd get if these founders were mentoring you 1-on-1.

Our debut episode - launched today - tackles a critical mistake most founders make early on:

“Most startups don’t focus on growth nearly early enough.”

This comes from @austinh___ who knows startup growth better than almost anyone else.

As a former early growth lead at @tryramp and now the co-founder and CEO of @unifygtm (>$30M raised from @ThriveCapital , @emergencecap, @OpenAI), Austin has both built a growth organization from scratch as well as helped scale one faster than almost anyone else.

A few weeks ago, I had a fascinating conversation with him that changed how I think about growth at startups, including:

1. Experimentation speed is everything
2. Why you have to start with outbound from day 1
3. To win, move from cold to warm outbound
4. Why to build your growth team as early as possible
5. The ultimate startup moat: Building in public

Starting tomorrow, I'll also share insights from these conversations in writing.

For more, check out our conversation on the newly launched focal podcast and subscribe to my Substack for the write ups (LINK IN COMMENTS).

[Abhishek Doshi @abhishekddoshi]

This essay from @emergencecap hits harder now than when it was first published.

For years, GenAI models have been trained on public internet data—unstructured, noisy, and not always high-quality. It got us surprisingly far, but we’re quickly approaching the ceiling of what that data can offer.

What’s next is already unfolding: proprietary data.
✨ McKinsey just launched a generative AI platform built on 150+ years of internal research, cases, and insight.
✨OpenAI has signed content licensing deals with The Wall Street Journal, The Atlantic, Vox Media, and more.

These partnerships are quietly opening the second tier—where models get access to structured, filtered, high-value content. And as more of this comes online, the quality of AI output won’t just improve—it’ll jump.

We’re stepping into a new innovation window. The data that used to live behind the firewall is becoming the differentiator.

[Alif @alifdotbuild]

A full circle moment at @emergencecap.

[Emergence Capital @emergencecap]

9/
AI success = user behavior × proprietary data × continuous learning.

Don’t settle for “demo AI.”

Build the perpetual algorithm.

[Emergence Capital @emergencecap]

1/
Most AI software isn’t evolving.
It’s just performing.

That’s why we built the Emergence Rate — a framework to measure whether AI products are actually learning and improving in the wild.

🧵 Here’s why it matters (and how to use it):

[Emergence Capital @emergencecap]

8/
If you’re building in AI:
Track your Emergence Rate.

If you’re buying AI software:
Ask how quickly it evolves.

And if you’re investing:
Look for products where customers are the secret proprietary training data.