The headline news is we have filled the gas tank again at USV and this tank is bigger. But scroll down to see the four areas we want to invest these funds into.
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Jay Yu 🐟
@0xfishylosopher
USV
USVinvestigating the frontier @usv | prev. @StanfordCrypto @StanfordPHIL
8.6KFollowers
1.5KFollowing
2.6KPosts
178Media
6.1KLikes
@0xfishylosopher reposted
congrats @iskdyl !! amazing to see @CatalystLabsX come to life
Catalyst@CatalystLabsX · Oct 8Introducing Catalyst.
What do you believe? How would you trade on it?
You notice data centers are popping-up everywhere, gold will skyrocket, or just know that Labubus will go out of fashion.
Catalyst researches your ideas, builds the optimal strategy, monitors events, and executes trades. Autonomously.
What do you believe? How would you trade on it?
You notice data centers are popping-up everywhere, gold will skyrocket, or just know that Labubus will go out of fashion.
Catalyst researches your ideas, builds the optimal strategy, monitors events, and executes trades. Autonomously.
0:40 0 0 0 19 2.1K 1
@0xfishylosopher reposted
A thesis should take you somewhere new.
Ours began with the possibilities of the open internet. Today, it reaches across AI, energy, financial markets, and the physical world.
We’re evolving USV alongside it, with $900M in new funds to lead more rounds, back founders for longer, and support the scale of their ambitions.
@mignano on the next chapter of USV.
Ours began with the possibilities of the open internet. Today, it reaches across AI, energy, financial markets, and the physical world.
We’re evolving USV alongside it, with $900M in new funds to lead more rounds, back founders for longer, and support the scale of their ambitions.
@mignano on the next chapter of USV.
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we raised a new fund!
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@0xfishylosopher reposted
Now you can text @Supertake on iMessage or RCS.
Last week, we shared our vision for Supertake: a world-class financial agent in your pocket that acts on your insights and works for you around the clock.
That means you need to be able to reach Supertake from anywhere, and Supertake needs to be able to reach you when something big happens in your portfolio.
Now, anytime there's a major swing (good or bad), Supertake can let you know right away by texting you.
But that's just the start. You can also text Supertake about anything:
* Start a new take on the go
* Ask it about the market or an individual position
* Get deep insights about how your portfolio is doing
* Discuss ideas you're thinking about
You can text Supertake just like you'd text a human, and it'll respond immediately.
To get started, activate texting in your Supertake settings. We'll also prompt you to turn it on next time you create a take.
Lots more coming soon!
Last week, we shared our vision for Supertake: a world-class financial agent in your pocket that acts on your insights and works for you around the clock.
That means you need to be able to reach Supertake from anywhere, and Supertake needs to be able to reach you when something big happens in your portfolio.
Now, anytime there's a major swing (good or bad), Supertake can let you know right away by texting you.
But that's just the start. You can also text Supertake about anything:
* Start a new take on the go
* Ask it about the market or an individual position
* Get deep insights about how your portfolio is doing
* Discuss ideas you're thinking about
You can text Supertake just like you'd text a human, and it'll respond immediately.
To get started, activate texting in your Supertake settings. We'll also prompt you to turn it on next time you create a take.
Lots more coming soon!
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i like this take a lot. i feel like the ai labs push for data creates a sort of a biolab-in-the-loop phenomenon, where you have research ai's identifying experiments to buy, and then outsource the actual experimental data to a biolab, before selling data back.
the biolab is essentially acting as an oem for experimental data, where they retain both the data AND the knowhow. this supplychain knowledge could allow biolabs to scale up the ladder and also create independent/domestic drug discovery loops.
i think the broader observation here is that we're entering an age of the API-fication of the oem as a way AIs interface with the real world - this loop works across bio/manufacturing/energy etc., where AI agents need some sort of real-world feedback to continue their research loops, and the OEM-in-the-loop can scale internal knowhow.
the biolab is essentially acting as an oem for experimental data, where they retain both the data AND the knowhow. this supplychain knowledge could allow biolabs to scale up the ladder and also create independent/domestic drug discovery loops.
i think the broader observation here is that we're entering an age of the API-fication of the oem as a way AIs interface with the real world - this loop works across bio/manufacturing/energy etc., where AI agents need some sort of real-world feedback to continue their research loops, and the OEM-in-the-loop can scale internal knowhow.
nikhil@uninsightful · Oct 66-12 months ago the large labs started buying bio data
this spend is starting to ramp very aggressively. the labs are somewhat indiscriminate buyers with enormous budgets. the therapeutics market has long had buyers of data (large and small pharma) but they've historically been the exact opposite of huge-budget and indiscriminate
this shift will distort the bio startup market in a bunch of ways. there will be a lot of short-termist behavior to try to get in front of this capital firehouse. but unlike the AI data labelers (mercor, et al) and the robotics labelers (mecka, et al), the bio startups serving up this data have a chance to emerge from this period with businesses that don't rely on selling data
the best bio startups will use these sudden resources the labs are dumping on them to supercharge their novel assay and work towards independently powerful models and eventually directly produce therapies
bio is the final frontier and its a very exciting time ahead for bio startups IMO
Open quoted post →this spend is starting to ramp very aggressively. the labs are somewhat indiscriminate buyers with enormous budgets. the therapeutics market has long had buyers of data (large and small pharma) but they've historically been the exact opposite of huge-budget and indiscriminate
this shift will distort the bio startup market in a bunch of ways. there will be a lot of short-termist behavior to try to get in front of this capital firehouse. but unlike the AI data labelers (mercor, et al) and the robotics labelers (mecka, et al), the bio startups serving up this data have a chance to emerge from this period with businesses that don't rely on selling data
the best bio startups will use these sudden resources the labs are dumping on them to supercharge their novel assay and work towards independently powerful models and eventually directly produce therapies
bio is the final frontier and its a very exciting time ahead for bio startups IMO
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@0xfishylosopher reposted
Say hi to @0xfishylosopher
Jay joins USV as part of our 2026 analyst class.
Jay was already a force before joining us and we're excited to see what the next two years have in store.
Read his introduction below and if you're building in the spaces he's exploring, reach out.
Jay joins USV as part of our 2026 analyst class.
Jay was already a force before joining us and we're excited to see what the next two years have in store.
Read his introduction below and if you're building in the spaces he's exploring, reach out.
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Over the last few weeks, really have felt how both @uninsightful and @fredwilson have sharpened my thinking + what it truly means to be a longterm investor
So excited to work with both of these generational GOATs!
So excited to work with both of these generational GOATs!
Matt Cynamon@mattcynamon · Oct 2Writing a check doesn’t qualify you to give advice.
When @fredwilson was 29 he tried to show up to a board meeting and start giving advice. One of the founders stopped him, “come do every job in the company for a week, then we’ll listen.” So he flew to Buffalo and did it.
With @uninsightful staying at USV as an Investment Partner, I asked the two of them to sit down and compare notes on a business they entered almost four decades apart.
Nikhil is the first analyst in our program’s 20-year history that we've offered the opportunity to stay and move up in the firm.
They covered earning a founder’s trust, building conviction before your partners agree, and staying open to ideas that challenge your strongest held beliefs. They also got into where USV has been right, where we’ve been (very) wrong, and how the venture business is changing.
0:00 Preview
1:46 Why Difficult Founders Make the Most Money
5:20 Before You Give a Founder Advice, Earn the Right
11:28 @fomo: We Passed. Then Spent Six Months Trying to Get In.
20:20 Biology Is Becoming Programmable and Opening Up to Outsiders
22:49 When Knowing Less Helps You See More
26:34 How Do You Compete With a $100 Billion VC Firm?
34:45 Why Fred Would Take His Company Public
38:01 What USV Gets Wrong About Founders
40:47 The Moat AI Hasn’t Broken: Network Effects
44:33 Who Wins When AI Becomes Multiplayer?
When @fredwilson was 29 he tried to show up to a board meeting and start giving advice. One of the founders stopped him, “come do every job in the company for a week, then we’ll listen.” So he flew to Buffalo and did it.
With @uninsightful staying at USV as an Investment Partner, I asked the two of them to sit down and compare notes on a business they entered almost four decades apart.
Nikhil is the first analyst in our program’s 20-year history that we've offered the opportunity to stay and move up in the firm.
They covered earning a founder’s trust, building conviction before your partners agree, and staying open to ideas that challenge your strongest held beliefs. They also got into where USV has been right, where we’ve been (very) wrong, and how the venture business is changing.
0:00 Preview
1:46 Why Difficult Founders Make the Most Money
5:20 Before You Give a Founder Advice, Earn the Right
11:28 @fomo: We Passed. Then Spent Six Months Trying to Get In.
20:20 Biology Is Becoming Programmable and Opening Up to Outsiders
22:49 When Knowing Less Helps You See More
26:34 How Do You Compete With a $100 Billion VC Firm?
34:45 Why Fred Would Take His Company Public
38:01 What USV Gets Wrong About Founders
40:47 The Moat AI Hasn’t Broken: Network Effects
44:33 Who Wins When AI Becomes Multiplayer?
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Multiplayer seems to be the next frontier for personal agents. but what might be a path to that happening? Here's my rough mental model:
> Phase 1 (where we are today): everyone gets a personal agent. GrokBot, Muse, Instinct etc. one human, one agent (or one human + a team of agents). the agent knows your context, but it still (primarily) interacts with the world the way a human would - scrolling sites, clicking through browser flows, filling forms, calling APIs.
> Phase 2: agent-to-agent. At the same time that consumers adopt agents, businesses (doordash, amazon, expedia) are also building in-house agents in their UIs (eg. Doordash's new text-to-order pic). At some point, the agents meet (probs in a matter of months), and A2A happens - my Muse/Instinct simply talks to Doordash/Expedia's agent, and haggles w them to build a personalized price.
The interesting part is that negotiation falls out of context asymmetry: each agent knows things about its principal that the other doesn't, and the job is deciding what to reveal. this rhymes way more with OTC trading than with a chat app.
> Phase 3: agent swarms and DAOs. Eventually, multiplayer will be more than 1:1 A2A, it will be a "congress" of agents expressing ideas on behalf of their principals. this is where DAOs become interesting again as a way to coordinate.
Back in the day i was a DAO voter, but the bottleneck was always attention/apathy - i simply could not read every forum post + proposal. but agents remove the bottleneck of human attention, and can understand your preferences, read every proposal, and advocate on your behalf. DAOs can then fulfill their potential as a structure for spinning up groups to coordinate shared resources/treasuries, becoming a coordination layer for agents to collectively make decisions.
To close the analogy, Phase 1 of where we are at is like the PC moment, where everyone has access to agents in the first place. Phase 2 is the Internet moment, where agents start talking to one another, and Phase 3 is where the agent-native, skeumorphic applications really come to life.
> Phase 1 (where we are today): everyone gets a personal agent. GrokBot, Muse, Instinct etc. one human, one agent (or one human + a team of agents). the agent knows your context, but it still (primarily) interacts with the world the way a human would - scrolling sites, clicking through browser flows, filling forms, calling APIs.
> Phase 2: agent-to-agent. At the same time that consumers adopt agents, businesses (doordash, amazon, expedia) are also building in-house agents in their UIs (eg. Doordash's new text-to-order pic). At some point, the agents meet (probs in a matter of months), and A2A happens - my Muse/Instinct simply talks to Doordash/Expedia's agent, and haggles w them to build a personalized price.
The interesting part is that negotiation falls out of context asymmetry: each agent knows things about its principal that the other doesn't, and the job is deciding what to reveal. this rhymes way more with OTC trading than with a chat app.
> Phase 3: agent swarms and DAOs. Eventually, multiplayer will be more than 1:1 A2A, it will be a "congress" of agents expressing ideas on behalf of their principals. this is where DAOs become interesting again as a way to coordinate.
Back in the day i was a DAO voter, but the bottleneck was always attention/apathy - i simply could not read every forum post + proposal. but agents remove the bottleneck of human attention, and can understand your preferences, read every proposal, and advocate on your behalf. DAOs can then fulfill their potential as a structure for spinning up groups to coordinate shared resources/treasuries, becoming a coordination layer for agents to collectively make decisions.
To close the analogy, Phase 1 of where we are at is like the PC moment, where everyone has access to agents in the first place. Phase 2 is the Internet moment, where agents start talking to one another, and Phase 3 is where the agent-native, skeumorphic applications really come to life.
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trade your takes with @Supertake !
Michael Mignano@mignano · Sep 28Introducing @Supertake, a new platform that transforms your unique takes on the world into real, shareable investment portfolios using frontier AI and trading agents.
Supertake makes it easy for anyone to invest in their ideas, even if they know nothing about investing.
1/
Supertake makes it easy for anyone to invest in their ideas, even if they know nothing about investing.
1/
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Great article by @__billygao on the importance of privacy when it comes to trading in onchain markets! Give @Sirius_Protocol a follow if you haven't already
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Wooo go @livjenkss !! Go follow her if you guys haven't yet - she's incredibly smart, kind, and just an awesome person to be around.
Extremely fortunate to have her as colleague at @usv !
Extremely fortunate to have her as colleague at @usv !
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been using the latest batch of personal agents (instinct/muse/grokbot) for a few weeks now, while navigating a career transition, a new city, and all the random errands that comes with it. a few thoughts/observations:
> imo these agents are primarily UX innovations rather than capability innovations. a smart harness on openclaw/hermes with browser scroll can do many of the tasks that these newest gen of agents are doing. the magic comes in the form factor - a direct messaging app or chat that does not require CS skills to setup (which was the case for openclaw/hermes)
> the "threading" UX between 3 agents is very interesting to observe -Instinct runs an iMessage mono-thread, Muse has monothread agent + sidechats, GrokBot is a fully multithread setup with a Chief-of-Staff coordinating. i think each UX appeals to different groups of ppl + might also be different for the context. Eg. I use GrokBot mostly for work (where I have to run multiple threads of market research/logging/dd etc), Muse for lifestyle tasks, and Instinct for adhoc errands.
> the other UX design is standalone app vs. messenger "miniapp". muse and grok are both apps, i would consider instinct a "miniapp". advantage of a miniapp is that its easier to setup/bootstrap, but you don't control your form factor. which means it is impossible to do something like "search for threads" on instinct - the agent can do a lot, but it cant change imessage's UI... On the other hand, the standalone app gives customizability, traded off for onboarding friction - I do actually have to download a seperate app, but it gives a blank canvas to experiment with new features to showcase to users.
> re. monetization of agents - this seems to be very WIP. i think GrokBot taps into X API and charges a pay-per-request + is linked to X Money. but I don't pay a cent for Instinct/Muse, even as I use them to do economic things like buy a laptop, book restaurants, haggle over subscriptions etc. the straightforward approach to monetization is to do a straight seat-based SaaS plan, or maybe some sort of per-token usage based billing. but this can hurt user acq. i wonder if theres an opp to do a per-tx tax model, where every time you make an economic transaction of say $100, the agent takes an $5 cut or something. If I get $100 back from cancelling subscriptions, I'd more than happy to give $5 to the agent.
overall, the amount of "agentic commerce" that's been happening with these agents over the last few weeks has been absolutely incredible, excited to see this evolve!
> imo these agents are primarily UX innovations rather than capability innovations. a smart harness on openclaw/hermes with browser scroll can do many of the tasks that these newest gen of agents are doing. the magic comes in the form factor - a direct messaging app or chat that does not require CS skills to setup (which was the case for openclaw/hermes)
> the "threading" UX between 3 agents is very interesting to observe -Instinct runs an iMessage mono-thread, Muse has monothread agent + sidechats, GrokBot is a fully multithread setup with a Chief-of-Staff coordinating. i think each UX appeals to different groups of ppl + might also be different for the context. Eg. I use GrokBot mostly for work (where I have to run multiple threads of market research/logging/dd etc), Muse for lifestyle tasks, and Instinct for adhoc errands.
> the other UX design is standalone app vs. messenger "miniapp". muse and grok are both apps, i would consider instinct a "miniapp". advantage of a miniapp is that its easier to setup/bootstrap, but you don't control your form factor. which means it is impossible to do something like "search for threads" on instinct - the agent can do a lot, but it cant change imessage's UI... On the other hand, the standalone app gives customizability, traded off for onboarding friction - I do actually have to download a seperate app, but it gives a blank canvas to experiment with new features to showcase to users.
> re. monetization of agents - this seems to be very WIP. i think GrokBot taps into X API and charges a pay-per-request + is linked to X Money. but I don't pay a cent for Instinct/Muse, even as I use them to do economic things like buy a laptop, book restaurants, haggle over subscriptions etc. the straightforward approach to monetization is to do a straight seat-based SaaS plan, or maybe some sort of per-token usage based billing. but this can hurt user acq. i wonder if theres an opp to do a per-tx tax model, where every time you make an economic transaction of say $100, the agent takes an $5 cut or something. If I get $100 back from cancelling subscriptions, I'd more than happy to give $5 to the agent.
overall, the amount of "agentic commerce" that's been happening with these agents over the last few weeks has been absolutely incredible, excited to see this evolve!
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Matt was the one of the first people in the @usv ecosystem I got to know - as a fellow philosophy + startups enthusiast we bonded over what it means to "do philosophy impactfully" today
It's incredible to see the vision of Cosmos Ventures come to fruition. In an era where slop commodifies right-brain labor, having a humanities/mission-driven philosophical mindset is more important than ever to drive tech for the betterment of humanity.
Excited for the future, congrats @_mattmandel @Brendan_McCord !!
It's incredible to see the vision of Cosmos Ventures come to fruition. In an era where slop commodifies right-brain labor, having a humanities/mission-driven philosophical mindset is more important than ever to drive tech for the betterment of humanity.
Excited for the future, congrats @_mattmandel @Brendan_McCord !!
Matt Mandel@_mattmandel · Sep 16Today @Brendan_McCord and I are launching Cosmos Ventures.
AI is overturning assumptions society has organized itself around for centuries. The models keep getting better, but no level of capability can tell us what kind of society we should make with them.
We need a new class of founders to build what comes next.
Instead of only “building what people want” and iterating their way to product-market fit, these founders start from the question of how we should live together. They build new institutions that set the standards for how entire industries operate. They combine a philosophical vision of the society they’re building toward with the technical ability to realize it.
We call them philosopher-builders.
Immanuel Kant gave the Enlightenment its motto: Sapere aude. Dare to know.
The AI age demands another.
Condere aude. Dare to found. 🫡
AI is overturning assumptions society has organized itself around for centuries. The models keep getting better, but no level of capability can tell us what kind of society we should make with them.
We need a new class of founders to build what comes next.
Instead of only “building what people want” and iterating their way to product-market fit, these founders start from the question of how we should live together. They build new institutions that set the standards for how entire industries operate. They combine a philosophical vision of the society they’re building toward with the technical ability to realize it.
We call them philosopher-builders.
Immanuel Kant gave the Enlightenment its motto: Sapere aude. Dare to know.
The AI age demands another.
Condere aude. Dare to found. 🫡
Open quoted post →
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life update: i joined @usv as an investor. i will be investing across the frontiers of crypto, ai, robotics, energy and biotech.
super excited to work with @fredwilson @nickgrossman @rebeccakaden @uninsightful and the rest of the team!
more soon...
super excited to work with @fredwilson @nickgrossman @rebeccakaden @uninsightful and the rest of the team!
more soon...
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Businesses are fundamentally bundles of risk, operationalized.
Statebook identifies the "platonic form of a hedge" and translating that into different concrete mechanisms - stocks, options, PMs, insurance to build a universal risk transfer layer.
@lzminsky is cooking 🧑🍳
Statebook identifies the "platonic form of a hedge" and translating that into different concrete mechanisms - stocks, options, PMs, insurance to build a universal risk transfer layer.
@lzminsky is cooking 🧑🍳
Lauris@lzminsky · Sep 10Introducing Statebook: Markets for All States of the World.
For the past few months, I’ve been exploring a simple market-design question:
What becomes possible if we start with the exposure someone needs, rather than the contract an exchange happens to list?
This question is becoming increasingly relevant as @HyperliquidX, @Kalshi, @Polymarket, and vertically specialized exchanges such as @Architect_Fi expand the universe of tradable underliers, and the boundaries between perpetuals, options, and event contracts begin to blur.
My answer: structured-product heaven.
The working paper and interactive research interface are below.
Thank you to @0xsmac, @0xfishylosopher, and Chris Saunders for reviewing and contributing to the initial draft.
statebook.app
Open quoted post →For the past few months, I’ve been exploring a simple market-design question:
What becomes possible if we start with the exposure someone needs, rather than the contract an exchange happens to list?
This question is becoming increasingly relevant as @HyperliquidX, @Kalshi, @Polymarket, and vertically specialized exchanges such as @Architect_Fi expand the universe of tradable underliers, and the boundaries between perpetuals, options, and event contracts begin to blur.
My answer: structured-product heaven.
The working paper and interactive research interface are below.
Thank you to @0xsmac, @0xfishylosopher, and Chris Saunders for reviewing and contributing to the initial draft.
statebook.app
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Been workshopping on compute markets as a thesis for the last few months. Sharing a couple of my perspectives on ideas like:
- How compute markets resemble power markets
- Who the structural long/shorts for compute are and how market structure evolves
- NVIDIA's role as the "central bank for compute"
- The 3-4 main products to build in the compute stack (physical settlement, index, derivatives exchange, financialization infra) and their pros/cons
- Compute markets vs. broader token markets
- The role of the "3 big elephants" in this market - NVIDIA, frontier labs, and Open Source models and game theory of compute providers.
- How compute markets resemble power markets
- Who the structural long/shorts for compute are and how market structure evolves
- NVIDIA's role as the "central bank for compute"
- The 3-4 main products to build in the compute stack (physical settlement, index, derivatives exchange, financialization infra) and their pros/cons
- Compute markets vs. broader token markets
- The role of the "3 big elephants" in this market - NVIDIA, frontier labs, and Open Source models and game theory of compute providers.
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Great read. When you think about it deeper the hesitation in underwriting residual value may be bc there's actually two different types of "depreciation" at play:
1. "Absolute depreciation" - how effective is a chip at generating tokens? Counterintuitively tokens efficiency per chip may actually increase over time, as new models become more efficient to serve than older ones. This variable is controlled by the labs that determine how efficiently a chip can run a model.
2. "Relative depreciation" - how does the chip perform relative to SOTA. This is largely controlled by NVIDIA - its up to them if they want to release Vera Rubin 6mos earlier or 6mos later. This likely also gives them confidence in releasing the 25% residual value support
1. "Absolute depreciation" - how effective is a chip at generating tokens? Counterintuitively tokens efficiency per chip may actually increase over time, as new models become more efficient to serve than older ones. This variable is controlled by the labs that determine how efficiently a chip can run a model.
2. "Relative depreciation" - how does the chip perform relative to SOTA. This is largely controlled by NVIDIA - its up to them if they want to release Vera Rubin 6mos earlier or 6mos later. This likely also gives them confidence in releasing the 25% residual value support
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