Daniel Chen
497 posts
Daniel Chen
@dychen3
Something new. Prev partner at @Sequoia. Started @PeopleGlassApp. @a16z @Caltech CS. Crypto and AGI maxi.
San Francisco, CA Katılım Aralık 2014
486 Takip Edilen3.5K Takipçiler
Daniel Chen retweetledi
meta: my chat with Claude got too long while drafting this critique of the RLM paper. Claude couldn't fit the full conversation in context. so it grepped the local transcript file and pulled in relevant sections. context as external variable, examined and retrieved programmatically... wait, my Claude is already doing RLM?
the paper (@a1zhang, @lateinteraction). the core problem is real: models need clean separation between the context they're reasoning over and the intermediate results of exploring that context. tool outputs and sub-call results shouldn't pollute the window you're thinking in. context rot from accumulated junk is a genuine failure mode.
but this divide-and-conquer is already happening at the harness level and useful patterns are being RLed into models. plan mode → external checklist → Ralph Wiggum loops working through tasks one at a time with fresh context. subagents returning distilled results so junk never hits the parent window. context-driven file exploration (check length, grep structure, selectively read)...
do the above well and each sub-task gets a focused window with mostly relevant context. this is where RLM's recursive approach actually costs you — every sub-call is a fresh prefill with no KV cache sharing, plus scaffolding overhead. when context is mostly relevant and fits in window, a warm cache with full cross-context attention wins outright.
the training contribution is clean RL env design: the model can't read long snippets from the prompt, forcing it to learn selective exploration and recursive decomposition. but existing coding tools already impose the same constraint — Claude Code's read tool rejects files over ~25k tokens. models are already learning context decomposition because their harness tooling forces it when being RLed.
for frontier models, the path forward is better divide-and-conquer, better tool use for external context — transcripts, persisted state files, disk artifacts — and better RL for learning when to decompose. not a new paradigm. All these are already underway. some RLM patterns are already there, as the opening makes clear.
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Daniel Chen retweetledi
Few know what’s going on in el segundo
And we may look back on it as one of the most important things that happened in America this century
Jakob Diepenbrock@jakobdiepen
America is the greatest country in the world. But we need more founders working on real problems. If you are in the early stages of building something that matters, you have to be in El Segundo.🇺🇸 Apply to the Spring Cohort in bio. Deadline February 20th.
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Daniel Chen retweetledi
Daniel Chen retweetledi
I was at the @LayerZero_Core event today
It genuinely felt historic
A gigantic leap forward in blockchain technology
LayerZero@LayerZero_Core
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We got married!!!
Joey Krug@joeykrug
Super thrilled to be co-leading a round in our future life together with @emmarosepb … she said yes! I love how brilliant and fascinating to talk to she is, her ambition and grit and relentless competence at anything she does, the way she understands me better than anyone, and how there’s no one I’d rather be stuck in an airport with. So excited to start this next chapter in life with Emma, and for our many future adventures together. ❤️
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Daniel Chen retweetledi
The ticker is $LIT.
x.com/Lighter_xyz/st…
Lighter@Lighter_xyz
We are announcing the Lighter Infrastructure Token (LIT)! Lighter is building infrastructure for the future of finance and the native token is key to aligning incentives. In this thread, we will describe the structure of the token, broader vision, and roadmap of use cases.
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Daniel Chen retweetledi
We are announcing the Lighter Infrastructure Token (LIT)! Lighter is building infrastructure for the future of finance and the native token is key to aligning incentives. In this thread, we will describe the structure of the token, broader vision, and roadmap of use cases.
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Daniel Chen retweetledi
We’ve raised 17 million led by @PanteraCapital, with participation from @Sequoia and others.
Fin enables users and businesses to move millions of dollars instantly - whether to other Fin users, directly into bank accounts, or across crypto rails.
If banks and payment products could be rebuilt from the ground up today, they would look like Fin.
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Request for startup: Prediction markets for friend groups
Bet like complete degenerates on all the people you mutually know
Will Alex get divorced in 2025?
Will Sarah have more than 4 drinks at the holiday party?
Over/under 6.5 likes on John's next Instagram post
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Daniel Chen retweetledi
Founding Beacon with @nilamg has been the most intense but also fulfilling time of my life. In just a year, we’ve grown to a team of 30+ and acquired dozens of mission-critical software businesses that quietly power everyday life, helping them bring AI to real-world industries.
We are deeply thankful to the entrepreneurs who have entrusted us with their life’s work and our partners at General Catalyst, Lightspeed, D1 Capital, MSD & BDT, and Sator Grove, along with our angels and advisors.
This $250M Series B fundraise enables us to increase the scale of our ambitions to build a generational AI holding company.
We are hiring across many roles! Check out our careers page.
Beacon Software@beaconsoftwarex
Introducing Beacon: the AI holding company for Main Street. Today, we're announcing a $250M Series B led by @generalcatalyst, @lightspeedvp & D1 Capital to give mission-critical software & services businesses a permanent home that preserves their legacy & scales their ambition. businesswire.com/news/home/2025…
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Daniel Chen retweetledi
we first met w sequoia in May 22. They invested in Dec 23. @shaunmmaguire intro'd us to spacex (and pushed us hard to think bigger), @josephinekchen connected us to some of our first customers, @Alfred_Lin helped us reason through scaling problems ...
If you can meet w sequoia, do it. If you can partner with them, definitely do it. it might take some time.
they very much helped shape bridge
Sequoia Capital@sequoia
We're launching our latest venture and seed funds to partner with the next generation of outlier founders at the start of their journey. We seek founders who see possibilities where others see limits. Here's what's inspiring our Early team:
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Daniel Chen retweetledi
Working with @sequoia as our 1st investor was the best early decision we made in @privy_io's life.
Starting a company is brutal - but some investors bend reality in your favor so you get a toehold to change things!
@shaunmmaguire @josephinekchen definitely did this for us 🙇
Sequoia Capital@sequoia
We're launching our latest venture and seed funds to partner with the next generation of outlier founders at the start of their journey. We seek founders who see possibilities where others see limits. Here's what's inspiring our Early team:
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Today, Dynamic is joining Fireblocks.
A month after starting Dynamic, I had my first call with the @FireblocksHQ CEO, Michael Shaulov.
I left that call thinking, “I need to partner with him.”
Since the beginning, we’ve admired how Fireblocks built trust and scale across the industry. I can't understate how much I respect this team, and always have.
By joining Fireblocks, we’re combining our strengths.
Fireblocks is leading the way in digital asset security infrastructure. Dynamic is leading the way in giving developers the tools to build next generation financial experiences, on crypto rails, with speed and simplicity.
Together, we can serve everyone, from the two-person startup to the Fortune 500 company, with one complete crypto stack for every stage of growth.
For our customers, nothing changes. You’ll keep building with the same tools and people you know and trust, now with more power behind you: stronger security, faster delivery, and global support.
This moment feels something we've been building toward for years. It’s the next step toward our vision of making crypto work for everyone.
To our customers, community, and investors, thank you for placing your faith in us.
LFG and back to work!
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Daniel Chen retweetledi
Sequoia's Chief Product Officer, @jesskah, won't hire well-rounded people.
She looks for a "spikes" in 1 of 4 traits that predict success:
• EQ: One-on-one people skills
• IQ: Raw intellectual horsepower
• PQ: Ability to navigate politics/systems
• JQ: Judgment on decisions that matter
In this week's episode of The Library of Minds, we went deep on how this framework shaped her journey from Google PM to Polyvore CEO to Sequoia’s Chief Product Officer. Jess explains why velocity is the strongest early predictor of product-market fit, how choosing the wrong business model was her biggest mistake as a founder, and why she now believes AI will spark a new wave of consumer media.
00:00 Intro
1:00 Who is Jess Lee
02:50 The EQ / IQ / PQ / JQ framework
03:44 What early Google taught her
05:35 When ambition becomes a weakness
07:34 Customer discovery vs visionary intuition
09:31 Polyvore: from user → CEO
12:37 Imposter syndrome & finding authentic leadership
15:20 Picking the wrong market
18:24 Firing fast & setting high performance bars
20:12 Building cult-like community and emotional loyalty
22:13 Velocity vs delight in product
24:32 What she looks for in founders (turn-based velocity)
25:59 The business model wake-up call
27:27 Storytelling as a founding superpower
28:26 Hot take: consumer isn’t dead, it’s being reborn
31:50 AI-generated media, fanfic, and the next YouTube
Grateful to be working with her at @withdelphi !
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Daniel Chen retweetledi
In 2020, @mansourtarek_ and @luanalopeslara dazzled us at @sequoia with a bold vision: make prediction markets federally compliant and mainstream.
Today, @Kalshi is available in 140+ countries and is one of the fastest-growing companies in the world.
Congrats to Team Kalshi. Proud to be on this journey with you from Series A to Series D and beyond.
Let's go!
Tarek Mansour@mansourtarek_
Kalshi recently raised $300M+ at $5B from Sequoia, a16z, Paradigm and others. Since then, we've grown over 3x, hit $50B of annualized volume, and became the largest prediction market in the world. And today…Kalshi goes global. 140+ countries. 1 liquidity pool.
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Almost exactly 10 years ago, we were building an internal prediction market @a16z. @cdixon is a true OG. Congrats
Chris Dixon@cdixon
Today we are announcing that a16z is co-leading the Series D in @Kalshi, a regulated exchange for trading on prediction markets. Prediction markets are a modern implementation of a classic economic idea, one most clearly articulated by Friedrich Hayek. Hayek and the knowledge problem Hayek argued that no central planner could ever access the dispersed knowledge held by millions of people across an economy, a fundamental challenge that has come to be known as the “knowledge problem.” Much of this knowledge is tacit and unspoken, embedded in people’s experiences, circumstances, and preferences. Hayek wasn’t just pointing out the limits of central planning. He was offering a solution. In his 1945 essay The Use of Knowledge in Society, Hayek argued that the solution lies in looking outward, not inward: “We need decentralization,” as he put it. Markets, in Hayek’s view, are not just allocation mechanisms but information systems. Prices act as signals, compressing vast amounts of local knowledge into actionable information. Moreover, prices create incentives: they encourage people to make decisions and act in ways that drive information back into the system. This creates an iterative feedback loop, an engine that drives better performance. Today we might say that the answer to the knowledge problem is not to give central planners more sophisticated computers. The answer is that markets themselves are the computers. Prediction markets make this idea concrete, applying it to questions about the future and turning collective knowledge into prices that reflect probabilities. Why we’re investing in Kalshi This is why we’re excited about prediction markets, and why we’re investing in Kalshi. Kalshi is bringing prediction markets into the mainstream with a compliant, scalable platform for event contracts covering everything from elections and economics to sports and culture. It has already seen billions in trading volume and continues to grow quickly. Kalshi also plans deep crypto integrations, work we’re excited to collaborate on, and today announced they’re expanding globally to 140 countries. We’re not the only ones excited about the potential of prediction markets. For businesses and investors, event contracts can hedge risk, such as exposure to economic or policy changes. For policymakers and analysts, market prices offer real-time forecasts that can outperform polls and expert predictions. And for society at large, prediction markets create an open, transparent, and incentive-driven way to aggregate beliefs about the future. This is the right moment for prediction markets. As trust in established institutions reaches historic lows — at least according to the polls — we need new systems that can earn trust in different ways. We believe the answer lies in open, decentralized systems. DeFi provides an alternative to traditional finance, stablecoins to conventional payment providers, and prediction markets to expert forecasts. Where people once trusted banks or pundits, they can now trust protocols and markets. Hayek’s insight was that knowledge is too widely distributed for any one authority to possess. Instead, we need systems that harness the intelligence of the many. Kalshi puts this idea into action, transforming dispersed information into concrete, market-based forecasts. We’re excited to support their work as they bring prediction markets into the mainstream.
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