@emmacui

Cofounder and founding managing partner@longhashvc. DM open for founders. Personal opinion only, non financial advice. Sloan fellow @StanfordGSB. ex McKinsey

 Palo alto
longhash.vc/
Joined October 2010
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3/ On cost, their view is that token prices keep falling and usage rises to match, so total spend stays flat. Same story Reuters reported this week: OpenAI told investors price cuts on cheaper models boosted usage.
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6/ So I think the next control layer looks less like a seat license and more like a spend policy: per-agent budgets, approval thresholds, audit trails. Startups like AIsa, which Tether just backed, are already selling exactly that.
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7/ If you run finance or ops at a company with agents in production, how are you budgeting for them? I'd love to compare notes.
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1/ Everyone worries about runaway AI bills. A startup CFO I interviewed this weekend for my Stanford research on AI spend told me the budget is the easy part. Data is the hard part. 馃У
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2/ Their setup is simple: a monthly cap per employee for AI coding tools (about $200), with senior and key roles whitelisted with no cap. Many people just buy their own tools and never expense them.
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2/ Trust is what's holding AI back in critical systems. In her words: "They don't trust vibe coding, so that blocks AI deployment." Formal verification goes straight at that: the code ships with a proof that it does what it's supposed to.
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4/ She closed with a big question about AI-generated math humans can't fully follow: "is math cancer biology or is math chess?" In other words, is it valuable for its own sake, or a tool for something else?
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5/ When generating output gets cheap, the value moves to deciding what's worth verifying. Where does verification break down in your AI workflow?
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1/ Today I heard @CarinaLHong, founder of @axiommathai, speak at @DigEconLab on "AI That Can Prove It." Two ideas I keep thinking about 馃У
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The intellectual horsepower in this photo is crazy!
Alexandr Wang
@alexandr_wangOct 19
got the HRT gang back together!
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Anthropic just grew revenue about 45% in a single quarter, to $16.8B, and told investors it was profitable on an adjusted basis. The reported reaction: maybe the IPO is worth about $1.5T, not $2T. That's what it looks like to be priced on the curve, not the business.
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For founders building on these models, that's mostly good news, because your input costs keep dropping. The harder question is whether your own pricing holds when your competitors' costs drop too.
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Sources: Reuters, Axios and Breakingviews, all Oct 15. Curious where people land: is 45% QoQ at this scale a slowdown, or just the new normal?
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Sat in on Boris Cherny (@bcherny), creator of Claude Code, at Stanford today. What stuck was less the product and more how they built it. 馃У
Boris Cherny speaking at Stanford CS146S guest lecture

ALT Boris Cherny speaking at Stanford CS146S guest lecture

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His bet is that as coding gets democratised, domain experts, not only engineers, will ship a lot of the best software. That feels right from both the VC seat and the classroom.
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Watching Anthropic builders talk shop on campus hits different after years in early-stage VC. The tools change, but the builder instincts don't.
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