ceo @pipeshiftai | yc s24 | forbes 30u30

San Francisco, CA
Joined August 2026
my indian dad just asked me why is it not 5T 😭
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qwen3-tts on one H100 at @pipeshiftai 28.4ms p95 first audio at 20 req/s next best was 54.3ms at 40 req/s every other engine broke while we held 33.7ms 0 of 41,337 requests failed launching our ultra low latency inference cloud for voice agents soon kudos to @FerraoEnrique, @pranavreddyg and the entire engg team!
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nvidia is the boogeyman in the compute market. everyone is throwing shitty prices to make compute unaffordable and you confront them over it and they straight up lie about “you know nvidia is doing this and that…..” then i call up people within the nvidia team and none of that bs is true.
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love seeing @PipeshiftAI customers crushing it!
Did not expect to be the top app on iOS for India at the peak of sale season.
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One of the best AI teams in India!
Oolka will exceed 2 trillion monthly input token consumption this month. We see this getting north of 50 trillion monthly runrate by 2027. Don’t write off India AI story yet.
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q: how to witness a lifetime worth of bullsh*t? a: set up an indian legal entity. the infrastructure is not built to support growth and no one cares enough to solve it cause at the end they get votes for religious polarization.
The smartest Indians continue to come to build in the US for the simple reason that the economic incentives are far far better. Perplexity ($20B), Skild ($14B+), Baseten ($13B), Together ($8B), Glean ($8B), Modal ($5B), Rubrik ($25B), Harness ($5B), Blacksmith, Parallel, Greptile, CodeRabbit, Composio, Distyl ($2B), Resolve, Luma, Cartesia, Wispr, dMatrix, Arize and many more - all started by at least one Indian-born founder. The US is a far easier to raise capital in with far less dilution. Most Indian companies are switching where they're domiciled to get access to the US capital markets. Every single Indian venture firm is trying very hard to invest in the US or risk not participating in the AI race (ironically, the management fees of venture firms are so high in India relatively that this is the one group that net of carry actually has incentive to be in India because they take home well north of a living wage whether or not funds perform do) While Zomato ($35B now, $8B at IPO) might be the biggest outcome in Indian venture, Cursor ($60B), Reflection (potentially $20B+), World Labs ($8B), OpenRouter ($8B), HuggingFace ($12B) and of course the $1T+ big labs quickly make those outcomes seem small and happen on a much smaller time scale, with much higher IRR. Engineers at these startups regularly get paid $1M/yr, and make $10M+ on exit. Even in BigTech, it is trivial to pull up levels fyi and see that if you're L6/L7+ with ~10 years of experience, you're making $1M/yr there too. And of course, we all know the slew of Indian CEOs of companies here, not to mention a huge bench of lesser known executives across the board in public and private companies. I say all this because every time there is a slight immigration hiccup in the US, I hear the online pleas to "build in India", I struggle to understand why most engineers, academics or founders would do that net of desire to be close to family, failure to obtain visa and devout patriotism. This is not a superiority thing or a US v India thing. The economic incentives at least for technologists to being in the US outweigh India by at least an order of magnitude.
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screw msft. we make too our chips at @PipeshiftAI
Nvidia - making chips Google - making chips Meta - making chips Microsoft - making chips Amazon - making chips OpenAI - making chips Anthropic - making chips Alibaba - making chips Everyone’s pushing to vertically integrate chip design to reduce reliance on Nvidia. Customers are working to become competitors. Most aren’t immediate threats yet, but they’re all moving quick Only makes sense for Jensen to compete back
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OpenAI had to create the market and fail at things so Anthropic didn’t. They struggled to get traction and capital initially, making the enterprise GTM a no brainer cause that’s what you do with less capital. It’s funny how all this is just 3 years 😂
focus, focus and more focus
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fair point: all roads lead to inference if you're engineers building in infra. however, with inference being such a large market with so many options, specializing towards a workload and offering a stack that improves with more telemetry, allows to build long term stickiness with an amazing nps within customers. the entire stack gets tuned to your workload patterns (input, output, cache hits, etc) and over a period of time, re-doing the cycle with another provider is like switching your database. specialize: codings agents and voice agents need completely different inference infrastructure, not just kernels. baseten and fireworks have spent so much capital building infra for cursor, that they have made everyone believe that the only way to tune performance is custom kernels.
Inference is the second way to raise a massive round right now. After the labs, you can still justify massive rounds by pointing at data centers and compute, which means more inference companies keep getting funded even as the underlying product stays extremely easy to switch away from. On the flip side, many neolabs are also renting out their own compute, adding yet another source of supply into the same market. Companies that tried to verticalize around batch workloads and post-training are now pivoting back to "pure inference" and joining the same undercutting cycle. The result is a permanent reverse auction: providers undercut each other over and over: half off Fireworks, half off Baseten, 10% cheaper GLM or Kimi—and every new entrant or neolab offering capacity just accelerates the cheaper pricing At the same time, app companies have so much choice right now that they can bake off and compete prices down extremely hard. They move millions of run-rate spend overnight whenever a meaningfully cheaper option appears, because the technical switching cost is essentially "one line of code". That combination: easy capital, extra compute from neolabs, low stickiness, and continuous price pressure makes inference one of the less defensible layers in the stack even as it continues to attract large valuations. However, if you are a smart team of infra people, it is the easiest way to raise 100M seed after a neolab Researchers: neolab <> engineers: inference
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AI has gotten so great! our engineering team hasn’t grown at all in the last 12 months. just a team of cracked engineers with multiple claude subs and our in-house GLM fine tune. in this period, we have gone from zero to millions in revenue. we are serving 100x the requests as compared to our direct competitors. key customers have also grown inference volumes by 3-5x within a quarter.
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someone should regulate the closed model companies. they are literally planning false flags. definitive predictions are made when you are the cause.
Executives at OpenAI, Anthropic and other AI companies are reportedly preparing for a public and political backlash after a catastrophic AI event, possibly as early as 2027 (via Axios). Axios reports that many industry insiders expect a major incident within the next 6–12 months, most likely a cyberattack disrupting banking, internet access, power or water. OpenAI confirms it runs preparedness exercises, but says: "These scenarios are not treated as inevitable, but are meant to help us prepare for a variety of circumstances." Anthropic declined to comment.
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AI inference could grow from $160B to $350B next year, overtaking databases as the largest market in software. For software companies, that could mean margins closer to 30–50% than the usual 72%.
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exactly what not using @PipeshiftAI for voice inference looks like.
.@WisprFlow what is breaking exactly?
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if this is who I’m hearing it is, it’s just so messed up. India went from being a click farm for DAU/MAU to students used as rlhf farm. middle class parents paying (sometimes even taking a loan) to get their child a degree and the kids are made to do rlhf (for basically free cause the parents paid for the course).
Fastest company ever to $1b annualized revenue Nope it’s not Higgsfield or Cursor or Cognition. Met a data company yesterday that did 0 revenue in November 2025 and 80m “in month revenue” in September 2026. They will hit $1b annualized from 11 months of being started. They are still under the radar so I can’t share who they are. Hopefully soon, with their permission. I don’t make the rules.
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All of them do it cause investors wanna look at the artificial analysis toks/sec numbers. No one runs evals against fp16 weights before rolling out a term sheet.
I'm going to start posting all the open soruce infra providers that quantize their models, which model and when. Shit's getting so annoying. Every single one of them does it, and all of them deny it when it happens. I can't tell if we're the only company with brains, or everyone else complains privately
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