
Co-founder/Partner @hanabicapital Prev Partner @IndexVentures, Infra Eng/PM@ Palantir + MemSQL
Santa Cruz, CA
Joined July 2009
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Bryan Offutt retweeted
It is very interesting that AI is quite bad at many things, but specifically good at many of the most dangerous things (hacking, code, bio, etc).
Bryan Offutt retweeted
Excited to announce Agent Mode.
1/ Right now, agents are struggling to use websites on the internet. As a result, personal agents take too long to reply, and don’t get the information they need.
Bryan Offutt retweeted
At some point you need to stop playing covers and start playing your own songs.
You cannot execute someone else's strategy.
Nobody thinks about your business nearly as much as you do. No one can obsess over the problem more than you. You have more data than all of them combined. You're the one who has to execute on all the space in between.
Every decision downstream of a framework you don't actually believe in gets wobbly. You just accumulate drift.
When things don't go perfectly right (and at a startup, they won't), you'll start second-guessing the whole thing and think you probably should have just done it your way. So yeah, just do that from the start.
Bryan Offutt retweeted
We did it again. Temporal just raised a $550M Series E round at a $12.55B valuation.
Learn more about how we got here: temporal.io/blog/temporal-ra…
Bryan Offutt retweeted
Contrast the present hysteria with Los Alamos.
The Manhattan Project scientists thought the first nuclear explosion could ignite the atmosphere and end humanity.
They did the math. They determined it wouldn’t. And they proceeded.
Because they weren’t fighting a thought experiment. They were fighting the Nazis.
Effective Altruism inverts this. Multiply a sufficiently horrifying hypothetical future by enough hypothetical future humans and suddenly speculation acquires the moral authority of fact.
That’s not empiricism. It’s secular eschatology.
Take risks seriously. Do the work. Engineer against them.
But don’t confuse the ability to imagine the apocalypse with the authority to rule the present.
Bryan Offutt retweeted
I’m more and more of the opinion that the DoE should nationalize the frontier labs so they can safely work on all the scary, world ending shit with the right controls.
And let the rest of us get on with building useful AI that, you know, automates menial shit and cures people.
Bryan Offutt retweeted
The world needs far more software than it can build. Cognition exists to change that.
We’ve just raised over $2B at a $48B valuation, led by a16z, Accel, Founders Fund, General Catalyst, and Avenir.
Since our round in May, run-rate revenue has grown from $492 M to almost $900 M.
Bryan Offutt retweeted
Good game, @ClickHouseDB.
We’ll leave the queries to you. We’ll take the three points.
@ceo_clickhouse
Bryan Offutt retweeted
Meet the superintelligent AI SRE that starts investigating before you do. Traversal Workers are now generally available.
Bryan Offutt retweeted
I’ll be continuing to do much of the same work at Hanabi, backing technical founders relentlessly pushing the frontier across AI, infrastructure, energy, and hardtech. Excited to do it with some new friends in @mavolpi and @BryanOffutt, and a very old friend in @ishanit5 :)
Bryan Offutt retweeted
we're hosting a GTM happy hour in our brand new NYC office next week!
bringing together top operators from AI companies like Ramp, Rogo, Profound, Decagon, and Cognition
comment or shoot me a DM for an invite
Bryan Offutt retweeted
Use Grok Voice models in LiveKit to build useful voice agents with full support for ZDR
We built a patient intake agent with @spacexai that runs end to end on Grok voice models.
Grok STT → Grok 4.3 → Grok TTS, cascaded through LiveKit Inference. Three model strings in one AgentSession. No separate API key, no separate billing, ZDR on every hop.
Talk to it: xai.livekit.space
Bryan Offutt retweeted
Replying to @ivanburazin
Tech consistently forgets that most things are not technology problems, they are human psychology, habit, and risk tolerance problems. They take time.
This makes tech often right about the thesis, and wrong about the timeframe over which it’s realized.
Bryan Offutt retweeted
OR chooses Modal, maybe you can too. modal.jobs
Bryan Offutt retweeted
You’d expect better frontier models to narrow the gap between purpose-built AI systems and DIY approaches. We found the opposite.
Today we’re sharing results from Traversal-Bench, comparing Traversal against frontier models with direct access to production systems across 25 real Sev 1–3 incidents at a large financial-services enterprise.
One finding stood out: Traversal captured roughly 3× more improvement from the same period of model progress.
Full results: traversal.com/blog/the-model…
More on the findings in the comments.
Bryan Offutt retweeted
This was our strongest quarter yet at @traversal_ai !
When one customer experienced Traversal for the first time, they called it the “Claude Code moment for SRE.” Traversal spread organically across their team, unlocking use cases faster than we could sell them. They expanded to more users and use cases within months of going live.
The results followed:
– ARR has grown 8× in the last six months
– Monthly active users up ~14× since January
– Customers ran 71,400+ investigations last quarter, supporting roughly 2,500+ engineers
It all traces back to one early decision: build Traversal around incident root cause analysis for complex enterprises – the hardest reasoning problem in software reliability.
Petabytes of telemetry, almost no labeled MELT data, APIs never built for agents reasoning across thousands of hypotheses in parallel. Solving RCA forced us to rethink both the data and AI architecture.
Customers first trusted Traversal with Incident RCA. Then it spread.
More than half of usage now comes from workflows we never built for – CMDB validation, release validation, data ops, infra resource management, cost optimization.
In one customer-built workflow, an engineer used Traversal to find redundant logging and uncovered $1M+/year in potential observability savings.
This reinforced something we’ve long believed: once AI deeply understands a production system, troubleshooting is just one application among many. The same reasoning foundation extends much further.
Grateful to our customers for pushing Traversal into new corners of their organizations, and to the team for pushing the technology forward.
Bryan Offutt retweeted
"Top AI researchers don't just join companies for compensation.
They want to work on ambitious visions they believe can change the world, and they care deeply about the real-world impact of the technology they're building.
For the best researchers, mission and meaning are often as important as the technical challenge." @joon_s_pk
What does no one seeing about recruiting researchers that everyone should see @LiamFedus @BrendanFoody @mikeyk @GarrettLord
Three weeks ago, I was sitting in the drawing room of the holiday rental my family always gets in July in Frinton-on-Sea (St Tropez of the UK).
It was midnight and as my grandparents were snoring loudly next to me; my phone suddenly buzzed. It was legendary investor, @shardul_shah @IndexVentures.
As much as I love Shardul, it is rare for him to send me a deal and so when he does, I pay attention.
Shardul was sharing @simile_ai with me, suggesting I meet @joon_s_pk. He spoke of all the companies he has backed, their growth being unparalleled. Given the man did Wiz, that really excited me!
I asked for the intro, and 60 mins later, at 1 AM UK time, I was on a call with Joon. Straight away, it was clear he was one of the most unique talents I had met; an ability to be world-class in two seemingly opposing skills: creativity and scientific rigour. The man was a painter before becoming world class AI mind! Wow.
I committed to invest on the call. Why? Joon is obviously insanely special. Second, I care deeply about upside. If this works, what could this be? If this works, it will change marketing forever. It will change stock markets forever. It will change human decision-making in general. Insane.
I had to be a part of it and so I gave Joon a boatload of cash and asked if I could summarise the notes from our conversation below. (Links in comments)
Huge thanks to @BennettSiegel @ninaachadjian @kevinhartz @BryanOffutt @karpathy for amazing thoughts, questions and feedback here.
1. The Question to Ask When Assessing Talent
The best way to evaluate talent is to look for consistent performance across multiple stages of a career, not impressive titles. Ask one question: Were they the common denominator behind every success? Exceptional operators repeatedly create great outcomes across different roles, demonstrating rare ownership and adaptability.
-- @kevinhartz you are one of the single best talent spotters in tech. What is the single biggest commonality in the best founders you have worked with?
2. The Sign of Truly Great Talent
Exceptional talent combines traits that rarely coexist. While most people have correlated strengths, world-class builders embrace cognitive tension. They are short-term paranoid but long-term optimistic—obsessing over daily execution while maintaining unwavering conviction in the bigger picture.
-- @dannyrimer you also have an immense love of art. How has art impacted your view on company building and entrepreneurship?
3. People Will Pay $100 Million for a Single Simulation
AI will enable simulations so valuable that companies will spend tens of millions on a single run. A simulation may cost $20 million in compute, but if it prevents a $500 million product failure, paying $100 million becomes an extraordinary bargain.
-- @GavinSBaker does this align to your views on specialised intelligence?
4. Why Simulation Requires Modeling Human Bias, Not Perfect Logic
Frontier labs are racing to build the “CPU of intelligence” optimized for perfect reasoning. The bigger commercial opportunity may be the “GPU of intelligence”: models that replicate human judgment, bias, and imperfect decision-making to simulate complex real-world markets at scale.
-- @ml_angelopoulos how does the role of evaluations change in this world?





























