Agarwal: Sequoia met 20 AI SRE startups before backing Traversal
Anish Agarwal · ⚡️Traversal: Causal ML and Reinforcement Learning · Oct 5, 2025 · at 8:34
Anish Agarwal, co-founder of Traversal, describes pitching Sequoia Capital partner Bogomil Balkansky, who had already evaluated 20 AI SRE pitches.
0:00 / 0:16exact quote · 16.6s
▶ Watch the full episode on YouTube → 720p mp4 · rendered on demand · StarZero watermark
“Our first VC backer was Sequoia, and I think they had met, I think, like, I think like 20 VC, 20, ah, companies before this, but unbeknownst to us, and that was the first question, like Bogomol, who's a board member from there asked, like, I've heard this pitch 20 times before. Why on earth should we go with you?”
quote is from the automated transcript, cleaned for reading: filler sounds and stutters are removed, nothing is rephrased. names can be misheard (the analysis reads context, assessments check outside sources). how →
More from Anish Agarwal
Agarwal: No AI incident troubleshooting competitor genuinely works in production
“And I don't think we've seen any other company in our space having something actually work at production.”
Agarwal: AI coding assistants will cause uninterpretable outages and endless firefighting
“And so it's pretty clear to us that, you know, and we were starting to use it ourselves and sometimes we didn't understand what the code was doing, but you know, we shipped it. And so it's like, well, if this is clearly, this is going to happen a lot more. And…”
Agarwal: Incident troubleshooting requires adaptive search over LLM context dumping
“You cannot just Put all of it into context of an LLM and hope something great happens. You have to search the data sequentially and adaptively, right? And that's what these agentic systems are fundamentally about.”
Agarwal: LLMs are really bad at processing time series data
“Because most of the data you're looking at is like time series data. And these LLMs are really bad at processing time series data, right? And that's really where like good statistics comes in.”
Agarwal: Observability incumbents lack incentive to analyze competitor telemetry data
“The typically the way they work is, is they price based on the amount of data they're storing, right? And so, you know, they have very little incentive for company A To provide you any insight on data being stored on, on company, observability company B, right…”
Agarwal: Rigorous eval suites are core IP for leading AI startups
“The best AI companies will always have to be the edge of what the models can do, right? I think you always want to be threading the line. If everything works all the time, then you're not really pushing the limit and you're not innovating, right? So I think yo…”