Anish Agarwal

Co-Founder, Traversal · 1 appearance on the record.

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Anish Agarwal is a co-founder of Traversal. He develops causal machine learning and AI systems for incident troubleshooting and root cause analysis in large-scale enterprise environments.

7statements → 1claims → 0claims resolved → 3.57/5average certainty → 2.29/5average debate potential → ≈4.5/5argument clarity, estimated →

1 not checkable as stated how the 1 claim stands · each chip opens the sources

1 prediction · 1 opinion · 4 insights · 1 disclosure · every statement was checked. The prediction and assertions are the 1 claim: statements the public record can support or contradict. 0 are resolved, and 1 names no date, number or outcome precise enough to check. Everything else (opinions, insights, what ifs, disclosures) can never be settled by the record, so it carries no assessment.

The record, in short

What the tape says about how Anish argues and how the claims held up. Everything they said, and everything said about them, is in the tabs below.

How they sound: not measured why? →

We measure speaking style by listening to the audio itself, and a fair number needs at least 2,000 words from one person on tape we have measured. There is too little of Anish Agarwal on measured tape to publish a rate. This says nothing about how they speak.

What they said7 Episodes1

Everything Anish Agarwal said on Latent Space that made the record, most notable first. Filter by type, assessment or year in the ledger →

Opinion

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.”

Anish Agarwal Oct 5, 2025 ▶ 25:49 ⚡️Traversal: Causal ML and Reinforcement Learning

Prediction Not checkable as stated

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…”

Anish Agarwal Oct 5, 2025 ▶ 7:40 ⚡️Traversal: Causal ML and Reinforcement Learning

Insight

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.”

Anish Agarwal Oct 5, 2025 ▶ 7:07 ⚡️Traversal: Causal ML and Reinforcement Learning

Insight

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.”

Anish Agarwal Oct 5, 2025 ▶ 17:58 ⚡️Traversal: Causal ML and Reinforcement Learning

Insight

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…”

Anish Agarwal Oct 5, 2025 ▶ 23:15 ⚡️Traversal: Causal ML and Reinforcement Learning

Insight

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…”

Anish Agarwal Oct 5, 2025 ▶ 35:31 ⚡️Traversal: Causal ML and Reinforcement Learning

Disclosure

Agarwal: Sequoia met 20 AI SRE startups before backing Traversal

“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 pitc…”

Anish Agarwal Oct 5, 2025 ▶ 8:34 ⚡️Traversal: Causal ML and Reinforcement Learning

Appearances (1)

Episode	Date	Speaking time
⚡️Traversal: Causal ML and Reinforcement Learning	Oct 5, 2025	19m

Anish Agarwal

The record, in short

How they sound: not measured why? →

Appearances (1)

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