Traversal

topic on 2 shows · 8 statements across 2 episodes · said 17 times in 2 episodes since 2025

Latent Space 16 the a16z Podcast 1

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2025 17 mentions in 2 episodes 9 per episode

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8 statements about Traversal, every show

a16z Assertion Not checkable as stated
Sarah Wang: AI SRE startups are beating legacy platforms like Datadog
“That's why we're starting to see even agents built on top of classic, iconic platforms like Datadog Lose to some of the new AISRE companies, like a resolve or a traversal.”
Sarah Wang Dec 26, 2025 ▶ 12:03 AI Is Coming For These 3 Industries In 2026 (a16z Big Ideas)
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
LATENT SPACE 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
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
Dwivedi: LLMs handle semantics while statistics must handle time series
“The agent is not good at looking at time series data, so that's, that is what statistics needs to take care of. But statistics doesn't understand what is the relationship between latency and memory usage and disk utilization. So that is the LLM part.”
Raaz Dwivedi Oct 5, 2025 ▶ 19:45 ⚡️Traversal: Causal ML and Reinforcement Learning
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
Dwivedi: Claude is superior at agentic tool calling and error unstacking
“For some of the agentic part of the stack, we are shifting towards Anthropic because they're agentic and the tool calling, especially the unstacking part, you know, when you go down the wrong path and you build context that forces you to keep going down the wr…”
Raaz Dwivedi Oct 5, 2025 ▶ 33:36 ⚡️Traversal: Causal ML and Reinforcement Learning
LATENT SPACE Prediction Not checkable as stated
Dwivedi: AI self-healing for complex incidents is 6-12 months away
“Now for, then there is this level of 30 to 40% of the incidents or issues where you need to involve you know, a senior engineer for sanity checking. I think that healing will appear in, I don't know, six months to a year that will be comfortably, the technolog…”
Raaz Dwivedi Oct 5, 2025 ▶ 39:34 ⚡️Traversal: Causal ML and Reinforcement Learning

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