LLM agents

5 statements across 5 episodes · 1 bullish · 1 bearish · 5 people on the record · first statement Nov 28, 2024 by Erik Schluntz · across every show →

Everything said about LLM agents, oldest first

Nov 28, 2024 neutral
Prediction Not checkable as stated
Schluntz: Trust and Auditability Will Be LLM Agents' Biggest Bottleneck
“The biggest limiting thing will start to become like, do people trust the output of these agents? And like, how do you trust the output of an agent that did five hours of work for you and is coming back with something? And if you can't find some way to trust t…”
Erik Schluntz Nov 28, 2024 ▶ 1:10:24 The new Claude 3.5 Sonnet, Computer Use, and Building SOTA Agents — with Erik Schluntz, Anthropic
Aug 4, 2025
Insight
Vaidya: LLM agents get confused when exposed to over 20 tool actions
“More than like 20, 25 actions like just confuses the server. Like it's not able to kind of like figure out which tool to use. And same goes with like, if the schema of the tools are really complex, that also confuses the agent.”
Karan Vaidya Aug 4, 2025 ▶ 10:46 ⚡️Composio: 10,000+ tools that evolve for Agents — Karan Vaidya and Soham Ganatra
Dec 30, 2025 bearish
Prediction Didn’t hold up
Nair: LLM agents will hit $1T before robotics hits $10B
“It feels like LLM agents are going to be like a trillion dollar market before robotics is maybe even like a ten billion dollar market.”
Ashvin Nair Dec 30, 2025 ▶ 3:59 [State of RL/Reasoning] IMO/IOI Gold, OpenAI o3/GPT-5, and Cursor Composer — Ashvin Nair, Cursor
Mar 14, 2026 neutral
Insight
Colvin: Untrusted users prompting cloud AI is equivalent to letting them write code
“If you're running this kind of thing in the cloud and you, and you're gonna have ultimately untrusted people prompting the model, that is effectively the same as letting an untrusted person write the code.”
Samuel Colvin Mar 14, 2026 ▶ 27:15 ⚡️Monty: the ultrafast Python interpreter by Agents for Agents — Samuel Colvin, Pydantic
Apr 15, 2026 positive
Insight
Agent Environments Must Favor Model Preferences Over Internal System Architecture
“I mean, that was, I would say that was a big learning is just, you know, really be savvy and really careful thinking about what the model wants in terms of, you know, its environment and cater around that and really try so hard not to expose it to any complexi…”
Simon Last Apr 15, 2026 ▶ 51:22 Notion’s Sarah Sachs & Simon Last on Custom Agents, Evals, and the Future of Work
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