3 ms·

IMO feels sorta like Simon Willison's definition of agents. "LLMs in a loop with a goal" feels super obvious, but not sure if I would have described it that way

IMO feels sorta like Simon Willison's definition of agents. "LLMs in a loop with a goal" feels super obvious, but not sure if I would have described it that way in hindsight

stavros 8mo ago
Maybe, but that's what I thought while reading the "what actually is async?" part of the post, so I don't think I got biased towards the answer by that point.
DonHopkins 8mo ago
One nuance that helps: “async” in the turn-based-telephone sense (you ask, it answers, you wait) is only one way agents can run. Another is many turns inside a single LLM call — multiple agents (or voices) iterating and communicating dozens or hundreds of times in one epoch, with no API round-trips between them. That’s “speed of light” vs “carrier pigeon”: no serialization across the boundary until you’re done. We wrote this up here: Speed of Light – MOOLLM (the README has the carrier-pigeon analogy and a 33-turn-in-one-call example). Speed of Light vs Carrier Pigeon: The fundamental architectural divide in AI agent systems. https://github.com/SimHacker/moollm/blob/main/designs/SPEED-OF-LIGHT-VS-CARRIER-PIGEON.md https://github.com/SimHacker/moollm/blob/main/designs/SPEED-... The Core Insight: There are two ways to coordinate multiple AI agents: Carrier Pigeon Where agents interact: between LLM calls Latency: 500 ms+ per hop Precision: degrades each hop Cost: high (re-tokenize everything) Speed of Light Where agents interact: during one LLM call Latency: instant Precision: perfect Cost: low (one call) MCP = Carrier Pigeon Each tool call: stop generation → wait for external response → start a new completion N tool calls ⇒ N round-trips MOOLLM Skills and agents can run at the Speed of Light. Once loaded into context, skills iterate, recurse, compose, and simulate multiple agents — all within a single generation. No stopping. No serialization.
- canadiantim 8mo ago
  Thanks for sharing, that distinction is very helpful.

IMO feels sorta like Simon Willison's definition of agents. "LLMs in a loop with a goal" feels super obvious, but not sure if I would have described it that way in hindsight

stavros 8mo ago

Maybe, but that's what I thought while reading the "what actually is async?" part of the post, so I don't think I got biased towards the answer by that point.

DonHopkins 8mo ago

One nuance that helps: “async” in the turn-based-telephone sense (you ask, it answers, you wait) is only one way agents can run. Another is many turns inside a single LLM call — multiple agents (or voices) iterating and communicating dozens or hundreds of times in one epoch, with no API round-trips between them. That’s “speed of light” vs “carrier pigeon”: no serialization across the boundary until you’re done. We wrote this up here: Speed of Light – MOOLLM (the README has the carrier-pigeon analogy and a 33-turn-in-one-call example). Speed of Light vs Carrier Pigeon: The fundamental architectural divide in AI agent systems. https://github.com/SimHacker/moollm/blob/main/designs/SPEED-OF-LIGHT-VS-CARRIER-PIGEON.md https://github.com/SimHacker/moollm/blob/main/designs/SPEED-... The Core Insight: There are two ways to coordinate multiple AI agents: Carrier Pigeon Where agents interact: between LLM calls Latency: 500 ms+ per hop Precision: degrades each hop Cost: high (re-tokenize everything) Speed of Light Where agents interact: during one LLM call Latency: instant Precision: perfect Cost: low (one call) MCP = Carrier Pigeon Each tool call: stop generation → wait for external response → start a new completion N tool calls ⇒ N round-trips MOOLLM Skills and agents can run at the Speed of Light. Once loaded into context, skills iterate, recurse, compose, and simulate multiple agents — all within a single generation. No stopping. No serialization.

canadiantim 8mo ago
Thanks for sharing, that distinction is very helpful.