Not to be all captain hindsight, but I was puzzled as I was skimming the post, as this seemed obvious to me:
Something is async when it takes longer than you're willing to wait without going off to do something else.
Something is async when it takes longer than you're willing to wait without going off to do something else.
"takes longer than you're willing to wait" describes the UX, not the architecture. the engineering question is: does the system actually free up the caller's compute/context to do other work, or is it just hiding a spinner?
nost agent frameworks i've worked with are the latter - the orchestrator is still holding the full conversation context in memory, burning tokens on keep-alive, and can't actually multiplex. real async means the agent's state gets serialized, the caller reclaims its resources, and resumption happens via event - same as the difference between setTimeout with a polling loop vs. actual async/await with an event loop.
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-...
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