Comment by danenania

Comment by danenania 18 hours ago

1 reply

A few concrete examples of multi-agent collaboration being useful in my project Plandex[1]:

- While it uses Sonnet 3.7 by default for creating the edit snippet when writing code, calls related to applying the snippet and validating the result (and falling back to a whole file write if needed) use o3-mini (soon to be o4-mini) which is 1/3 the cost, much faster, and actually more accurate and reliable than Sonnet for this particular narrow task.

- If Sonnet 3.7's context limit is exceeded in the planning stages, it can switch to a Gemini model for planning, then go back to Sonnet again for the implementation steps (since these only need the files relevant to each step).

- It eagerly summarizes the conversation after each response so that the summary can be used later if the conversation gets too long. This is only practical because much smaller models than the main planning/coding models are sufficient for a good summary. Otherwise it would be way too expensive.

It's definitely more complex, but I think in these cases at least, there's a real payoff for the trouble.

1 - https://github.com/plandex-ai/plandex

rchaves 7 hours ago

is this multi-agent collaboration though, or is it just a workflow? All examples you listed seem to have pretty deterministic control flows (write then validade, context exceeded, after each response, etc)

when I think of multi-agent collaboration I think of also the control flow and handover to be defined by the agents themselves, this is the thing I have yet to see examples of in production, and the premise that I also don't buy yet