everybody's talking about loops!! how can you instrument them with langchain?
1. token loop supported by a model (choose any model with langchain)
2. create_agent gives you the agent loop (model + tools + repeat until done)
3. deepagents gives you the self verification loop (agent loop + verify + repeat until satisfied)
4. deployments give you the meta loop (trigger agent runs in reaction to events that help improve a system)
5. i think the ??? loop is what we're trying to close with engine: run an agent over each trace and figure out what to tweak - prompts, tools, self verification, etc so that your meta loop is more effective per cycle.
[AINews] Loopcraft: The Art of Stacking Loops
@RichardSSutton has his “Bitter Lesson” for models. We now have the Salty Lesson for agents:
Don’t fix things yourself, as you have done historically.
Instead focus on systems that scale with more agents, like goals and orchestration.
More in today's op-ed: https://www.latent.space/p/ainews-loopcraft-the-art-of-stacking
