Rather than asking an agent to internalize its algorithm, you should teach it an API and then ask it to design an algorithm which you can run that in user space. There are very few situations where I think it makes sense (for cost or accuracy) for an LLM to internalize its algorithm. It's like asking asking an engineer to step through a function in their head instead of just running it.
So in concrete terms I'm imagining:
1. Create a prompt that gives the complete API specification and some general guidance about what role the agent will have.
2. In that prompt ask it to write a function that can be concisely used by the agent, written to be consumed from the agent and with the agent's perspective. The body of that function translates the agent-oriented function definition to an API call.
3. Now the agent can use these modified versions of the API that expose only what's really important from its perspective.
4. But there's no reason APIs and functions have to map 1:1. You can wrap multiple APIs in one function, or break things up however made most sense.
5. Now the API-consuming agent is just writing library routines for other agents, and creating a custom environment for those agents.
6. This is all really starting to look like a team of programmers building a platform.
7. You could design the whole thing top-down as well, speculating then creating the functions the agents will likely want, and using whatever capabilities you have to implement those functions. The API calls are just an available set of functionality.
And really you could have multiple APIs being used in one function call, and any number of ways to rephrase the raw capabilities as more targeted and specific capabilities.
4. Now the
Also, since you're implicitly questioning OP's claim to have been saying this all along, here's a comment from September 2023 where they first said the same quote and said they'd been building agents for 3 months by that point [1]. That's close enough to 2 years in my book.
[0] https://hn.algolia.com/?dateEnd=1685491200&dateRange=custom&...