31–39 of 39 posts
Your example is with Codex - OpenAI could implement this easily on their end right? Every prompt of yours was an API call and they have a log, they can easily re-create a quick history of what you did/asked for before?
But in the end, it doesn't really matter; it is public on GitHub, so anyone can use it.
Has been working for me for a couple of months already. So far human curation of context is the way to go.
Using the same approach for dev documentation storage: https://ctxlayer.dev/ Has been working for me for a couple of months already. So far human curation of context is the way to go.
Using the same approach for dev documentation storage: https://ctxlayer.dev/ Has been working for me for a couple of months already. So far human curation of context is the way to go.
How does the agent intelligently synthesize information across different files?
Earlier quoted context omitted.
How does the agent intelligently synthesize information across different files?
I found progressive discovery works very well. I have an INDEX.md file in every folder with a table describing what files are in that folder and what they do.
Have you noticed an relationship between recall and the number of files/memories?
Earlier quoted context omitted.
I found progressive discovery works very well. I have an INDEX.md file in every folder with a table describing what files are in that folder and what they do.
Ah, so you are effectively offloading the file exploration mechanism to the INDEX.md in the sub-directories rather than writing a complex prompt?