We're using Github Copilot chat (the interface hosted at https://github.com/copilot) for this purpose today but I'm curious how one would build such a thing ourselves.
Launch HN: Relace (YC W23) – Models for fast and reliable codegen
51–54 of 54 posts
Re: Launch HN: Relace (YC W23) – Models for fast and reliable codegen
#52Very interested to see what the next steps are to evolve the "retrieval" model - I strongly believe that this is where we'll see the next stepwise improvement in coding models. Just thinking about how a human engineer approaches a problem. You don't just ingest entire relevant source files into your head's "context" -- well, maybe if your code is broken into very granular files, but often files contain a lot of irrel…
I have a different pov on retrieval. It's a hard problem to solve in a generalizable format with embeddings. I believe this can be solved at a model level where its used to fix an issue. With the model providers (oai, anthropic) going full stack, there is a possibility they solve it at reinforcement learning level. Eg: when you teach a model to solve issues in a codebase, the first step is literally getting the right…
> Boris from the Claude Code team explains why they ditched RAG for agentic discovery. > "It outperformed everything. By a lot"
Re: Launch HN: Relace (YC W23) – Models for fast and reliable codegen
#53Your message wasn't delivered to support@relace.ai because the address couldn't be found, or is unable to receive mail.
btw, I'm interested in trying out relace for my AI app generator tool: http://dyad.sh/
Re: Launch HN: Relace (YC W23) – Models for fast and reliable codegen
#54Earlier quoted context omitted.
I have a different pov on retrieval. It's a hard problem to solve in a generalizable format with embeddings. I believe this can be solved at a model level where its used to fix an issue. With the model providers (oai, anthropic) going full stack, there is a possibility they solve it at reinforcement learning level. Eg: when you teach a model to solve issues in a codebase, the first step is literally getting the right…
Relevant interview extract from the Claude Code team: https://x.com/pashmerepat/status/1926717705660375463 > Boris from the Claude Code team explains why they ditched RAG for agentic discovery. > "It outperformed everything. By a lot"