[ramoz]

I can import my entire codebase to Gemini and get more than a nuanced similarity score in terms of agent guidance.

What’s the differentiator or plan for arbitrary query matching?

Latency? If you think about it - not really a huge issue. Spend 20s-1M mapping an entire plan with Gemini for a feature.

Pass that to Claude Code.

At this point you want non-disruptive context moving forward and presumably any new findings would only be redundant with what is in long context already.

Agentic discovery is fairly powerful even without any augmentations. I think Claude Code devs abandoned early embedding architectures.

[eborgnia]

Hey, these are really interesting points. The question of agentic discovery vs. one-shot retrieval is really dependent on the type of product.

For Cline or Claude Code where there's a dev in the loop, it makes sense to spend more money on Gemeni ranking or more latency on agentic discovery. Prompt-to-app companies (like Lovable) have a flood of impatient non-technical users coming in, so latency and cost become a big consideration.

That's when using a more traditional retrieval approach can be relevant. Our retrieval models are meant to work really well with non-technical queries on these vibe-coded codebases. They are more of a supplement to the agentic discovery approaches, and we're still figuring out how to integrate them in a sensible way.