adityamishra241

This is really cool. The attention to detail on the internal mechanics is impressive, especially the inspection tools you built. Looking forward to seeing where you take it!

This is a really fun use of cross-referencing datasets. Curious how you decided which Wikidata themes were worth including.

Interesting approach. The iterative refinement + verifiable constraints combination seems especially useful. Curious what kinds of tasks have worked best in practice.

Really interesting approach. I’m curious how much the verifier pass improves the output quality compared to just increasing the token vocabulary.

The local-first approach is interesting, especially for finance workflows. Being able to save a workflow and rerun it later without involving the LLM again is a nice touch. Curious to see how this evolves.

Nice approach. AST-level similarity seems much more useful than simple text matching.

Nice idea. This could make large agent-generated PRs much easier to review.

Really impressive speedups. Curious how much of the gain comes from the runtime optimizations vs the few-step distillation in real-world robotics workloads.

This is actually a nice idea. I especially like the “dump now, organize never” approach — feels much more useful than another notes app. A global hotkey would definitely make this even more convenient.

This is a really interesting middle ground between venvs and containers. How much overhead does gVisor add in practice for typical local development workloads?

How do you handle task distribution and prevent the benchmark from favoring models that are tuned specifically to these 534 questions?