# KARABASAN

- **Event:** [Built with Opus 4.7: a Claude Code hackathon](https://cerebralvalley.ai/e/built-with-4-7-hackathon)
- **When:** Apr 21 at 12:00 PM – Apr 27 at 2:00 AM (EDT)
- **Where:** Online
- **Team:** [Yigit Polat](https://cerebralvalley.ai/u/dyigitpolat)
- **GitHub:** https://github.com/dyigitpolat/compilagent_triton
- **Demo video:** http://youtube.com/watch?v=GYY5VyMMroY
- **Gallery:** https://cerebralvalley.ai/e/built-with-4-7-hackathon/hackathon/gallery
- **Page:** https://cerebralvalley.ai/e/built-with-4-7-hackathon/hackathon/gallery/109

Compil'agent reframes compilation as an agentic problem. It's a drop-in replacement for `torch.compile` and `@triton.jit`, and the main mechanisms are backend-agnostic. In just three lines of code, users get a faster, correctness-validated callable.

What's distinctive is where the agent searches. Conventional autotuners sweep user-facing knobs like BLOCK_SIZE or num_warps. Compilagent goes a layer deeper, into the compiler's own decisions: Triton's MLIR pass pipeline, Inductor's scheduler, FX graph rewrites, or even lowering registry overrides. 

The agent reads the actual IR, forms hypotheses tied to specific evidence in those artifacts, proposes multi-knob candidate batches, benchmarks each, and reflects across the batch before the next round. 

The interesting bet Compil'agent makes isn't just that LLMs can do compiler search. This points to a broader shift in how compilers are built. The field has long shipped fixed pipelines tuned by hand-written heuristics that must work passably across every workload. Compil'agent treats the pipeline as a search space and the compiler's own decisions as a tool surface, and in the future, enables the agent to become the compiler itself.

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Markdown version of https://cerebralvalley.ai/e/built-with-4-7-hackathon/hackathon/gallery/109. Site index for agents: https://cerebralvalley.ai/llms.txt · full text: https://cerebralvalley.ai/llms-full.txt