Hi HN! We built Fast Deep Coder, an AI system that codes at human-level accuracy but an order of magnitude faster. Try it: https://super.myninja.ai?select=deepcoder

How it works:

* Runs on Cerebras wafer-scale hardware, pushing ~2,000 tokens/sec through Qwen3 Coder 480B.

* Executes full plan→code→test→debug loops inside a secure cloud VM (with VS Code + dev tools), then ships commits/PRs directly to GitHub.

* Benchmarked on SWE-Bench: 69.6% accuracy—on par with frontier models, but much faster

What you can do today:

* Feature builds in unfamiliar repos

* Multi-file refactors & debugging

* Repo-aware reasoning with explainable steps

Read more here:

* https://www.ninjatech.ai/blog/fast-deep-coder

* https://www.cerebras.ai/press-release/ninjatech-ai-and-cereb...

We’d love feedback: if every coding experiment ran in its own VM at warp speed, what pain point in your stack would you tackle first?