# Google uses AI agent swarms to find and fix silent TPU compiler bugs

> Original title: Banger paper from Google on using agent swarms to fix Google's TPU compiler.

- Source: Elvis Saravia
- Published: 2026-11-03T13:42:02.000Z
- Bad Influence: https://badinfluence.news/items/fwo45v67lhbrb5jwh8ac20ip2
- Original: https://x.com/omarsar0/status/2117613273189376072

## Summary

Google's team used swarms of AI agents to find and fix silent miscompilation bugs in its TPU compiler, resolving over 142 so far. The framework combines fuzzing on synthetic and production graphs with bisection that narrows failures to a single operation inside a fused kernel. Agent patches needed adversarial pre-filtering before human review, and the team reports reviewer effort grew faster than fix complexity.

## Post

Banger paper from Google on using agent swarms to fix Google's TPU compiler.

The team used swarms of AI agents to find and fix silent compiler bugs, and the framework has resolved over 142 of them so far.

They find silent miscompilations are the most dangerous. The compiler raises no error, but numbers drift, or buffers get corrupted, which can ruin a large training run or degrade live serving.

The team combines fuzzing on synthetic and real production graphs with checks that run alongside the existing autotuner. A bisection pipeline narrows a failure in a full workload down to one operation inside a fused kernel.

The agents generate stress tests, reproduce failures, and write fixes.

The team steered them away from easy crash bugs and toward silent data corruption, and 103 more findings are under review.

They also report that reviewer effort grew faster than the complexity of the fixes, and agent patches needed adversarial pre-filtering before humans looked at them.

https://arxiv.org/abs/2611.00624

Chat with Paper: https://academy.dair.ai/papers/xla-from-the-trenches-correctness-on-tpu-workloads-at-scale-2611.00624

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