Self-play for training software engineering agents
In a post published on December 23, 2025, Self-play SWE-RL alternates one agent between injecting and fixing bugs in real repositories, without human-labeled issues or tests.
Source: Self-play RL para injeção e correção de bugs (x.com). Text prepared with AI from this source.
What happened and what to do
A post dated December 23, 2025 presents Self-play SWE-RL (SSR) as a way to train a single language-model agent to alternate between injecting and fixing bugs in real repositories, without relying on issues or tests labeled by people. The post highlights the approach for teams exploring how to train coding agents without those labeled data.
A company could evaluate the idea through a controlled workflow in test repositories: generate buggy changes, attempt repairs, and assess repair quality with tests and engineering review. The implementation should isolate experiments from production environments and record results to compare agent versions.
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Wendelmaques can diagnose the opportunity, define safety and evaluation criteria, and propose a scoped implementation of the experiment workflow, including monitoring and operation.
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