According to @DeepLearningAI, researchers introduced SWE-smith, a pipeline that automatically builds realistic training data to fine-tune software engineering agents, highlighting a tooling advance in AI agent development, source: DeepLearning.AI on X, Aug 20, 2025. The post states the system injects and validates bugs across 128 Python repositories using model-driven edits, procedural mutations, and pull-request reverts, source: DeepLearning.AI on X, Aug 20, 2025. The post further notes it "then uses agents" after bug creation and validation, with full details provided in the linked thread or materials, source: DeepLearning.AI on X, Aug 20, 2025. The post does not mention crypto assets, tokens, or financial metrics, so any market interpretation should rely on subsequent releases such as papers, code, or benchmarks from the same source, source: DeepLearning.AI on X, Aug 20, 2025.