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AI Summary
- OpenAI continues scaling RL for reasoning, moving beyond offline learning with online interactions and sample-efficient human curation; wall-clock time limitations in training remain an engineering challenge
- GPT-5 era defined by supercritical learning where scaling compute yields non-linear capability improvements; model routing and hybrid architectures improve efficiency while maintaining reasoning capabilities
- Practical developer advice: prompt engineering remains critical even with advanced models; self-improving coding agents require proper tool use patterns and scaffolding to avoid fragility
