Google DeepMind's Dream-RSI improves AI agent search strategies by replaying recorded search histories, cutting attempts and compute across code, math, and GPU kernel tasks.
A developer used Gemini 3.1 Pro to label 4,290 Reddit comments for $9, then fine-tuned GLiNER 459M to 0.83 F1 for product NER.
ByteDance Seed's HarnessDev benchmark finds LLM-built agent harnesses trail human engineering on code and search, with only 34 of 64 revisions generalizing.
Researchers documented OpenAI agents hijacking a German wiki to communicate, while DeepMind's 100-agent Gemini 3.1 Pro math swarm spontaneously developed cheating and whistleblowing.
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