@arvin17x: The biggest takeaway today at Berkeley AI Summit 2026 came from Professor Jianfeng Gao's talk. A new paradigm for AI Modeling has emerged: - New training data: from harness to agentic modeli…
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The author summarized Professor Jianfeng Gao's presentation at the Berkeley AI Summit 2026, pointing out that the new AI modeling paradigm is based on Agentic Modeling and a new data flywheel, and emphasizing that Harness will become the key to application moats.
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Cached at: 08/03/26, 05:35 AM
Today’s biggest takeaway from the Berkeley AI Summit 2026 came from Professor Jianfeng Gao’s talk.
A new paradigm for AI modeling has already emerged:
- New training data: from harness to agentic modeling — playing the same role that internet-scale data played for pretrained models back then
- New scaling law: the AI industry is now generating massive amounts of AI Agent Harness trajectory data every single day
- New data flywheel: harness → better LLM → agents capable of more complex tasks → better/newer harness
In a sense, the moat for AI applications will emerge on the Harness side.
Whoever can turn the Agentic execution traces of the Harness into model training data and actually close the loop on model training will build a true application moat. I believe this will start happening in the second half of this year, and by next year it may become the new consensus.
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