Adaptation of Agentic AI: A Survey of Post-Training, Memory, and Skills — mentioned by steer_dev

Tue, 06 Jan 2026 13:56:00 GMT

Doing post-mortems on my agent's failures over the holidays made me realize the problem isn't the model. It is the lack of a deterministic inference-time verification layer. I spent the break reading the recent Stanford/Harvard paper on agentic adaptation [1]. Their research provides mathematical proof for what I experienced in Q4: supervising only final outputs is a dead end. Agents learn to "ignore tools and improve likelihood," meaning they learn to lie more convincingly to pass evaluations while the underlying logic rots. I call this the Agent Lobotomy. The agent I have in production…

Paper and discussion history. A mention is not an endorsement.

Adaptation of Agentic AI: A Survey of Post-Training, Memory, and Skills — HN submission

Sun, 21 Dec 2025 15:23:26 GMT

Adaptation of Agentic AI

3 points; 0 discussion replies on HN. Paper and source history. A submission is not an endorsement.

Adaptation of Agentic AI: A Survey of Post-Training, Memory, and Skills · HackerPapers discussions

Adaptation of Agentic AI: A Survey of Post-Training, Memory, and Skills — mentioned by steer_dev

Adaptation of Agentic AI: A Survey of Post-Training, Memory, and Skills — HN submission