MIT OpenCourseWare 6.S950 updates Lecture 5 Harness handout

MIT OpenCourseWare 6.S950 Agency with AI has updated the Lecture 5 The Harness handout. The handout uses a teaching Agent Baby Anigans—about 300 lines of Python, containing only two tools, search and read_lines, and running locally on Ollama—as an example to break down how the Harness works, and summarizes the Agent as LLM plus Harness. The handout also discusses the transparency trade-offs in observability, namely the problems brought about after vendors encapsulate context summaries and reasoning processes into encrypted APIs, and traces practices such as context management, mandatory interception, and least privilege back to system principles from 1965 to 1975. The handout also points out that there is no universal optimal solution: among 5 models, 4 have different best Harnesses on different benchmarks. Currently, the handout has been released with the course update, and there are no further developments yet.

AI-generated from public reports

1. Oct 21· 1 reports

   English translation is being prepared.

   Source:Shao Meng