EFFECTIVE HARNESSES FOR LONG-RUNNING AGENTS

Summary from the TLDR AI newsletter

Developers are increasingly requiring agents to take on complex tasks that require work that spans hours or even days. Getting agents to make consistent progress across multiple context windows remains an open problem. Agents need a way to bridge the gap between coding sessions as context windows are limited, and most complex projects can't be completed within a single window. This article proposes a two-fold solution, with an initializer agent setting up the environment on the first run, and a coding agent tasked with making incremental progress in every session while leaving artifacts for the next session. Code examples are provided.