JIT-Agent Generates Custom Harnesses for AI Tasks

Rohan Paul tweeted about a new paper that presents JIT-Agent as a way to improve agent performance. The method generates a custom harness for each task, determining the best configuration for memory, planning, actions, tools, and skills. Paul claims this allows a smaller model, specifically DeepSeek-V4-Flash combined with JIT-Agent, to outperform more powerful models that lack such adaptation. Paul points out that a smaller model with the right task-specific harness can beat a stronger model. The evidence consists of the tweet text and a screenshot of the arXiv paper abstract. No other sources in the packet corroborate the results mentioned.