Tag
This paper investigates what makes interaction trajectories effective for training terminal-based AI agents, introducing the Terminal-Lego pipeline and revealing a pedagogical paradox where weaker agents can produce better training data. It finds that environment-grounded supervision, rather than teacher performance, is key for student generalization.
OpenHands released an open-source software agent SDK inspired by Claude's dynamic workflows, enabling developers to build agents for code tasks such as test coverage improvement.
A new paper formalizes skill optimization for agents by treating markdown skill files as trainable parameters, using bounded edits validated against holdout sets. The approach transfers well between models and improves performance on procedural benchmarks.
A tweet points out that due to years of contributions from the open-source community to circumvention software, the relevant protocols and implementations have been internalized by large models; now you can use a domestic code agent to deploy an Alibaba Cloud International server and client within ten minutes, and even customize the obfuscation protocol.
Hugging Face releases a new 'Skill' and test harness designed to help port language models from the transformers library to mlx-lm, leveraging code agents to streamline open-source contributions.