HAR 1.0: The open harness for AI coding workflows you can trust and verify (github.com)

HAR 1.0 has launched as an open-source agent harness designed to streamline and secure AI coding workflows. By enabling each coding agent to operate within its own isolated environment, HAR ensures consistent validation, verifiable outputs, and enhanced observability across projects. This approach addresses common challenges associated with running multiple agents on a single repository—such as conflicting dependencies and verification uncertainties—by establishing a clear, machine-readable contract. The tool integrates comfortably with popular coding agents like Claude Code and Codex, allowing developers to leverage their existing CI/CD processes while customizing their workflows. The significance of HAR for the AI/ML community lies in its ability to foster a more reliable and efficient development environment. With features such as deterministic validation steps, an open-source local dashboard for project tracking, and a growing ecosystem of plugins, HAR empowers developers to trust the outputs of their coding agents without exhaustive manual checks. Moreover, by standardizing the verification process and maintaining a clear evidence trail, HAR helps mitigate the risks associated with complex AI coding tasks, ultimately promoting better collaboration and quality assurance in software development.