Harness, the platform for the autonomous SDLC, launched Agent-Ready Harness Code Repository and AI Code Review, built for teams increasing their adoption of AI coding agents. The capabilities are designed to work as one experience: code lands in a repository built for the volume now generated by agents, and is reviewed by a system that understands what a change puts at risk.
Coding stopped being the hard part
Generating code is no longer the constraint. With agents in the loop, teams produce far more code, far faster, than they could alone, and the work has shifted to what happens next: storing, reviewing, approving, and shipping all of it without anything breaking.
The tools underneath were not built for that. Legacy source code management tools in wide use today, GitHub included, assume a human writes code and opens a pull request before a few colleagues look at it over the next few hours or days. When agents are doing the writing, the cracks show up in ordinary places: search and file history get slower as indexing falls behind, pull requests pile up faster than anyone can read them, and a permission system designed around a list of developers has no good answer for an agent that might merge code on its own. Harness has now rebuilt that layer.
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“Software delivery is going through its biggest shift since the move to the cloud, and the systems we all built our workflows around were designed for a different scale and a different kind of user,” said Jyoti Bansal, CEO and co-founder of Harness. “You do not solve that by adding AI features to a repository designed fifteen years ago. The entire SDLC has to become autonomous, which means the repository, the review, the pipeline, and the governance must all work as one system.”
One platform, from commit to production
Committing, reviewing, building, testing, securing, and deploying code already follow a single sequence inside Harness, which is why the repository and the review layer could ship together. Both are now part of the outer loop that the Harness Software Delivery Agent runs end-to-end, from commit to production, under one policy engine.
That sequence is also what makes the review useful. Harness already knows how a team releases software, which policies they enforce, and what has failed in their production before. All of that is mapped in the Harness SDLC Knowledge Graph, providing enterprise context for every review to reference.
SOURCE: PRNewswire