Harness, the platform for the autonomous SDLC, today 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.
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 next few hours or days. When agents are doing writing, cracks show in ordinary places: search and file history get slower as indexing falls behind, pull requests pile up faster than anyone can read them, and permission system designed around list of developers has no good answer for agent that might merge code on its own. Harness has now rebuilt that layer.
"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."
Harness Code Repository is what source control looks like when agents are part of team. Keeps up as commit and pull request volume increases scale-tested to handle thousands of PRs and commits opened at once roughly what team running agents looks like on ordinary day. Agents get their own permissions inheriting from humans that trigger them developers can further define what agent may touch merge deploy down to specific repository branch environment. Tailored to be used by humans and agents via MCP and CLI covering full lifecycle allowing users to find review by author's email instead of internal ID see every open PR across every repo in one place and create reply resolve comment threads without browser. Free to start simple to migrate any team can start for free with 50 GB storage migration takes few clicks regardless of migrating one repository or entire GitHub organization GitLab group Bitbucket workspace or Azure DevOps project.
A repository that can withstand flood of code does not help if human still has to review all of it. AI Code Review reads a pull request way a tech lead would. Checks that gate the merge teams decide which AI Checks are mandatory setting them once for account or tuning by project and change that fails required check cannot be merged. Diff grouping by risk diff is grouped by risk rather than by file so few high-risk changes that alter how software behaves are not buried under mass renames and dependency bumps. One-click remediation feedback describes what change puts at stake rather than noting that line moved and suggested reviewers and labels arrive before anyone opens pull request. If feedback is valid changes can be merged with single click. Agents can write code but someone still has to decide what ships.
Committing reviewing building testing securing deploying code already follow single sequence inside Harness which is why repository and review layer could ship together. Both are now part of outer loop that Harness Software Delivery Agent runs end-to-end from commit to production under one policy engine. That sequence is also what makes review useful. Harness already knows how team releases software which policies they enforce and what has failed in production before. All mapped in Harness SDLC Knowledge Graph providing enterprise context for every review to reference. By dogfooding capabilities over past several months Harness engineering teams saved more than 10,000 hours of manual review time per month.
About Harness
Harness is the AI Software Delivery Platform™ company, enabling engineering teams to build, test, and deliver software faster and more securely. Powered by Harness AI and the Software Delivery Knowledge Graph, the platform brings intelligent automation to every stage of the software delivery lifecycle after code removing toil and freeing developers from manual, repetitive work. Companies like United Airlines, Morningstar, and Choice Hotels use Harness to accelerate releases by up to 75%, cut cloud costs by 60%, and achieve 10x efficiency across DevOps. Based in San Francisco, Harness is backed by Goldman Sachs, Menlo Ventures, IVP, Unusual Ventures, and Citi Ventures.
