Introducing Agentic Change Management | CodeRabbit<br>We raised $143M to build the control layer for software change.Read more

Log InGet a free trial

*+*]:mb-0! [&>*+*]:mt-16! md:[&>*+*]:mt-30! lg:[&>*+*]:mt-38!">Code is abundant. Judgment is scarce. We raised $143 million to help it scale.<br>by

Harjot Gill<br>Gur Singh

August 12, 2026<br>•9 min read

Issue tracking is dead. And that’s changing everything.<br>Introducing the Agentic Change Management platform<br>CodeRabbit Triage directs attention<br>CodeRabbit Change Stack explains the change<br>CodeRabbit Security protects what has shipped<br>AI that keeps humans in the loop<br>Why we’re raising now

Back to blog

When we founded CodeRabbit, AI was already changing how software was written. We saw where the industry was going and there was one question that we knew would become increasingly important. Who would independently verify all of that code?

That led us to create the first AI code review product. Over the last four years, CodeRabbit became the industry-leading independent AI code review layer. It understands your codebase, learns from your team, and gives developers evidence-based feedback they can trust and act on.

Fast forward to today. We’re announcing two milestones.

The first is that less than a year after raising our Series B, we raised $143 million in a Series C funding round at a $1.5 billion valuation. Atomico and Smash Capital co-led the round, with participation from new investors, including BMW i Ventures, Datadog, Hirtle Callaghan, SineWave Ventures, Scenic Management and our existing investors, including CRV, Scale Venture Partners, Flex Capital, Pelion Venture Partners, Harmony Partners and Engineering Capital.

We’re also introducing a new product category we call Agentic Change Management, a platform that represents the next chapter for CodeRabbit. In conversations with thousands of teams trying to navigate the changes AI coding agents have made to their workflows, we realized that AI code review only solves part of the problem.

Agentic Change Management requires a full suite of tools to help teams validate what should ship, prioritize where developer attention and time generate the most value, explain the intent and risk of the massive PRs AI generates, and keep their codebase healthy after merge in the face of increased AI security threats.

Issue tracking is dead. And that’s changing everything.

It used to be that implementation was expensive. Teams discussed what to build, established priorities, assigned the work, and then carefully invested scarce engineering time in turning an idea into code.

The high cost of implementation forced planning and judgment to happen before the code existed.

AI is reversing that sequence.

A product requirement, support ticket, security finding, or production alert can now easily and quickly become a proposed code change with the rise of autofix features.

Coding agents can work for hours, produce thousands of lines, and open pull requests with limited human involvement. Anyone on your team can initiate code changes, be they developers, product managers, designers, or even marketers.

The shift is compounding. GitHub is on pace to record 14x more commits this year. Among companies in the 90th percentile of coding-agent adoption, autonomous agents open 35% of PRs.

Because of that, code increasingly exists before a team has decided whether the work is valuable, how it should be prioritized, or whether it deserves engineering attention. The backlog is moving from tickets to pull requests.

And that shift fundamentally changes the role of the PR.

The PR is set to become the auditable planning and decision point where the team determines what to ship and whether a change meets the quality bar, what risks it introduces, how it affects the larger system, and whether it is ready to ship.

The problem teams now need to solve is the fact that human attention remains finite while the PR backlogs continue to grow. Large scale agent outputs exceed the time humans have to understand them. Every PR adds new relationships, dependencies, security exposure, and maintainability risk to the codebase.

The new bottleneck is judgment.

Introducing the Agentic Change Management platform

The Agentic Change Management platform is the control layer for software changes created by humans and agents.

It extends CodeRabbit’s independent AI code review into one connected system that validates changes, prioritizes attention, explains impact, and continuously monitors the shipped codebase.

Proposed changes should come with evidence, a priority, and an explanation people can understand, and the codebase they land in should stay secure and governable as it evolves.

Independent AI code review remains the foundation. CodeRabbit evaluates changes using multi-repository context, organizational standards, pre-merge checks, team knowledge, and evidence from isolated test environments. It challenges the assumptions behind a change and verifies...