“Issue tracking is dead”; How the pull request became the last chokepoint in the SDLC bottleneck

CodeRabbit has unveiled Agentic Change Management, a new control layer designed to manage the software development lifecycle (SDLC) in an era where AI-generated code is becoming increasingly prevalent. According to CodeRabbit CEO Harjot Gill, traditional issue tracking systems like Jira and GitHub Issues are outdated and no longer effective in managing the rapid flow of code produced by both human developers and AI agents.

In today's software engineering landscape, Gill argues that the conventions and mechanics of the SDLC have evolved. AI-driven platforms can create code or open pull requests continuously, leading to an abundance of code that often precedes proper alignment, prioritization, and decision-making. As a result, the pull request has emerged as the last real chokepoint in the SDLC, serving as an auditable decision point for determining whether a change meets quality standards, carries risk, requires human attention, impacts the larger system, and should be accepted and shipped.

CodeRabbit's Agentic Change Management extends its AI code review services to a broader system for governing software change. By utilizing its proprietary codegraph technology, the platform dissects codebases into trust boundaries, mapping out how every element is interconnected. This context generation pipeline guides AI on how code changes can affect other areas, enabling more effective human review focused on intent, architecture, behavior, and trade-offs rather than line-by-line code inspection.

In this new paradigm, adversarial review agents work alongside coding agents in a loop, automating review, validation, and remediation processes before human approval.