Agents write the code. Release Autopilot gets it safely to customers.
Blog post from LaunchDarkly
AI-assisted software development is increasing the volume and speed of code changes, creating a release-management bottleneck as engineering teams remain accountable for production failures despite relying more on automated generation, testing, and review. LaunchDarkly’s Control Gap Report found that 94% of surveyed engineering leaders believe AI has accelerated development, while 91% have become more cautious about deploying AI-generated changes. LaunchDarkly introduced Release Autopilot to automate safeguards around releases while allowing teams to retain control through configurable approvals and guardrails. The product assesses change risk, recommends or applies feature flags, manages staged rollouts, monitors technical and business metrics, automatically rolls back problematic changes without redeployment, and helps remove obsolete flag-related code. LaunchDarkly and Ramp report that broader use of automated release controls has supported substantial growth in flagged changes and pull requests while reducing serious incident time, positioning the platform as a control layer intended to let organizations delegate more release work to AI agents without sacrificing oversight. Select Release Autopilot capabilities are available in beta.
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