Overview
LaunchDarkly is the runtime control layer for AI-era software, helping engineering teams safely manage code and AI agents in production. It combines feature flags, progressive delivery, and automated rollback with a dedicated AgentControl platform that governs LLM behavior, prompts, and model routing in real time.
Developers love LaunchDarkly because it turns risky production changes into controlled, reversible experiments. Whether you are shipping AI-built code, tuning prompts, or deploying autonomous agents, LaunchDarkly gives you the observability, targeting, and self-healing capabilities to move at AI speed without losing control.
The platform is built for both developers and their agents, offering native integrations, a LLM Playground, and agent-native onboarding so teams can adopt it quickly and scale it across their entire stack.
Key Features
- Feature Flags & Progressive Rollouts: Target and segment users, roll out changes gradually, and monitor impact in real time before full deployment.
- Automated Rollbacks & Self-Healing: Instantly remediate failing code and misbehaving agents without human intervention, keeping systems stable.
- AgentControl: Govern AI agents in production with online/offline evals, adaptive triggers, agent observability, custom judges, and RBAC.
- AI Performance & Cost Optimization: Test prompts and models in production, dynamically route traffic to the best option, and track cost trends.
- Experimentation Platform: Run A/B/n tests, multi-armed bandits, and holdouts on both code and agents to optimize based on real-world results.
- Observability & Monitoring: Error monitoring, logs & traces, session replay, and feature monitoring for full-stack visibility.
Use Cases
- AI Engineering Teams: Ship AI-built code with confidence by progressively releasing changes and rolling back instantly based on real-time impact metrics.
- Product & Data Teams: Run reliable experiments on AI agents and code, with trusted data and a
