Control your code in production.
Ship confidently with automatic recovery and continuous improvement built in.
Learn about CodeControlThe runtime control layer for the AI era.
Automatically control code and agent behavior in production—no redeploys or human intervention necessary.
Runtime control that works—at global scale.
Control at runtime only works if it’s fast, reliable, and global.
50T+
Flag evaluations per day
< 200ms
Config propagation, globally
99.99%
Enterprise uptime SLA
SOC 2 Type II
Certified
ISO 27001
Certified
ISO 27701
Certified
DPF
In accordance with GDPR and CCPA
Start using LaunchDarkly from your tools.
Operate LaunchDarkly directly from tools like Claude Code, Cursor, terminal, or your IDE. Manage code and agents from wherever you already work.
Agent-native from
Day 1.
Control and update behavior directly from tools like Claude Code, Cursor, your IDE, or terminal—no context switching required.
See agent integrations
Works across your
entire stack.
25+ native SDKs across frontend, backend, mobile, AI, and more. Control every part of your system at runtime.
View SDKs
Integrates with your existing delivery pipeline.
Works alongside your CI/CD and observability tools, adding control at runtime without changing how you deploy or monitor.
Explore integrationsWorks across your entire workflow.
GitHub
Gitlab
Vercel
Datadog
Elastic
Cloudflare
Segment
Sentry
VS Code
Cursor
Claude
The missing
layer in AI development.
You can build and deploy code and agents. But you can't control what happens after you release them.
Today's stack lets you build, test, and deploy—but control stops at release.
Runtime control fills that gap. It gives you the power to control deployment, reimagine observability, and adapt code and agent behavior in production as it happens.
You're not replacing your stack. You're adding the layer that lets it actually work at AI speed.
Code & Agents
Stay in control—no matter how you build.
- Feature Flags
- Targeting & Segments
- Progressive rollouts
- Automated rollbacks
- Feature monitoring
- Observability
- Error monitoring
- Logs & traces
- Session replay
- Auto-remediation
- Experimentation
- A/B/n testing
- Multi-armed bandits (MAB)
- Holdouts
- Warehouse native
- Self-healing
Control your agents in production.
One place to keep your agent behavior under control.
Learn about AgentControl- Online evals
- Offline evals
- Adaptive triggers
- Progressive rollouts
- Agent observability
- AI Insights
- Custom judges
- LLM Playground
- LLM traces
- A/B/n testing
- Agent graphs
- Approvals
- Agent definitions
- RBAC
- Prompt snippets
- Experimentation
Platform Overview Demo
See what teams can do with agents in production.
From release control to self-healing systems, these are the problems teams solve using runtime control—right from their existing toolset.
Ship AI-built code with confidence.
Progressively release changes and roll back instantly based on real-time impact.
Control and govern AI agents in production.
Monitor agent behavior, detect drift, and take action — without redeploying.
Optimize AI performance and cost.
Test prompts and models in production and dynamically route traffic to the best option.
Enable self-healing systems.
Automatically prevent issues, understand change behavior, and fix issues instantly with suggested changes and PRs.
Experiment continuously.
Experiment with code and agents in production and optimize based on real-world results.
Learn why industry leaders choose LaunchDarkly.
Get a demo
Install with AI using this prompt.
Drop this into your favorite coding assistant and get up and running with AI in seconds.
Onboard me to LaunchDarkly. Start by installing the onboarding skill: `npx skills add launchdarkly/agent-skills --skill onboarding -y`. source-launchdarkly
Got questions? We have answers.
Runtime control is a system that lets you control how software and AI behave in production—without redeploying code. It allows teams to control exposure, monitor behavior in real time, and adapt instantly as conditions change.