For AI agents: a documentation index is available at the root level at /llms.txt and /llms-full.txt. Append /llms.txt to any URL for a page-level index, or .md for the markdown version of any page.
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DocsGuidesSDKsIntegrationsAPI docsTutorialsFlagship blog
  • Guides
    • Cheatsheets
    • Feature flags
      • Best practices for upgrading users to contexts
      • Creating flags
      • Deciding between flag targeting strategies
      • Defining and targeting mobile applications
      • Feature flag hierarchy
      • Flag conventions
      • Improving flag usage in code
      • LaunchDarkly CLI dev-server reference guide
      • Performing multi-stage migrations with migration flags
      • Reducing technical debt from feature flags
      • Testing code that uses feature flags
      • Using entitlements to manage customer experience
      • Using flags on static sites with JavaScript
      • Using the LaunchDarkly CLI for local testing
      • Using segments and targeting to manage early access programs
    • AgentControl
    • Experimentation
    • Statistical methodology
    • Metrics
    • Infrastructure
    • Account management
    • Teams and custom roles
    • SDKs
    • Integrations
    • REST API
    • Additional resources
  • Guides
  • Cheatsheets
  • Control and govern AI agents in production
  • Enable self-healing systems with runtime controls
  • Optimize AI performance and cost with AgentControl configs
  • Run continuous experiments in production
  • Ship AI-built code with AgentControl or CodeControl
  • Feature flags
  • Best practices for upgrading users to contexts
  • Creating flags
  • Deciding between flag targeting strategies
  • Defining and targeting mobile applications
  • Feature flag hierarchy
  • Flag conventions
  • Improving flag usage in code
  • LaunchDarkly CLI dev-server reference guide
  • Performing multi-stage migrations with migration flags
  • Reducing technical debt from feature flags
  • Testing code that uses feature flags
  • Using entitlements to manage customer experience
  • Using flags on static sites with JavaScript
  • Using the LaunchDarkly CLI for local testing
  • Using segments and targeting to manage early access programs
  • AgentControl
  • Getting started with OpenAI and AgentControl
  • Getting started with Anthropic Claude and AgentControl
  • Getting started with Google Gemini and AgentControl
  • Getting started with Amazon Bedrock and AgentControl
  • Getting started with LangChain and AgentControl
  • Getting started with LangGraph and AgentControl
  • Getting started with Strands and AgentControl
  • Managing AI model configuration outside of code
  • Using targeting to manage AI model usage by tier
  • When to use prompt-based vs agent mode
  • Building a chatbot with multiple AI providers using AgentControl
  • Experimentation
  • Creating an A/B experiment using a funnel metric group
  • Creating mutually exclusive experiments
  • Designing experiments
  • Example experiments
  • Experimentation best practices
  • Bayesian versus frequentist statistics
  • Maintaining consistency across user sessions when running experiments
  • Measuring Experimentation impact with holdout experiments
  • Migrating from Statsig to LaunchDarkly Experimentation
  • Proving ROI with data-driven AI agent experiments
  • Sample size calculations for frequentist experiments
  • Statistical methodology
  • Choosing a statistical methodology
  • Covariate adjustment and CUPED methodology
  • Statistical methodology for Bayesian experiments
  • Statistical methodology for frequentist experiments
  • Multiple comparisons correction
  • Stratified sampling
  • Sample ratio mismatch
  • Metrics
  • Building a metric import and sync integration
  • Example metrics
  • Understanding LaunchDarkly metrics
  • Using metrics from engineering insights
  • Infrastructure
  • Deployment and release strategies
  • Managing flags with Terraform
  • Using flags with Cloudflare Workers
  • Using LaunchDarkly in serverless environments
  • Account management
  • LaunchDarkly for large enterprise teams
  • Merging LaunchDarkly accounts
  • Migrating your existing feature flag solution to LaunchDarkly
  • Minimizing LaunchDarkly's access to end user data
  • Onboarding to views
  • Using LaunchDarkly with Protected Health Information (PHI)
  • Using SSO with LaunchDarkly
  • Teams and custom roles
  • Building teams in LaunchDarkly
  • Creating roles
  • Onboarding to preset roles
  • SDKs
  • Unit testing with Jest
  • Use cases for SDK wrappers
  • Using LaunchDarkly without a supported SDK
  • Using mobile SDKs
  • Using the Lua SDK with HAProxy
  • Using the Lua SDK with NGINX
  • Using the JavaScript SDK in Salesforce Lightning Web Components
  • Resilient architecture patterns for LaunchDarkly's SDKs
  • Integrations
  • About LaunchDarkly integrations
  • Integrations use cases
  • Using flag triggers with Dynatrace
  • Building a change history event hook integration
  • Building an ephemeral Environments as a Service integration
  • Building a synced segments integration
  • LaunchDarkly Shopify Pixel
  • REST API
  • Comparing LaunchDarkly's SDK and REST API
  • Using the LaunchDarkly REST API
  • REST API migration guide
  • Additional resources
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Guides

Feature flags

These guides help you excel in the use of LaunchDarkly’s fundamental product feature: the feature flag.

  • Best practices for upgrading users to contexts
  • Creating flags
  • Deciding between flag targeting strategies
  • Defining and targeting mobile applications
  • Feature flag hierarchy
  • Flag conventions
  • Improving flag usage in code
  • LaunchDarkly CLI dev-server reference guide
  • Performing multi-stage migrations with migration flags
  • Reducing technical debt from feature flags
  • Testing code that uses feature flags
  • Using entitlements to manage customer experience
  • Using flags on static sites with JavaScript
  • Using the LaunchDarkly CLI for local testing
  • Using segments and targeting to manage early access programs
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