Statsig

Statsig combines feature gates (flags), dynamic configs, experiments, and product analytics in a single platform. For agents, the key differentiator is the experimentation engine: Statsig automatically computes statistical significance for A/B tests, removing the need for agents to implement their own statistics. Feature gates support boolean and multivariate evaluation. Dynamic configs provide remote configuration management. The SDK evaluation model mirrors LaunchDarkly — local evaluation with background syncing. The REST Console API covers gate/config/experiment CRUD, targeting rules, and result retrieval. The generous free tier (1M events/month) makes Statsig accessible for experimentation. Warehouse-native mode connects to Snowflake, BigQuery, or Databricks for analysis on existing data. For agents managing product experiments, Statsig's automated statistical analysis is a major productivity gain.

Console API uses console API keys created in project settings. SDK evaluation uses server/client secret keys. Keys are scoped per-project. Console API keys grant management access to the project. The key model is simpler than LaunchDarkly — no role-based scoping on API keys. Access control is managed at the project member level in the dashboard. For agents, a console API key per integration provides clean isolation. No OAuth for third-party integrations. Keys don't expire by default. The free tier's generosity means agents can experiment without cost pressure. TLS is enforced. The main security consideration: console API keys grant broad project access — there's no way to create a key that can only manage gates but not experiments.

Documentation at docs.statsig.com is well-organized with quickstart guides, SDK references, and conceptual explanations. The experimentation documentation is particularly strong — it explains statistical concepts (significance, power, sequential testing) in accessible terms. SDK documentation covers initialization, evaluation, event logging, and shutdown for each language. The Console API reference includes endpoint descriptions and examples. The Statsig blog publishes engineering and statistical methodology posts that inform advanced usage. Community support via Slack. The documentation's main strength: it bridges feature management and experimentation concepts, helping agents understand when to use gates vs. experiments vs. dynamic configs. For agents new to experimentation, the learning materials are better than most competitors.

Two integration surfaces: SDKs for evaluation and Console API for management. Server-side SDKs (Node, Python, Java, Go, Ruby, .NET) evaluate gates and configs locally with background sync — similar to LaunchDarkly's model. The Console API at statsigapi.net/console/v1/ covers gates, dynamic configs, experiments, segments, and metrics. Gate creation and targeting use rule-based conditions on user attributes. Experiment creation defines control and test groups with metric targets. The API returns experiment results with statistical significance, confidence intervals, and relative lifts. Event logging via SDK tracks user actions for experiment analysis. The Console API uses simple JSON REST — easier to construct than LaunchDarkly's semantic patching. Pagination uses cursor-based tokens.

Console API errors return JSON with status and message. HTTP status codes follow conventions. SDK evaluation is resilient — cached configurations enable continued evaluation during network interruptions. Experiment results include p-values and confidence intervals, and Statsig flags results that haven't reached statistical significance — this guards agents against premature decisions. The experiment engine uses sequential testing to account for peeking, reducing false positives. Rate limits on the Console API are documented but generous. Event ingestion is async with eventual consistency — metrics may take minutes to reflect recent events. The main reliability consideration: the free tier has event quotas, and exceeding them degrades analytics but doesn't break flag evaluation. Gate evaluation is independent of analytics pipeline health.