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Product managers
Test features with real users, see what’s working instantly, and adjust behavior in production—without waiting on engineering or redeploys.
Release features gradually, validate behavior in production, and stop or adjust changes before they impact users.
Ship changes to minimize impact on system stability.
Test features in production with a small audience to help reduce risk.
Turn off or modify feature and agent behavior in real time if something isn’t working.
Understand engagement, conversion, and system behavior tied to each change.
Compare how different users experience features with both metrics and session replay.
Make decisions based on real user behavior—not only hypotheses and evals.
Measure real user behavior and outcomes to see how features perform in production.
Update features, targeting, and experiences in real time—without redeploying code.
Adjust feature behavior or targeting without shipping new code.
React to performance, user behavior, or feedback immediately.
Disable or modify features as soon as problems arise.
Improve
Run experiments in production, promote what works, and continuously improve product performance.
Test variations in production to quickly validate ideas.
Shift traffic to the best-performing option based on real-time user data.
Use real-world results to refine features and drive better results over time.
We can take bigger risks in the kinds of AI features we build, and we can validate that they’re worth it because we can see downstream impacts all the way through.
