Capture reusable Learnings across experiments

Learnings let you save conclusions from multiple experiments and bring that evidence into future work. Capture a pattern once, keep supporting and contradicting experiments attached, and make the conclusion available to teammates and agents planning the next change.

Keep the evidence with the conclusion

Each learning can carry the context needed to interpret it:

• Link experiments that support or contradict the conclusion.
• Scope the learning to projects and tags.
• Use a customizable status to mark unverified or outdated conclusions.
• Update the learning when new evidence arrives.

You can also capture qualitative findings alongside experiment evidence. Keep the conclusion's scope clear so a pattern from one workflow doesn't become a rule for every part of your product.

Bring past evidence into new work

Learnings are accessible through GrowthBook's API and MCP support. Agents can retrieve relevant conclusions before designing or implementing a change, with the underlying experiments still available as evidence.

Getting started

Open the Learnings page and add a conclusion with its supporting and contradicting experiments. For API creation and updates, your plan must include Learnings. Semantic search also requires AI access and available embedding capacity.

See the Learning record reference for the fields a learning can contain.