Unlock more learning with every experiment
Blog post from GrowthBook
GrowthBook has launched Learnings, a feature intended to turn accumulated experiment results, user research, and other evidence into a shared organizational knowledge base for people and AI agents. Rather than treating A/B tests as isolated decisions, Learnings captures broader patterns across multiple studies, such as which approaches work for particular user segments or product areas, while linking conclusions to supporting and conflicting evidence and allowing them to be scoped, updated, or marked uncertain. The feature addresses the difficulty of finding relevant insights among large experiment archives by providing a compressed layer of decision-relevant context, accessible through GrowthBook APIs, MCP support, and agent-oriented Skills. GrowthBook can also use AI to identify candidate patterns across experiment histories, though teams retain responsibility for reviewing them. The company emphasizes that clear hypotheses, context, results, and conclusions are essential because better experiment documentation makes both individual tests and the broader knowledge base more useful over time.
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