What’s worth
building next?

Yes. Wave gives you a practical way to apply AI to a product goal you already care about, such as activation or conversion. Start by reviewing opportunities and their supporting evidence, then move an approved change through your existing development process. Your team sets the direction and decides what ships, so you can build confidence as you go.

Yes. Dismissals, comments, and edits help Wave understand what matters within each Product Area. Explaining why you rejected an idea, such as a business constraint or an intentional design choice, gives future investigations useful context. Wave uses that feedback alongside your goals to make subsequent recommendations more relevant to your team.

Wave respects your Amplitude access controls and keeps your organization’s context separate. Connected code is not used to train shared models, and Amplitude contractually prohibits its AI providers from training on your customer data. Amplitude’s coding agent works in isolated environments and opens pull requests for your team to review. External coding providers operate under your agreements with them.

Start with an eligible Amplitude Growth or Enterprise plan, meaningful Product Analytics and Amplitude Session Replay data, and a business goal you want to improve. You’ll also need product and engineering owners who can review recommendations and act on them. Connecting relevant repositories gives Wave the context to ground implementation plans in your code. Our team can help assess your readiness.

Yes. Focus Wave on one journey or product surface, such as onboarding or checkout. Define its goals, target metrics, and boundaries, then review the opportunities it discovers. You can test a change and establish a working process before expanding. Each Product Area has its own scope and feedback, so teams can steer recommendations around their priorities.

After setup, the first discovery run can take up to an hour. You can then share prioritized opportunities, their supporting evidence, and the metrics they target. Demonstrating business impact depends on how quickly your team ships a change and collects enough data to measure its effect. Wave connects that outcome back to the original opportunity.

Yes. Wave uses experiment results to understand what you’ve already tried and inform future recommendations. With Amplitude Experiment, your team can test proposed changes against target metrics and guardrails, then feed measured outcomes into the next investigation. If you use another experimentation platform, our team can assess how its results fit into your Wave workflow.

Your engineers can build a custom workflow. They would also need to maintain the data connections, product context, recommendation quality, execution handoffs, and measurement that make it useful over time. Wave brings those capabilities together on top of Amplitude and works with your engineers and coding agents. That lets your team put more of its effort into the product improvements themselves.

Wave’s focus is turning customer evidence into shipped improvements with measurable outcomes. You give it a Product Area, business goals, and guardrails. It investigates opportunities, prepares plans grounded in your code, and helps your team or coding agents move them into implementation. The evidence, plan, and measured result stay connected, giving the next investigation context about what your team has already learned.