Amplitude said its Wave product agent can turn product insights into shipped changes in 1-2 days, versus roughly a month before, by handing implementation plans directly to coding agents.
On Amplitude’s own homepage, Wave found users were ignoring generic suggestion cards—80 of 100 replayed users typed their own prompts, while only 12 clicked a suggestion—and proposed personalized cards.
That change produced a 160% increase in messages sent through homepage suggestion cards versus control after one day, following a brief human review and an A/B test.
Amplitude said Wave is about 80% powered by OpenAI models: GPT-6.1 Sol for deeper investigations, GPT-6 Luna for cheaper high-volume checks, and GPT-Image-2.5 Flare for mockups.
Among customer-launched experiments, flags and guides, one in four went live the same day Wave surfaced the opportunity, half within four days, pointing to Amplitude’s push toward self-improving products.
Could automating product changes in a single day lead to massive feature bloat rather than genuinely improving the user experience?
If Wave feeds user session data directly into OpenAI models, how can companies guarantee sensitive customer information remains completely secure?
If AI agents can identify problems, write technical plans, and deploy code autonomously, what exactly remains of the traditional product manager's role?