Amplitude is showcasing a practical example of AI speeding up product development with Wave, its proactive product agent built primarily on OpenAI models. The agent helps teams identify what to build, collaborate with coding agents to implement changes, and measure whether those changes actually improve the product.
From insight to impact, faster
Instead of stopping at analytics or recommendations, Wave supports a fuller product workflow: spotting opportunities, helping teams take action, and tracking outcomes. According to OpenAI’s customer story, this can help Amplitude ship product improvements in just 1–2 days.
This is a strong example of AI moving beyond simple assistance into agentic workflows that connect decision-making with execution. For product teams, that means faster experiments, shorter feedback loops, and more time spent improving the user experience.
Why it matters
- Speed: AI helps compress product iteration cycles from idea to shipped change.
- Focus: Teams can prioritize improvements backed by product signals.
- Measurement: Wave closes the loop by assessing the impact of changes after release.
While this is a business deployment rather than a scientific breakthrough, it points to a broader win: AI agents are becoming useful partners for real-world teams, helping them turn data into measurable product progress.