At first glance, feature flag and experimentation platforms don’t seem closely tied to AI. But at GrowthBook, we see it differently. These platforms don’t just test whether a feature works technically—they test whether it delivers the business outcomes developers intended. That distinction is critical, and it’s exactly the kind of feedback loop AI coding platforms need to evolve.
Research shows only about one-third of software features actually deliver the expected results. Another third make little difference. And the final third actively harm key metrics like conversion or engagement. Without structured feedback, teams repeat the same costly mistakes.
Now imagine an AI that could warn you before you invested weeks of engineering effort: “This feature is unlikely to move the needle.” That’s the future we believe is coming.
The Next Frontier for LLMs
Most AI coding tools today help developers build features exactly as they always have. Which means they’re just as likely to produce features that underperform. The next breakthrough will be AI systems that understand what to build and how to build it—drawing on millions of past experiments.
OpenAI has already hinted at this direction. In its GPT-5 Prompting Cookbook, it recommends creating a rubric to evaluate a development plan, then iterating until the plan earns top marks. Now imagine if that rubric weren’t handcrafted, but instead learned automatically from thousands of feature tests. AI wouldn’t just critique plans. It would know what success looks like—and guide you there directly.
That’s a leap toward more intelligent, agentic AI—not only in coding, but also in fields like finance and healthcare, where feedback loops are abundant.
Bringing Agentic Coding Into Your Workflow Today
The good news: you don’t need to wait for the future. With GrowthBook’s MCP server, AI coding tools can already tap into your past experiments to build intelligent rubrics. They can:
- Design and deploy experiments for the features they create
- Measure results in real time against your KPIs
- Iterate continuously until outcomes align with business goals
The scale of experimentation today is staggering. GrowthBook customers collectively run hundreds of thousands of experiments each month—and that number is growing. AI now has the ability to unlock insights from this volume of data in ways that were never possible before.
The Bigger Impact
Building a culture of experimentation does more than improve feature delivery. It accelerates innovation, drives better customer experiences, and creates measurable gains in usage, retention, and sales.
Feedback loops will make agentic AI smarter, faster, and more valuable to every software team. The future of coding isn’t just about writing code—it’s about learning from every outcome. And with the right experimentation infrastructure, that future is already here.