Your testing tool runs tests. pagent builds them.

Every testing platform shares a silent assumption: someone else produces the test. Someone reads the data and writes a hypothesis worth running. Someone builds the variant. Someone checks it on desktop and mobile. Someone starts the test and reads the result. The tool runs experiments. Your team produces them.

That assumption is why most testing programs run five tests a month while the backlog holds fifty. The bottleneck was never the tool. It is the capacity to specify, build, and QA each experiment.

pagent removes that bottleneck. It is the AI Experiment Engineer: an agent that runs the whole loop on your live site. It analyzes your pages and your data. It writes hypotheses like a senior CRO strategist: specific, prioritized, worth testing. It builds each variant as real code with your components, your spacing, your tone. It checks its own work on desktop and mobile, runs the test to the statistical standard you already use, whether Bayesian, frequentist or sequential, and learns what to try next.

In practice that changes four things:

• Hypotheses at human level. Test ideas from most tools are weak. pagent’s are backed by the page’s own data and ready to run.
• Variants that match your design system. Tests look like your site, not like a testing tool. No flicker, real code, on most sites running on the first try.
• Complex changes, whole site. From new copy to UI and UX changes, including the long-tail pages and segments that never reach a roadmap.
• Idea to live in days. Not a sprint, not a quarter. Launch capacity stops being the limit on your backlog.

The results compound. One shop reached +16 % order conversion, with the first measurable uplift about 10 days after going live.

If you want the deeper comparison of how pagent fits next to the tools you already run, read the AI A/B testing agent page and the tool guides. Or skip ahead: we will show it on your own shop. Get a demo.