Autonomous Coding Loops

As our team has experimented with agentic development, we’ve come to the same conclusion as many others: an agent needs tools to verify its own work. The more effective those tools are, the longer an agent can productively run and stay on track. An agent that can verify its own work as it goes can ask for less direction and is much more likely to return with a mostly done (and mostly correct) result.

Many tools exist to help agents verify their work. The most obvious ones are exactly the same ones that humans use — compilers, type checkers, tests.

But UI development is different. Human developers examine results visually, interact with them, navigate through flows. This is a harder step for an agent.

Playwright (often via Playwright MCP) is a powerful tool to give an agent insight into the browser experience. But it also incredibly context-hungry and testing multiple or repeated flows very often blows through the context and leads to repeated compactions and the corresponding loss of fidelity. An agent that spends most of its context on browser navigation has little left for the actual coding.

Separating verification from coding

Ideally, verification should be a separate process that’s hands-off for the coding agent. The agent kicks off a verification task, gets structured results back, and keeps its context for the work that matters: reading code, reasoning about architecture, writing changes.

That’s what Ranger Verify Feature does for browser-based verification.

It does this by spawning a separate browser agent for each verification. This agent has its own context window and its own Playwright session, meaning that it doesn’t distract from coding and many can be run in parallel. The only job of each of these agents is to navigate the app and determine whether a specific behavior works. It returns a verdict (verified, failed, partial, or blocked) along with screenshots, video, and traces. The coding agent never touches the browser directly.

This has a practical consequence: the write-verify loop can run many times without degrading. A coding agent using Playwright MCP might get three or four verification cycles before context pressure forces a compaction. With verification offloaded, the coding agent can iterate dozens of times and still have full recall of the codebase, the task, and its earlier decisions.

Running without supervision

This also changes what it means to supervise an agent. With inline browser testing, you’re often watching the session because the agent will go off track after a compaction or two. When verification runs separately and returns structured results, the agent can self-correct reliably. It reads the verdict, looks at the failure reason, fixes the code, and verifies again. This is a loop that works while you’re not watching.

This matters most for long-running sessions and background agents. If you kick off an agent before stepping away, you want to come back to a result, not a question. An agent with reliable UI verification can work through a feature end-to-end: implement the code, verify it in the browser, read the failure, fix the issue, verify again. Each iteration is cheap in context, and the structured feedback prevents the kind of drift that makes agents go in circles.

Evidence accumulates as the agent works. Screenshots, video, and Playwright traces are uploaded to the dashboard at each verification step. When you come back, you’re not reading a conversation log trying to reconstruct what happened. You’re looking at screenshots of your app and a clear pass/fail for each behavior.

The human review step

The agent writes and verifies in a tight inner cycle, then surfaces its work for human review.

The review happens asynchronously on the Ranger dashboard, where you can see exactly what the agent built and how it verified each behavior. If something needs to change, you leave a comment. The agent picks up that feedback, makes the fix, and re-verifies.

This is a different relationship with the agent than live pair programming. You define the feature, the agent does the work and checks itself, and you review the evidence when it’s done. The agent’s ability to verify its own UI work is what makes the handoff trustworthy.