Short answer: interrupt the moment you see the same error twice, do not keep prompting. Stop the agent, read the last error yourself, and restart with a single explicit instruction that includes the error text.

How do you spot a loop before it wastes an hour?

Look at the agent’s action list, not its prose. A healthy run shows varied actions — editing different files, installing a package, running a new command. A loop shows the same two actions alternating.

Three signals mean stop now.

How do you break the cycle?

1. Press the stop button. Do not let it finish “figuring it out.”
2. Copy the full error text from the console or preview.
3. Identify the file and line the error points to yourself, in the editor.
4. Send one message: what the error is, what file is responsible, and what the correct fix is if you know it.
5. If you do not know the fix, check whether the previous agent edit broke a working file — then revert that edit in the version history.

Replit keeps checkpoints. Rolling back one bad edit often fixes the build faster than any prompt.

Why does more prompting make it worse?

Each failed attempt stays in the conversation. When you add “still broken,” the agent sees a growing pile of failed fixes and tends to try something more elaborate — a rewrite, a new library, a config change — instead of the boring correct fix.

Context pollution is the real problem. A clean restart with the error text and no history outperforms ten follow-ups on a polluted thread.

What are the common root causes?

In practice, most stuck builds trace back to a handful of things: a missing environment secret, a database schema that does not match the code, a port or start command mismatch in the deployment config, or a dependency version conflict introduced by the agent itself.

Check secrets first. An app that works in the workspace but fails on deploy is almost always missing a key in the deployment environment rather than a code bug.

How do you avoid this next time?

Commit or checkpoint after every successful feature, not at the end. That gives you a clean rollback point and keeps the working state recoverable. Ask the agent to run the test suite before declaring a task done, so failures surface in a small step instead of after three features.

And keep changes narrow. The larger the task you hand the agent in one go, the longer it runs before it notices it is wrong — and the more credits the loop costs.

Quick Summary

• Stop the agent as soon as the same error appears twice.
• Interrupting early saves credits; “still broken” follow-ups rarely help.
• Restart clean with the error text and the responsible file named.
• Roll back one bad edit via checkpoints faster than re-prompting.
• Check environment secrets first when workspace and deploy behave differently.

Short answer: start a new Replit workspace, describe an app in one scoped paragraph, let the agent scaffold it, test in the built-in preview, then hit Deploy. Keep tasks narrow and check the credit meter after every run.

What is Replit Agent 3?

It is an autonomous coding agent inside Replit. You describe an app; it plans, writes code, installs dependencies, runs the app, and browses its own output to verify it works before handing back.

Agent 3 can work on one task for up to about 200 minutes, which is a large jump over earlier versions that stopped after a few steps. It supports common stacks — React, Node, Python, and Postgres — and handles hosting and a database for you.

How do you start a project the right way?

1. Create a new Replit and choose Agent as the starting point.
2. Write one paragraph: what the app does, who uses it, and the three screens it needs.
3. Let the agent present a plan, then correct it before approving.
4. Watch the preview pane; test each screen yourself as it appears.
5. Add features one at a time through follow-up messages.

Vague starting prompts produce sprawling apps. “A task manager” gets you menus you did not ask for; “a single-page app where I add tasks with a due date and filter by today” gets you the thing you wanted.

How do you control credit spend?

This is the main practical concern. Agent 3 bills against credits, and a long autonomous run consumes them steadily.

Check the usage meter after each session. If you see the agent repeating the same fix three times, interrupt it — that is a stuck loop, and it will not resolve on its own.

How does deployment work?

Once the preview looks right, use the Deploy button. Replit provisions hosting and gives you a live URL, usually in a couple of minutes. You can attach a custom domain from the deployment settings.

Databases and secrets are configured in the workspace settings rather than hardcoded, which is what you want for anything beyond a toy. For a demo, the default setup is fine; for real traffic, check the deployment tier limits before launch.

What are the real limitations?

Agent 3 is strong at small full-stack apps and weak at large codebases. Past a few thousand lines it starts losing track of its own structure and duplicating logic. It also has no testing discipline unless you ask — generated code often ships without meaningful tests.

Cost is the other constraint. Heavy agent use on a complex app can consume a large share of a monthly credit allowance in a day or two.

It suits founders and hobbyists who want a working app fast and do not want to manage infrastructure. It is a poor fit for teams with strict security requirements or large existing repos they need to integrate with.

Quick Summary

• Replit Agent 3 runs autonomously for up to roughly 200 minutes per task.
• Scope the first prompt to one paragraph with three clear screens.
• It tests its own output in a real browser, but review every screen yourself.
• Credits burn fast on long runs — interrupt repeating fix loops.
• Best for small full-stack apps; it degrades past a few thousand lines.