# Automated Bug Fixes

Automated bug fixing works best when an agent can inspect real code, reproduce failures, run checks, and return either a fix or a clear debugging handoff.

- Canonical: https://tryreplicas.com/use-cases/automated-bug-fixes
- Start a workspace: https://tryreplicas.com/auth?mode=signup
- Sentry docs: https://docs.tryreplicas.com/features/sentry

## What are automated bug fixes?

Automated bug fixes are agent workflows that start from a concrete failure signal: a CI failure, Sentry issue, failed E2E test, bug report, or reproduction step.

The valuable part is not only editing code. A strong bug-fixing agent can also reproduce the issue, explain why it happens, identify the responsible code path, and tell the team when a safe fix is not obvious.

## How Replicas handles bug-fixing work

Bug fixes need evidence. Replicas gives the agent a workspace where it can inspect files, run commands, and return a visible trail.

- **Failure signal arrives:** The task starts from CI, Sentry, a human report, Slack, Linear, or another concrete signal.
- **Agent reproduces or narrows:** Replicas can run tests, inspect logs, search code, and identify the most likely failing path.
- **Fix is attempted:** When the bug is scoped enough, the agent edits code and reruns the relevant checks.
- **Handoff stays reviewable:** The result is a PR, test output, reproduction note, or blocker summary for human review.

## What bug reports work best?

The best automated bug-fix tasks have a signal the agent can verify. Without that, the right output is often an investigation note rather than a guessed patch.

- Failed tests or CI logs with a clear failure mode.
- Sentry issues with stack traces and affected routes.
- Bug reports with reproduction steps.
- Flaky E2E flows that need repeated runs and logs.
- Regression reports linked to a recent PR or code area.

## How to evaluate automated bug fixing

A useful bug-fixing agent should reduce debugging time without hiding uncertainty. The human reviewer should see what was reproduced, what changed, and what still might be risky.

- Does it reproduce or narrow the bug before changing code?
- Does it run the smallest relevant checks after the fix?
- Does it explain the root cause or only provide a patch?
- Does it avoid broad refactors when a targeted fix is enough?
- Does it return a clear handoff when it cannot safely fix the issue?

## FAQ

### Can Replicas fix bugs automatically?
Replicas can investigate and attempt fixes in a cloud workspace. The output should still be reviewed by humans before merging or deploying.

### What happens if the bug cannot be reproduced?
The agent should return what it tried, the evidence it found, and the missing information rather than inventing a fix.

### Are automated bug fixes only for CI failures?
No. CI is a strong trigger, but bug-fix sessions can also start from Sentry, Slack, Linear, PR comments, or manual requests.

## Related docs

- [Cloud coding agents](https://tryreplicas.com/cloud-coding-agents): Learn why cloud workspaces make delegated engineering tasks practical.
- [Code review follow-up](https://tryreplicas.com/use-cases/code-review-follow-up): See how PR comments, CI failures, and review findings become follow-up work.
- [Automations docs](https://docs.tryreplicas.com/features/automations): Configure event-driven and scheduled workflows for Replicas workspaces.