From bug report to verified fix in minutes. AI agents that understand your codebase and resolve issues autonomously.
Bug fixing consumes 30-50% of a typical development team's bandwidth. Developers context-switch from feature work, spend time reproducing the issue, trace through unfamiliar code paths, write a fix, and then verify it does not break anything else. Agentik {OS} automates every step of this process for a large category of bugs.
Our bug-fixing agents read the error report, reproduce the issue in an isolated environment, trace the root cause through the codebase, generate a targeted fix, and run the existing test suite to confirm nothing else breaks. The fix is submitted as a pull request with a clear explanation of the cause and the solution.
Not every bug is straightforward. When the agent encounters an issue that requires architectural decisions or involves ambiguous requirements, it escalates to your team with a detailed analysis: root cause, affected code paths, proposed solutions ranked by risk, and test coverage gaps. This gives your developers all the context they need to make a decision quickly rather than starting the investigation from scratch.
The agent reads bug reports from GitHub Issues, Jira, Linear, or Slack and extracts the relevant error details, steps to reproduce, and affected components.
An isolated environment is spun up and the agent attempts to reproduce the bug using the reported steps. Logs and error traces are captured.
The agent traces the error through the codebase using call-graph analysis, recent commit history, and dependency mapping to identify the root cause.
A minimal, targeted fix is generated. The agent prefers the smallest change that resolves the issue without introducing side effects.
The existing test suite is run, and the agent writes additional test cases for the specific bug to prevent regression. A pull request is opened with full context.
The agent excels at logic errors, null reference exceptions, type mismatches, off-by-one errors, missing error handling, and incorrect API usage. Complex architectural bugs are escalated with detailed analysis.
Every fix is verified against your existing test suite, and the agent generates additional regression tests. It also performs static analysis on the fix to check for common anti-patterns.
Yes. The agent adapts to any codebase regardless of age. For legacy code with limited test coverage, it is more conservative and provides detailed explanations to facilitate human review.
See how our AI agents handle bug fixing and dozens more tasks autonomously.
Book a Demo