Code review that fixes AI-written code, on your machine.
The agents ship. Your engineers carry the risk. Truemend finds the mistakes coding agents repeat, shows each fix as a diff you can read, and hands bigger changes to your team.
The catch block is empty, so a failed query is dropped and never reaches the logger.
Rather start with a person? I run audits alongside your team.
Truemend does the reading. Your team makes the calls.
Illustrative sample run. Review diffs and run your tests before merging. How to read a finding
What a run gives you.
What it catches →One command on your machine. Nothing on disk changes until you apply a fix.
A bare except hides the real failure mode. Narrow it to the real exception type and log the context.
Each finding sits on its line in the pull request, with its tier and the change on offer.
The report prices the backlog by tier, so the work can be planned before the sprint starts.
Illustrative output, built from the halyard-api sample report.
Measured in public, losses included.
All results, with dates and scope →Truemend10.9%
Semgrep17.1%
Share of findings judged wrong on Netflix Dispatch. Lower is better.
On NetBox, Bandit, Pylint and Ruff combined beat it. That result is published too.
A product, and a person who works through it with you.
I lead every engagement myself, and bring in engineers I’ve worked with when a job needs more hands. The goal is a team that keeps its own code straight without outside help.
Why Truemend exists →Run it on a repository you already have.
$ pip install truemend$ truemend .