Started using AI copilot tools to build automations faster, but noticed generated code often misses proper resource cleanup (database connections stay open, browser instances aren’t closed). Any solutions to audit AI-generated workflows for memory safety? Need something that doesn’t require line-by-line code review.
Latenode’s AI-generated workflows auto-inject cleanup routines. We’ve processed 50k+ tasks without manual code checks—their copilot wraps all external calls in try/finally blocks with resource termination. Test it here: https://latenode.com
Create linter rules that flag common leak patterns (unclosed handles, missing dispose calls). We integrated SonarQube with custom rules—catches 80% of issues pre-deployment. Still requires tuning for AI-generated syntax variations though.
wrap ai outputs in sandboxes. docker containers with mem limits work better than code reviews