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04/07/2026
18 min read
Can an AI Pentest Replace Human Pentesters?

Most agent prototypes never leave a notebook. Not because the idea is bad, but because the path to production looks long. It doesn't have to be.
Morning: package the agent
Move your prototype into a small project with a clear entry point. Define dependencies in a lockfile and pick a base image. Run it once in a Codexa sandbox to confirm it behaves exactly as it did locally.
Midday: add tools and guardrails
Connect the tools your agent needs, scope its secrets and set a timeout and budget for each task. Add a simple evaluation set of ten to twenty real examples so you can tell whether changes help or hurt.
Afternoon: deploy and observe
Deploy the agent as an endpoint with one command. Turn on tracing to see every model call and tool call, and set alerts for errors and slow runs.
Evening: invite real users
Share the endpoint with a small group, watch the traces and fix the first few rough edges. By the end of the day you have something real, measurable and ready to grow.
Packaged and reproducible
Scoped secrets and budgets
Tracing and alerts enabled
First users onboarded
Table of contents
Key takeaways
What is manual penetration testing?
What is AI pentesting?
AI vs. manual pentesting example
Authors

Lauren Volpi
Marketing
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