Learn · Coding agents
AI-generated code is safe to ship only after a human reviews it, the same standard you'd hold any code to. Agents write plausible code that usually works, but they can introduce security holes, miss edge cases, or use an outdated pattern, and they do it with the same confidence as when they're right.
Common risks include exposed secrets, missing input validation, insecure default settings, and dependencies with known vulnerabilities. None of these are obvious from a quick glance at code that runs. They surface in review, testing, and security scanning.
Treat agent output as a fast, competent first draft from someone who never gets tired and never double-checks themselves. The productivity gain is real. Skipping review to capture it is how the gain turns into an incident.
Updated July 2026
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Review it more carefully than human code, not less, because it looks polished even when it's wrong. Read every change, run the tests, check anything touching authentication, payments, or personal data by hand, and run a security scan. Never merge a diff you don't understand just because it passes.
You can build a working prototype or a simple app with an AI agent, even without much coding experience. Where it gets hard is everything after the demo: security, handling real users and edge cases, payments, performance, and keeping it running. Those are where inexperience shows and where costs hide.
As of 2026, coding agents still struggle with big-picture architecture, subtle bugs that only show up at scale, novel problems with no examples to learn from, and knowing when they're wrong. They're confident even when mistaken, so they need a human checking anything important.