Code Agent Review — Page 4

AI agents now catch twice as many code bugs as traditional static analysis tools.

AI agents broke traditional CI/CD pipelines, and platforms just caught up.

Production agent reliability depends on execution plumbing, not model intelligence or prompts.

Software agents that plan, act, and iterate autonomously are reshaping how teams ship code in 2026.

Prevent duplicate charges and phantom orders by designing agent steps to safely survive retries.

Choosing the wrong memory backend forces a costly rewrite later.

Companies are deploying AI agents faster than they're building governance to control them.

Agents fail in ways incident response wasn't built to catch.

Policies decide what agents can do; guardrails enforce those decisions before harm scales.

Execution traces reveal where AI agents silently fail when traditional debugging tools can't.

Well-designed tools matter more than raw model power for building agents that work in production.