How to Review an AI Agent (Like an Expert)

Every company now has a model that talks. The real question is, who reviews what it says?

In software, code review became the backbone of quality assurance. In AI, that same discipline must evolve from inspecting logic to evaluating behavior. Unchecked code introduces bugs. Unchecked agents introduce behavioral drift: when an agent’s reasoning slowly diverges from the intended outcome.

A code review checks what was written. An agent review checks how it learns, reasons, and decides.

When teams skip structured agent reviews, they lose visibility into critical risks such as:

• Context misalignment
• Broken feedback loops
• Unchecked reasoning paths
• Missing safety boundaries

This is how agents that look perfect in testing quietly fail in production. And once trust is lost, scaling stops.

A good review checks clarity, transparency, and logs. A great review asks one simple question:

Would I trust this agent to act unsupervised on a Friday evening?

That’s the new benchmark for production readiness. Mature teams don’t just fix errors. They study how the model learns from them. Every review becomes both an evaluation and a training loop.

Agent reviews are not about control. They are about shared understanding between humans and machines.

Without that discipline, teams rely on luck to maintain reliability. With it, they evolve from delivery-driven to trust-driven operations.

The future of AI maturity will be defined not by how fast we deploy but by how deeply we understand what we have deployed.

If your team already runs retros or sprint reviews, you’re halfway there.

Add one more layer called Agent Review Rituals:

• Sessions where teams evaluate what the agent did right or wrong
• Document learnings before retraining
• Reinforce alignment between human logic and agent reasoning

These rituals are how teams scale trust, not just automation.

Coding literacy built the software era. Agent literacy will define the AI era.

Every enterprise deploying autonomous systems will need people who can review judgment, not just code.

Reliability is not built in testing. It is built in reflection. And that reflection starts with a review.