Hana Vidal

Prepare incident logs now or lose the evidence needed to explain why your AI agent acted.

Strong performance in one environment reveals little about an agent's reliability in another.

Framework choices often matter more than the model itself when measuring coding performance.

Google's agent protocol solves discovery but leaves trust to organizations.

Secure Bedrock agents by scoping four IAM role layers to prevent autonomous privilege abuse.

Organizations are doubling agent deployments without naming who owns them.

Frontier AI agents slip past traditional safeguards designed for static software.

Hybrid control planes are replacing the managed-versus-self-hosted choice.

Why AI agents demand a governance rethink as deployment scales faster than readiness.

Invisible failures lurk beneath green dashboards in AI agents running for months without crashing.

Teams must choose which agent actions need human approval to prevent irreversible mistakes.

The credential management problem that predates AI agents and breaks most enterprises anyway.

AI agents need OAuth patterns built for continuous operation, not human approval.

Most companies deployed agents first and built governance later, leaving billions on the table.

Stopping dangerous AI agent actions before they execute, not after the damage is done.

Agents store sensitive data as a side effect.

Most enterprises talk governance but run unmonitored agents across their systems.

Agent traces reveal failures that infrastructure metrics miss, forcing new pipeline architecture.