What Happens When Your AI Agent Goes Wrong — And How to Design for It
Developing AI agents that perform real-world tasks requires robust engineering to handle failures and prevent unintended consequences. Solutions include implementing durable execution workflows, such as those offered by Temporal, to ensure agents can resume from where they left off after crashes. Additionally, a governance layer, akin to a firewall, is crucial for intercepting and validating agent actions before they execute, thereby preventing catastrophic or irreversible operations and meeting regulatory requirements. AI
IMPACT Ensures AI agents can reliably perform complex tasks and integrate safely with real-world systems, crucial for enterprise adoption and regulatory compliance.