Agents

Oracle's betting enterprises will accept AI agents as baseline functionality.

DeWitt's framework cuts through agent commerce hype with engineering reality—acknowledging current limitations while mapping concrete preparation steps for teams building toward programmatic customer transactions.

Microsoft's 2030 timeline for AI agents replacing SaaS is bold, but the governance implications are immediate. Success requires building accountability into agent architectures from the start.

Conversational interfaces break down when AI handles complex workflows and governance requirements. Deploying autonomous systems requires new interface patterns for transparency, control, and human oversight

Multi-agent workflows create distributed accountability that challenges existing legal frameworks designed for single AI tools rather than collaborative AI systems with emergent behaviors and shared decision-making.

Agentic AI validates itself in real time, creating audit trails that help product teams build both reliable systems and the transparency needed for legal compliance when AI decisions need explanation.

Product counsel need to become infrastructure assessors, evaluating not just model capabilities but whether entire enterprise ecosystems can handle advanced AI before deployment.

Microsoft just released their Agent Factory framework, and it's forcing a rethink of how we approach AI governance. These aren't the AI tools…