The accuracy paradox requires attestations beyond statistical metrics
The governance of generative AI is currently anchored to a flawed assumption: that optimizing for statistical accuracy is the most effective way to mi…
Memory architecture patterns for persistent AI agents
I've written about how agents need supervision frameworks that match their autonomy level, how privacy law struggles when agents operate persisten…
The timeline compression that hit software development is here for legal work
AI generates contract provisions faster than you can review them. Creation isn't the bottleneck.
Nine trends defining AI governance in 2025
AI systems are no longer just responding to prompts—they're setting goals and executing actions.
Beyond the Broccoli: How AI Governance Fills Your Trust Reservoir
Governance without narrative is just bureaucracy
MCP Server Security: What You Need to Know
The worst case: prompt injection tricks your agent into handing over its own credentials. Attackers bypass the AI entirely and access your systems with the agent's full authority.
Five predictions for AI in 2026
AI moved from tool to actor. 2026 is when we build the accountability structures those actors require.
AI reasoning explanations fail four times in five: what to verify before shipping
For product teams, these findings establish concrete design constraints for any feature that relies on model self-reporting about internal states, reasoning processes, or decision factors.
