The productization of legal risk
AI-powered legal risk discovery transforms class action economics from reactive case finding to proactive violation scanning, making corporate compliance gaps discoverable by external parties at scale.
The governance case for splitting monolithic AI into focused agents
Microsoft's multi-agent paper shows why single AI agents break under enterprise pressure. Specialized agents with domain expertise plus central orchestration mirrors how real teams work and solves compliance nightmares.
“Your Honor, I personally did not check it. I am responsible for it not being checked.”
"Mike Lindell's lawyers managed to combine AI hallucinations with basic professional negligence into one $6,000 lesson for the rest of us."
Vanguard's 20-minute prototypes show where legal work is heading
Legal work fails quietly and expensively, sometimes years later when someone finally reads the contract language that AI generated and a non-lawyer approved.
AI Companies newest Prompt: Blocking State Legislation
As of August 21, 2025, major tech players—OpenAI, Meta, and Google—are ramping up efforts to block U.S. states from enacting AI regulations that could…
Why this research may change how you should evaluate AI vendors
Companies that can't provide concrete answers are essentially admitting they lack mature safety processes.
AI agent sprawl repeating API mistakes, delayed governance makes sense
Companies throwing AI agents at problems without oversight. 72% adoption, 75% governance concerns. Smart approach: experiment messy, add controls when agents need to coordinate with each other.
Agents will move from vision to buildable infrastructure
Agent commerce conversation heavy on vision, light on working systems. DeWitt's framework offers a practical middle path—not betting on immature technology but positioning for a customer category that will transact at scale.
