Hooked on AI
Harvey's new alliance program with Stanford, UCLA, NYU, Michigan, and Notre Dame
AI agents learn to remember what works
New research gives AI agents procedural memory that learns from failures and transfers between tasks. Early results show higher success rates with lower token costs—potentially solving the economics that have held back agent adoption.
Legal tech fails because we treat mindset shifts like software updates
Legal tech adoption isn't a procurement challenge—it's a mindset transformation disguised as a software purchase.
Why “Human in the Loop” Still Matters in Legal AI
On the In-House podcast, I shared why AI won’t erase lawyers — but it will change every role inside the legal function. Tools may act like lawyers, yet judgment and oversight remain squarely human.
AI agents work when they fit your process, not replace it
Block and GSK show successful AI agents adapt to existing workflows rather than forcing teams to rebuild around technology. The key is making AI feel invisible while amplifying human expertise.
Why RAG Should Be the Exception, Not the Default
RAG isn't broken—it's that we treated it as the default when it should have been the exception.
Stop treating agentic AI data architecture as an engineering problem
Your data architecture is your governance architecture—build accordingly.
YouTube forces the AI content conversation platforms have been dodging
YouTube's July 15 Partner Program update targets AI-generated filler while protecting legitimate creators—creating a template that other platforms facing similar content quality pressures will likely follow.
