The operational reality of AI safeguards at scale
Anthropic's safeguards architecture demonstrates how legal frameworks transform into computational systems that process trillions of tokens while preventing harm in real-time.
Law students taught me what institutions are missing about AI
Working with summer interns revealed that the next generation treats AI as another developing tool, not an existential threat.
When machines think straighter than justices
Justice Kagan's surprise at Claude's constitutional analysis reveals an irony: while we fixate on AI hallucinations, we miss when machines reason more systematically than humans, modeling dispassionate legal analysis.
The fluency gap: why AI adoption creates permanent competitive advantages
Legal AI adoption isn't just about efficiency gains—it's about positioning for a market where early adopters build compounding advantages that become nearly impossible for late adopters to overcome.
The professional privilege gap in conversational AI
Altman's admission about ChatGPT's confidentiality problem exposes a fundamental design flaw: AI systems that encourage professional-level trust without professional-level legal protections.
Law schools build AI fluency through hands-on training programs
Law schools teach AI verification skills through hands-on training. Yale students build models then hunt for hallucinations. Penn gives 300 students ChatGPT access. Early movers create graduates who understand AI capabilities.
Agents are redesigning work, not just doing it faster
Companies that succeed with AI agents aren't just automating tasks—they're choosing between rebuilding workflows around agents or adapting agents to existing human patterns. The key is knowing which approach drives adoption.
Why reasoning AI demands spacious leadership
Reasoning AI promises better decisions, but the most successful implementations happen when leaders resist the urge to move fast and instead create space for teams to think deeply about what really matters.
