Why legal tech adoption should work like a kitchen apprenticeship
And for everyone involved, meaningful change in legal operations happens through evolution, not revolution.
The organizational move that made AI safety a competitive weapon
Anthropic's decision to place red team work under policy rather than engineering reveals how organizational structure can turn safety research into both technical protection and regulatory positioning.
Switzerland proves responsible AI development works
Compliance as a feature, not an afterthought: What Switzerland's Apertus model means for AI procurement
Why the Anthropic-Humanloop deal signals a shift in enterprise AI competition
Anthropic's Humanloop acquisition shows enterprise AI competition has moved beyond models to specialized talent who can build trust into AI systems.
Anthropic's safeguards framework shows embedded governance in action
Anthropic's safeguards architecture shows how legal frameworks become computational systems that process trillions of tokens while preventing harm in real-time.
Building Real Moats for AI Startups
Organizations can't engineer moats from a business plan. Defensibility emerges from solving real problems—discovering unique workflows, building proprietary datasets, and integrating so deeply into operations that switching becomes prohibitively expensive.
Your AI's cultural bias depends on the language you use
MIT researchers tested GPT and ERNIE in English and Chinese. The finding: language choice shapes the cultural assumptions in AI responses. When prompted in English, models reflected American values. In Chinese, they shifted to Chinese values.
Keep thinking: why legal AI makes judgment more valuable
Andrusko's a16z analysis reveals why "thinking partner" rhetoric clashes with billable hour economics. Since AI tools will never be flawless, traceability and workflow adaptation matter more than sophistication
