Conversational interfaces break down when AI handles complex workflows and governance requirements. Deploying autonomous systems requires new interface patterns for transparency, control, and human oversight
Research shows 250 poisoned documents can backdoor any size language model—challenging the assumption that larger models need proportionally more malicious data. The fixed-number threshold changes how teams should think about data provenance and vendor due diligence.
Anthropic's Humanloop acquisition shows enterprise AI competition has moved beyond models to specialized talent who can build trust into AI systems.
MIT research shows how single-word changes can flip AI text classifier decisions. The testing gap affects content moderation, financial services, and medical AI systems across production environments.
"This 2023 analysis correctly predicted that AI audit requirements would create compliance theater without meaningful bias prevention, warnings that have proven increasingly relevant as agent technologies emerge."
The Machine Intelligence Research Institute's latest piece makes a blunt point: nobody controls what these systems become. Engineers discover behaviors after the fact rather than designing them upfront.
Every six months, the rules change. Old playbooks don't work anymore. The only way through is to ask better questions. Here are nine questions that matter for anyone building with AI
OpenAI's GPT-5 made "vibe coding" the new normal. When business leaders go from concept to working prototype in minutes, legal guidance needs to happen at prototype speed, not policy-document speed.
