Mistral shifts AI development focus to enterprise partnerships
Generic models are giving way to deep integrations where AI development happens inside the enterprise
Why the difference between AI agents and agentic AI matters for product teams
I keep seeing teams conflate AI agents with agentic AI, and this distinction matters more than most realize. One's a contained service; the other's a network of intelligent actors making collective decisions.
JPMorgan's AI timeline doesn't match what's happening in entry-level hiring
Excerpt: JPMorgan predicts AI productivity gains in under seven years versus 61 for steam engines. But current entry-level job losses suggest the transition might be rougher than historical precedent indicates.
AI agents need their own authentication layer
Scalekit raised $5.5M to build authentication for AI agents. With Gartner predicting 25% of breaches by 2028 will involve compromised agents, traditional identity management needs an upgrade for autonomous workflows.
Why splitting AI agents into thinkers and doers actually works
Developer discovers splitting AI into planning and execution agents beats monolithic design for complex voice tasks like restaurant reservations.
Trust Isn't a Checkbox—It's Infrastructure: Lessons from IAPP PSR 2025
At IAPP PSR 2025, the pattern was clear: we're building AI systems faster than accountability structures.
Agentic AI accountability creates a genuine management puzzle
AI accountability isn't just about rules—it's about redesigning management for systems that move faster than human judgment.
AI training environments create new liability exposure for product teams
Anthropic's $1B RL environment budget signals training phase liability issues. When agents learn in simulated workflows, who owns the resulting IP? Product teams need training data governance before shopping for agent capabilities.
