Agentic AI moves from demos to durable workflows
Tracking long-horizon agents, tool-use reliability, automated critique loops, and the evaluation gap between impressive demos and dependable systems.
Updates
Signals from the AI landscape: agentic systems, infrastructure shifts, governance pressure, security failures, and the model behavior that changes what teams can safely build.
AI agents
AI infrastructure choices become enterprise strategy
Following model serving costs, inference hardware, vertical integration, and the tradeoffs enterprises inherit when platforms control the full stack.
AI accountability pressure keeps expanding
Monitoring provenance, labeling, regulated-use boundaries, security failures, and the practical controls needed when AI systems touch real decisions.