Moves from assess → trial and trial → adopt for Anthropic MCP, agents.md, OpenRouter, NVIDIA NeMo, Terminal Bench, GPT-5.4, reinforcement learning, and C show a shift toward orchestration layers, protocols, benchmarks, and training methods that make AI usable in real workflows.
Enterprises are moving from model experiments toward the infrastructure needed to run controllable AI workflows. Teams now need to standardize tool-to-tool communication, monitor agent behavior, and measure outputs rather than just pick the strongest model.