3 articles
Coding agents are increasing the volume of plausible software faster than organizations can safely absorb it. Engineering advantage will belong to teams that redesign specifications, tests, and review around machine-scale output.
AI agents fail across trajectories, not isolated answers. Teams that evaluate only the final output are measuring the least informative part of the system.
Agent benchmarks can tell you whether a system cleared an obstacle course. They cannot tell you whether it will behave sensibly inside your company—unless evaluation becomes part of the product’s architecture.