organization

taken together, it appears that for most domains LLMs will continue to look like a cracked intern: quick and effective in the hands of an adult but not given run of the place. most firms will not be able to adopt fully autonomous AI, not for problems of skill issue or lagging technology diffusion but rather for structural reasons seemingly endemic to current architectures.

Drawing on telemetry from over 10,000 developers across 1,255 teams, Faros’ recent landmark research report confirms:
Developers using AI are writing more code and completing more tasks
Developers using AI are parallelizing more workstreams
AI-augmented code is getting bigger and buggier, and shifting the bottleneck to review
Any correlation between AI adoption and key performance metrics evaporates at the company level

The core insight is this: AI agents don’t save you time by finishing your work. They expose how much work was always possible but never attempted. Five constraints now govern how much of that backlog any organization can actually capture: judgment, planning, coordination, evaluation, and absorption. Understanding those five constraints tells you exactly which new roles are being created and why.