business

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.

Every SaaS business will become a harness around a model, whether or not they’ve realized it yet.

If this continues, there’s a world where 3rd party harnesses become less valuable when used with frontier lab models because the 1st party harness behavior is already baked in. And there’s no longer a fine tuning escape hatch to generalize this behavior away.

It’s going to be funny if the network effects the AI labs have been searching for end up looking just like the network effects of the SaaS era. Coding harnesses, managing the environments around the agent, look a whole lot like the SaaS platforms of old.