For most of 2024, we believed the same thing everyone else did: AI can’t write quality code. It’s a nice autocomplete, maybe useful for boilerplate, but real production code? That requires human understanding.
Then we started experimenting. What we discovered fundamentally changed how we work.
The Turning Point
The turning point came when we stopped treating AI as a code generator and started treating it as a junior developer who never sleeps, never forgets context, and can be given extremely detailed instructions.
The key insight: AI quality is directly proportional to instruction quality. Vague prompts produce vague code. Precise specs produce precise implementations.
Restructuring for Agents
We restructured our entire workflow around this insight:
Documentation First: Every feature starts with a detailed spec. Not because of process religion, but because agents work better with clear instructions.
Atomic Tasks: We break work into small, well-defined chunks. Agents excel at bounded problems with clear success criteria.
Continuous Validation: Automated tests run constantly. Agents write tests for their own code, and we review both.
Human Oversight: Seniors review agent output for architectural consistency and edge cases. This is where human judgment remains essential.
The Results
The results exceeded our expectations. Delivery timelines compressed. Bug rates dropped. Developer satisfaction increased—because they were solving interesting problems instead of writing boilerplate.
This isn’t the future. It’s now. And teams that don’t adapt will find themselves unable to compete with those who have.