Moving fast with agents without losing comprehension

Addy Osmani wrote a great post last week on comprehension debt, the hidden cost of AI-generated code. The core idea: AI generates code far faster than humans can evaluate it, and that gap quietly hollows out the team's understanding of their own codebase. It resonated with me, but what struck me most is a specific asymmetry in how the industry is responding. Most guidance around working with agents optimises for agent comprehension: context files, MCP servers, documented skills, feeding in the right information so the agent can reason about your codebase. There's far less conversation about the equally important problem: making sure humans still understand the system the agent is changing. We're optimising for agent comprehension while human comprehension quietly erodes. That gap is what's made me think carefully about how I've been working, and what actually needs to be in place before you can move fast without losing the understanding that keeps a codebase healthy. The thing reviews