Addy Osmani

And so generating code is not necessarily the part that you need to worry about the most. Given enough context, agents can write the implementation and run the tests and inspect failure and revise code for us. We need to get to a place where we feel like there is enough of human taste encoded in the environment that we can trust what is being built, so that our human attention can be focused on the places where it’s needed most.

Comprehension debt is the growing gap between how much code exists in your system and how much of it any human being genuinely understands.

An agent optimizing for passing tests will find ways to pass them. If the tests were written after the implementation, they are likely testing what the implementation happens to do rather than what it should do.

You cannot write a spec that survives that environment unless you deeply understand the architecture, the integration boundaries, the edge cases, the failure modes, and the invariants that must never break. The spec is not a prompt anymore. The spec is the product thinking made explicit.

The infrastructure that needs to exist to support this model at scale includes better automated regression detection, artifact-level validation that goes beyond diffing changed lines, reliable and fast environment provisioning, and guardrails that hold up under parallel workloads.

If you cannot articulate what success looks like in a way that can be evaluated, no amount of autonomous execution will produce it. Agents cannot clarify requirements they are never given. They will fill the gaps with assumptions, and those assumptions compound.