The list in the article looks like verification practices. Document intent, develop taste, find the hard stuff, etc. It assumes that when code is cheap the bottleneck shifts to knowing whether what you generated is actually right.

e2e tests can do a lot, but in my experience it's not enough. By the time the test fails you've already burned a generation cycle on an artifact that came from a flawed spec or design. I've gotten more mileage from having checks at stage boundaries (standard SDLC: plan, design, code, test). We all know the earlier you catch the mistake, the cheaper the fix.

The "implement to learn" is the same idea: you need to know enough about both where you want to go AND the path to get there to guide the agents to a proper implementation. You have contact with the world, both the users and the operational considerations that come from running software. Agents do not. We do the same thing with spikes, but now our spikes become far more sophisticated.

Code being cheap doesn't remove verification, it moves it earlier.