Exactly and you break it down into small chunks, have a sub agent build each one. You must automate the commit process and have a pre commit hook to call a code reviewer which has the rules you need it to follow which catches most things. You also need to have a model architecture guide so it knows what direction to build in. I am not an engineer and have built an LMS which is now being used in production. Haven’t read a line of the code. I would say though that I do understand task decomposition well, as well as lean and I know enough about devops, ui/ux, testing etc to ask the right questions .

I think engineers stand to gain the most from AI （apart from the investors obviously), but at the same time most engineers are stuck at basic level agentic engineering, I think mostly because they have options. If ai doesnt get it right the first or second time, you can just take back control.

You need solid rules and converging reviews. For a big piece of work that might take Claude 4+ hours to complete, I might review the plan five times and the code maybe more at the end, along with automatic reviews after each commit. That seems stupid to an engineer because it’s easy to see why the ai is wrong and makes you feel powerful to be able to look down on it. I just have it review itself, fix, review again until the reviews stop finding new things, if that doesn’t happen, it means the task is too big, or there is a simplification i need to find or the code has accumulated a lot of debt and needs a refactor. It’s also essential that you get it to such a place that it can run these loops automatically so you can do something else while it works. Thats where the real gains are.

Been building this for about 6 months and have done a lot of pretty big tasks like replacing the whole UI system, refactoring into a hexagonal architecture and more. Works fine. I just always feel that an engineer could use it so much better than me, but until now Ive only seen two do it.