That’s exaclty what usually happens when you lead a group of developers, not all can be authonomous geniuses, that’s why proper directions are the key. As you said we have an idiot (sometimes I see some Asperger-related behaviour) but that is a very efficient idiot that strictly follows your directions. And as a bonus it is incredibly fast

you are a senior developer, start to transform your view in a senior architect. With AI there’s no more need of developers. An architect ius needed, and if it haas a solid dev backround as yours projects will change view. Technology is always changing and it’s hard to stay at pace. But if you look from an higher perspective your project your experience will only help the AI to do the Job for you

The most important thing developers forget is planning. I am senior and used to delegate dev to Junior Devs. If you have not enough experience in software architecture you are missing the most important thig: You cannot start developing. You must start planning, first of all require your agent to plan the steps for the target mission. Than examine the plan produced, ask to divide int single in testable units. Most AI Vibe programmers start with develop directions. That is wrong. The longest part of the job is to prepare the Agent to perform correctly

I wrote my first service worker, for a PWA application… Since then I could never write an app without. It’s truly needed if you (as me) don’t like useless store apps, e.g. for Android. But When you make a PWA for the Desktop taht truly makes sense !

Wow this is a resource! Got several older desktop and laptops to revive! Down with the programmed obsolescence!

The problem isn’t the tool; it’s the lack of engineering foundations. Generalizing all AI-assisted development as ‘vibe coding’ is a massive oversimplification. There is a vast difference between a beginner blindly copy-pasting LLM output into a codebase they don’t understand, and a senior architect using LLMs as a high-powered assistant to speed up boilerplate, local schema generation, or parsing scripts. When you already know exactly how the underlying system operates, how memory is managed, and how to design clean software architectures, the LLM is just a productivity multiplier. You still design the data flow, audit the tool-use sandboxes, and review every single line of code. It doesn’t replace thinking; it replaces tedious typing.