I’ve been wondering the same, so hard. I feel like at this point I’d like to see a comparative study of the job of people that see it VS the job of people that don’t.

I remember some twenty years ago when I finished college I had this internship that turned into a summer job afterwards. Prestigious organization in fancy skyscraper. Our teachers were a bit nervous about it since it was the first time the got the org to accept interns and made it clear we should be extremely grateful and well behaved, or else.

Godfuck the job was boring. This massive tentacular place had a million subdivisions doing roughly the same thing in a different region but somehow each had enough torque to get to have their own little website with a different interface design and a handful of different fields. Our job was to rewrite backends from [boring old basic MS tech] to [shiny new overengineered MS tech]. Dozens and dozens of roughly alike but not entirely identical backends. After months of work there was still at least as much to do as had been done. The architects in place had no desire for harmonization or reuse. They knew be heart the features the seemed to rewrite periodically in a fancier ways.

Sometimes I wonder how many places feel like that, how many programmers embrace the repetitive churn, oblivious to the affront against the very core of software this represents. If these are the ones that see it.

I worked on desloppifying a codebase, but had to do with AI. This was a job. Spec driven development didn't work on that project but targeted refactors did.

Setting up a project to work with AI is not easy, IMO. You need rules, and skills, and commands, and whatever else they call it in order to be productive, otherwise you spend your time fighting with the the AI.

You're right to question 10x and 100x productivity gains. Those only exist if you're not willing to look at the code. I've had people tell me "code isn't important", then run into issues, and ask me to help out. The code was indeed important. Therefore, how you use AI is the important part here.

Using AI to write the entire codebase is cute. It might get your project to MVP very quickly and then you have to hire somebody who knows what they're doing to fix all the stuff in it. I would recommend using it in a targeted manner:

• ideation
• code analysis
• targeted refactors
• boilerplate
• mini features
• bug detection

As an example, connecting an AI to an MCP like Ghidra for working with decompiled binaries is impressive. You do have to stay on your toes all the time and verify what it says, but it changes the while experience.

Once you let it loose to make bigger changes, it will inevitably fuck up while spitting out reams of code at you. Reviewing all of that is the bottleneck because it requires Actual Intelligence. Using another Artificial I to review what the previous AI did is only useful for bug detection or exploit detection (in my experience). For architectural mistakes or clean code (whatever your perception of that is) has only lead to pain for me.

So yeah, not 100x, not 10x, but maybe 1.1-1.5x. More if you're careless or don't know what you're doing and Just Want It To Work ™️.