This is happening all over the place right now. There is a ton of greenfield happening, which further adds to the illusion of speed. Eventually you produce a big old pile of shit that even with the help of the LLM is weird to reason about, and it slows way down. Many such cases.

Yeah, enterprise code has that trope of being enterprise-y, verbose and bad. In my experience, that has always been the opposite. At the big corps/FAANGs I worked at, a single line of change can adversely impact millions of paying customers, so a lot of the verbosity and harnesses exists to dampen the failure modes. Most of the terribly written stuff has always been at startups, where devs fling nearly anything across the finish line, if it barely works the happy path.

> If it works it isn't low quality.

then the same applies to AI written code?

The code I have seen and see still, started shitty.

Let’s not romanticize it too much... A lot of enterprise systems are built by developers copying an old AbstractBeanFactoryFactory from a 2011 stack overflow thread without really understanding it :)

> But humans still need to be responsible for understanding what they're shipping

I don't necessarily disagree. That said...

Why?

I've been grappling with this myself. There is an easy/obvious answer, but I wonder how stable/permanent it is. If you feel strongly about this, are you willing to unpack your judgement?

Yeah... like we all get to start green field projects and write all the code we should understand. Many of us cut our teeth on bad legacy stuff with no proper documentation made by "engineers" long gone. At least a LLM can easily make sense of this mess.

To be fair the pitch has frequently been that Devin/Claude/Astra/whatever is some sort of superhuman bottled John Carmack that will single-handedly replace entire teams of developers.

The pressures from management and the company environment are not always a bad thing. It really depends on whether the pressures are coming from a logical business perspective or whether they are just coming from stupidity or ignorance. In a business environment, taking a long time to ship great code can mean that the company goes out of business, and then the software developers have a lot of great code and no income.

Many people were and still are simply terrible developers.

Hand those people an LLM and they don’t suddenly become competent, but they do start slinging more code.

This is off-topic, but I strongly dislike AI written documentation.

When I see AI house style my eyes glaze over. Just this morning I reviewed an RFC from a colleague that he said was a spec for a web service. The document had no introduction, no context, it described endpoints for 2 distinctly different services instead of 1, and made no effort to reconcile why there are 2. It was scattershot with details, some of them important, some completely irrelevant. It was replete with typical LLM-ism.

Basically, it was a dump of a conversation he had with an LLM. As a document to build shared knowledge, it was nearly useless. The only feedback I could provide was a polite "I do not understand what you are trying to build".

But, supposedly, another engineer is already working on implementing this spec. I assume the other engineer just cycled this "spec" into his LLM, and off the two of them went. \o/

They are trying to pull me into their project right now, I stood up some containerization infra for them. But, oh boy, do I not want to join. I looked over their codebase, by LOC the codebase is 35% comments, and a lot of the comments are contradictory, there are dependencies that are not used, there is no tooling of any kind (no type checking, no linting, no PR process), there is no auth (this code is already running in production lol -- they have public endpoints exposed that can be used to scrape/mutate internal company data). Another 30-40% of the codebase is unit tests that test trivial stuff like whether their framework's serializers and ORM work, ex: x=DB.create_x(arg=1), assert(x.arg == 1).

At the intuitive level, I do not understand people who say coding is solved... To me it seems like LLMs are a multiplier (LLMs are amazing, sci-fi level shit), but if you multiply a negative number or 0, you get something that is <=0. Making agentic coding work requires a lot of discipline & expertise.

AI documentation is practically worthless ime. I forbid it in my projects. It's almost always more useful to not have any documentation and read the code than to rely on AI docs.

Testing though I'll mostly give you