Our outcome is also AI-generated (or AI-assisted) code. It is not possible to rewrite 100k loc in a week. Where our stills are is refactoring at scale with help of agents. Basically, software engineer knows better what prompt to put, and when to redo the process or go different path.

> I don’t think this is anything new, really: Businesses have been running software that we’d call a “big ball of mud” [1] forever.

Well but something really is something totally new. Github went from x commits per year in 2025 (when AI-slop was already being pushed to Github) to the same number of commits in four weeks in 2026. 2025 compared to 2024 was already something like 15x.

It's never happened in the history of computing that so much new code was produced so quickly.

My bet is we'll see much more of this. And these aren't going to be 100% AI-pilled companies solving these issues but companies like the one in TFA: experienced devs using the help of LLMs to fix slop.

My other bet: slop shall outlive COBOL and dwarf COBOL's legacy big times.

We don't target software developers. Most of the time, they know their craft. We target those who don't have experience and diging into how serwer should be implemented, or best composition of a domain model is not what they would like to sepend hours doing.

The typical client is a 40 years old ex-CTO, that had idea, verified it with Claude Code and got to the point, where the repo is too big. Maybe even rewrote it all from zero, once or twice, but end-up with the same outcome after adding more features.

He can either hire a developer to work on the codebase and refactor it or hire 3party company.

Sometimes the requirement is a security review. And you pay much less if you downsize the repo before handig it over.

Those who would wouldn't have mountains of unmaintainable code generated for them.

No shame in using Fable to help with the grammar and style of text. English is not my native language and while I can use it quite well, LLMs are much better in forming my thoughs into something simple, that sounds great.

My writing workflow is: (1) write what I want to have on the page. (2) /grill-me it should be sound and logical and easy to read. (3) Manually review the text, replace by hand what I don't like.

I think it is deliberately written to be LLM slop so the folks buying their services will be comforted.

Some people like AI generated comfort-slop nowadays. They feel uncomfortable when they run into individualistic human language.

If you have even the remotest mental slop filter, I assume you are not really part of their target market.

https://dictionary.cambridge.org/us/dictionary/english/disti...

"Fulfil" is the same way

fixed

parent commenter may not be american

Initial AI scan can list most of system usecases. Then we review it with a client and agree on what must stay. We can propse better solutions at this stage. If we remove the code, then we can also remove its unit tests. For intergation, repo-wide tests, we treat it as documentation/requirements that must work on the other side.

Human to human interaction is the tool we use the most :)

With a twist that you also have to use LLM for the job to finish it in time.

I owe the first decade of my career to shitty outsourced code.

I worked with such an "enterprise code" in the past. LLM code is a bit different. For example you don't see code repetition in the same file very often. I'd say it's a next level of slop. Slop at scale!

Our profession is keep changing. A few years from now, future developers will look at us and say: "2026, what a wild, wild west it was".