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> One week. Three senior engineers. $10,000. What your markup on their salaries? For the level of work you're promising, it sounds like they may be at market or below.
My barber once told me, "You don't pay me for what I cut, you pay me for what I leave behind". Now I'm bald.
> One week. Three senior engineers. $10,000. What your markup on their salaries? For the level of work you're promising, it sounds like they may be at market or below.
A salary like this is only a big compromise if you live in a very high cost of life area.
lol looks like they are using a similar methodology to how we use Claude in house. Honestly, the code we write with AI is cleaner, better documented, better factored, more maintainable, and less bugs than back in old days before code assistant agents. I think people must be just yoloing it, because it seems a lot like a holding it wrong type problem. Documentation driven development is your friend.
Previously, I would need to do the trade-off calculation. How urgently does this need to ship, and do we have time to rework this? What are the deal breakers that need to be addressed, versus what things are best practice/ideal for maintainability? How did their last code review go and do they need a small win right now?
There's no more "nit" comments tagged as nits: just things to fix. It's de-personalized in the sense that we can both at least pretend/have plausible deniability and blame the model for being dumb, as opposed to the person making mistakes. I flat out told someone that a PR was not solving the right problem earlier, and neither of us thought it was a big deal. I could give the technical guidance and suggest a path forward to "help Claude understand better".
$333/week doesn’t quite seem like enough to live on. How many of these are you planning to run concurrently?
“We use Claude Code too” I understand that it’s probably impossible to sell non-AI-assisted solutions to AI-pilled companies (even when their headaches are AI-induced), but my gut reaction to “take an AI-inflated codebase and apply AI deflation to it” is something like “that’s akin to applying two rounds of lossy transcoding; the errors don’t cancel out, they cross-multiply”.
NGL I'd argue there's a certain appeal to "use AI to prototype a feature as fast as possible and focus your engineer hours on building a comprehensive testing and fuzzing plan" followed by a "remove and review everything that can be cut without breaking the tests" cleanup pass.
Sounds like you forgot to have the agents use red/green TDD and build a robust test suite while they were shipping all of those features.
Creator here, There is a new kind of task for software engineers these days. A client calls, asks for a "small refactor," and sends you 100k lines of AI-generated spaghetti. And this is great! This is something we can work with. Any experienced engineer can look at a codebase like that and quickly see what to refactor, where a library replaces a few thousand hand-rolled lines, and what smells bad. Removing the first…
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. A common way to market to these firms is to be very easy to find when their software starts to have serious issues. [1] https://www.laputan.org/mud/
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.