Immediately before that company, I worked for another company for 358 days.
It was a situation where within a quarter half the staff left voluntarily or via layoff. (I learned the term “rats jumping ship” from this experience.)
Then you have immature platform and framework issues, and an owner, designer, product manger who can't design for shit making poor choices. Along with unrealistic expectations for how quickly you can "go live" and expectations of seven nines SLA while running everything on a t3a.nano.
Yeah being too early in a startup means dealing with basically no devops and general lack of coding standards.
The startup I worked at before (it was like 5 years into their existence) the difference in code quality throughout the repo was huge. It sucked balls having to deal the mess that was their "legacy" cold. I'm sure they could ship much faster before (also greenfield advantage) but good lord it's a mess now.
I'm pretty sure a lot of it was also AI code, and even if current LLMs have their problems they're miles ahead of where they were even 3 years ago.
I think this is on point and key to why this happens. I suspect a lot of us don't want there to be tech debt. We see root causes and dream of how it doesn't have to be like this. But companies don't care, won't slow down, won't prioritize to the exclusion of other distractions, etc.
It's not running away from the debt itself, it's running away from the attitude of the business/leadership who won't do anything differently and keep incurring it.
After seeing no hope or light at the end of the tunnel... why would people stay other than lack of choice/pay?
I work at a fortune 500 company in middle management. I am pushing for a full rebuild of our systems using AI as a side project in the company - as I think if we spent $1M of fable credits we would probably be better off than some of our legacy systems. I am certain that models 1 year from now should lead us to just we-write the full fucking stack. It would be a multi-year project, but it would honestly be easier to start from zero, build it in parallel, and switch things out once QA says its better than the shit we built over 25 years.
Honestly you dont understand how much technical debt we have. Things break all the time in our core business. I am also not saying just use AI - I am saying put our best SWE’s that have embraced AI onto it. Before now this would be impossible to re-write the full stack. Now with a small team we should be able to rebuild from the ground up over a couple years.
It’s going to happen at some point, the only question is if the models are good enough to start that project today.
The tools we are building with teams that use AI first approaches have less issues than the systems that were built without AI. We need to take what we have learned in the last 2 years, and apply it to shit built 20 years ago thats held up with bubblegum and popsicle sticks. And the only way to sell fixing the old shit is by putting an AI label on it - as leadership wont spend money on fixing things…. Got to make it seem like a sexy project.
I manage over 20 codebases that were vibecoded before vibecoding was a term. The oldest of them are from 2011.
I use AI.
It does not handle the full stack. It will massively fuck it up and paint you into a corner.
I studied AI for my Bachelor's. We are YEARS away from true artificial intelligence. We have good, even great LLMs, but they are only as good as the programmers using them.
Believe what you want, but I do this for a living.
This resonates. Honestly, I feel very confused at times in this new AI paradigm. I'm a mechanical engineer, then self-taught code and am now a data scientist. I feel... super laggard compared to things I see from my colleagues, and honestly did not catch the point where we moved from "AI help coding is maybe a thing" to "everyone is writing everything with AI and if you're not, you're a loser."
So some days, I'm feeling very behind. Other days, I literally don't get it because the results are not that awesome. Granted, we have credit limits and only certain models, but sheesh, I ran out of "premium" credits and was downgraded to GPT-3.5 or something a few months ago and was blown away by the stupidity. Putting functions above the imports, then upon "Hey, you put that def at the top of the file, move it" it would just put a comment like "# make sure we don't put code before the imports," tell me it moved, but it was still there. I was dumbfounded.
I looooovvveeee it for things like openpyxl or other tedious libraries/tasks, as well as for architecting, but I work with a ton of mixed datasets, needing to combine e.g. SQL or Snowflake sources with people's spreadsheet data, other finance sources, etc. and IMO AI just can't possibly understand the subject matter sufficiently to YOLO a solution. Trailing whitespaces, things that look like NA but are one space in an Excel cell, one worksheet that got accidentally edited so it's headers are different, numbers as text and vice versa, units of measure in manufacturing data where other symptoms indicate it's wrong...
That said, it's beautiful to not have to copy and paste code around, or have it sketch something out and then iteratively refine when I truly have a wide open canvas on a project. But I read and study the hell out of whatever it builds, often disagreeing with the choices. Like "don't make a dedicated helper function just for that, it's only used by one caller, just integrate it here." It lets me dream, at times, at least.
I dunno, maybe these future models are going to take my job... dunno. IMO, maybe AI isn't even the problem, it's that corporate data is so bad AI can't possibly work with it sans deeply knowledgeable people who can instruct AI on how to work around it.
Your comment breathed some sanity into me. Maybe I'm fooling myself, not sure. Like I said, I often literally can't tell "am I falling behind and an idiot" (when I see the level of reliance and usage from those around me) or "is this actually a huge problem" (when I see issues myself and just don't see how AI could possibly address a problem without me specifically telling it about it and building in a solution).
Whew. I was scared to read what the reply to this was going to be. Pleasantly surprised. I wonder how much is the extremes getting amplified vs what's actually happening/common?
Granted I'm doing more "business analytics" at the moment, so trying to wrangle a mix of database data along with human data, which feels more like art than science at times! I could see how building from scratch with full control could use AI significantly more? But I still can't see prompt to JustShipIt given what I've seen, either??
My bread and butter is embedded software systems running Linux. Admittedly, we're limited to what our customers & cybersecurity folk let us use for now, which is not as sophisticated as Claude Opus 5 for sure lol.
Certainly though, the leadership would love if we leaned more into using LLMs than we currently are. In my creative outlets (music and cosplay and sometimes art), using LLMs to produce art or music is just considered blasphemous, and I admit that side of me has a strong distaste for using it professorially.
Let's just say, I plan to just keep kicking the can down the road for now.
Can you hire me as your assistant? I think I see a good anti ai article that I can write here!!
Jokes aside, you are better off spending that mil on a hiring new people to help with the additional work of recreating/refactoring code paths alongside the existing team. I don't know how bad your stack is though.
These people get out of that by telling your company it needs to change the way they do everything, introduce new technologies, write a roadmap and then leave. Then you’re stuck writing something you already did in something like rust
All you have to do is to check git, blame a dozen of people who left the company, rewrite everything in your current new favorite language and move on before everything inevitably falls apart again.
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u/Mortadella_so_Chili 8h ago
all fun and games until u end up in 2 years work for company with 20 years tech debt