I see a lot of discussion here about over-hyped AI, and then I see the huge AI bubble at my workplace, in news, in PR statements, etc.
Are there folks who work at companies – especially interested in those in tech – that have a reasonable handle on AI’s practical uses and its limitations?
Where I work, there’s:
- a dashboard of AI usage by team and individual, which will definitely not affect performance review in any way
- a mandate to use one AI tool last month, and this month a new one to abandon that tool and adopt a different one
- quarterly goals where almost every one has some amount of “with AI” in it
- letters from the CEO asking which teams are using AI to implement features from ticket descriptions, or (inspired by the news) use flocks of agents, asking for positives without mention of asking for negatives
- a team creating a review pipeline for AI-generated output in our product, planning to review the quality of the output… using AI
- teammates are writing code and designs and sending them for review without ensuring functionality or pruning irrelevant portions, despite a statement that everyone is responsible for reviewing AI output
Is all the resistance to overuse of AI grassroots and is the pressure for rampant adoption uniform among executives/investors? Or are some companies or verticals not drinking the koolaid?
Medical device industry here. Some of our software and electrical engineers are using Claude as a sounding board for ideas, or as a starting point to find possible paths forward when they get stuck with a hard problem. Nobody trusts the model to give an accurate answer. Nobody is being encouraged to use AI models. At the end of the day, all work committed to a project is done by real humans with the normal review processes.
Management is cautiously looking at potential uses for AI in our products, but there is a healthy dose of skepticism all around. If your machine is displaying diagnostic data to a doctor there cannot be any question as to whether the machine is hallucinating.
Honestly, this is probably the best use case for LLM’s.
Tom Scott did something recent 2-3 years ago where he fed a bunch of his video titles into an LLM and had it come up 100 new names with a similar style. Most of the output sucked, a handful he had already done, and a few more sounded plausible but didn’t exist. But he got 8-10 that he could have turned into actual videos (doing all the work himself) and even did so for a couple.
The hallucination of AI can be used to help a human artist or programmer, designer, scientist, etc.) make a new connection they couldn’t before, and they can then use that new connection to implement their new idea. But LLM’s generally suck for anything more than that, and over-reliance on them slowly erodes people’s ability to think and create over time
My company is approaching AI like it’s been approaching anything for the past 40 years: with extreme caution. It’s coming alright, but the engineers are carefully evaluating it for coding, and it certainly isn’t being rolled out recklessly.
I’m one of several die-hards who flat-out refuse to use it - not so much because it’s AI, but because it’s provided by an American company - and my choice is respected. Our CEO sees old-timers like me as the fallback is AI ends up shitting the company’s bed.
Have you checked if
MinstrelMistral can generate code? When I’m back at keyboard I’m going to see if it has, an intellij plug in.Edit: Yes
I run a tech company that doesn’t use any AI:
https://sciactive.com/human-contribution-policy/
We make an email service, and we have a hard stance against any AI in our product:
Work in a big multi national company. not a software company, but I’m on an engineering team.
Leadership makes a lot of noises about AI.
The engineers can’t even use git competently. I’ve suggested quietly maybe we should focus on learning software fundamentals instead of chasing dreams but no one here listens to me.
Not in tech, but LLMs have been great for my safety and compliance consulting business. I can honestly say LLMs have made me thousands of euros.
Before LLMs, I would spend quite a bit of my regular workday on creating safety plans and coming up with systems to improve conditions and ensure compliance.
Now, with the power of LLMs, management can generate those plans themselves. So instead of me spending my normal workday on it, I get to bill my emergency rate when the hallucinated slop gets rejected and they need something actually legal at the last minute.
urge to downvote rising… rising…
…calm
AI slop clean up is the new highest paying job.
The one I work at went “all in” about a month ago. I started noticing a dramatic increase in garbage/nonsensical code at the end of last week. I didn’t make the connection between the two until Tuesday.
I’ve got a manager that usually listens and they asked me to try it and take notes because they know I’ll tell them the truth. … I’ve got a lot of examples prepped for our next meeting.
The hard part is definitively blaming LLMs because I don’t have time to track down every single commit and analyze it for LLM usage but there’s 100% a correlation.
Yeah, I wish git blame could highlight the lines written by Claude/Codex. Usually when I ask my colleagues ‘so did you use AI much for this one’ they will say yes. But it makes code review that much harder, especially when they then take my PR comments and feed them to the LLM, so I’m coding by playing telephone with a bot.
