It has become impossible to tell managers mesmerised by artificial intelligence that the tools are not, in fact, helpful. So employees just play along with the fiction to keep their jobs, writes our tech columnist
OK, but the point still stands if you allow that: It has become impossible to tell managers mesmerised by artificial intelligence that the tools are often not, in fact, helpful.
Sure, although I would phrase it I think a bit more pointedly: “it has become impossible to tell managers mesmerized by artificial intelligence that the tools are not, in fact, capable of what they imagine they are capable of.”
This points, rightly, at it being a failure on the part of the managers - not artificial intelligence. And God knows that’s spot fucking on.
Nothing is helpful until you need help. The fact that you think AI is helpful for you don’t have to force me to use AI. If you pay me $100k+ per year and you force me to use your tools to do my job why you even hired me ? To force this cult on me or to do the job ?
It’s pretty normal for an employer to dictate what tools and applications an employee uses. If you prefer gitlab but your employer requires teamcity, you don’t really get a say, right?
However, if you think you can meet your deadlines without using a code generating AI tool, then don’t use it. Ideally, if they are as useless as you imply, no one will be able to tell whether you’re using it. The conflict should only really appear if they do increase productivity, and you refuse to use them, resulting in less productivity than your peers.
Company will be able to tell if you’re using it because companies behind sota models come with monitoring. You will have meeting with hr and your manager when you will be forced to use it even if you meet quotas. They will argument it that maybe you can do more and increase your normal quota with expected ai usage increase in productivity even if you had best productivity in team without ai and your productivity stays the same. Suddenly you will be under performing because you are refusing to use ai so you will be first to fire even if you are best employee. That’s how corporations work. They are monitoring usage because it costs them money. For big corporations they pay upfront to get discounts. Company also make many trainings and meetings to encourage everyone use AI models they pay for but nobody wanted.
The conflict should only really appear if they do increase productivity, and you refuse to use them, resulting in less productivity than your peers.
While it should be easy to point out where this helps, it very much is not in reality because AI accelerates execution on ideas, but corporations nearly always suck much more at deciding which ideas to actually implement in the first place.
I predict that the longer this goes on, the more useless, untested half-features will be stuffed into software and the more bloated “fall back” implementations full of duplicated spaghetti code will exist.
If the tools don’t stick around because it’s too cost prohibitive to keep using them, we’re going to be cleaning up after the bots for a decade.
It’s been a boon for personal slopjects for me. But that’s because I could never find time for execution in the past. Now I just have the (free tier) AI slop up my ideas.
Sure, but not at this speed. The bots can churn out a mountain of non-sense that does not work faster than people can review it and the bots themselves will lie to you and say “it’s all implemented”.
For people who have clear ideas of what to implement but struggle to find the time, this is a big gift. You can work hand-in-hand with the bot and say “nope, not that, this” until it implements what you had in mind. For aimless corporations with “ideation” meetings who cannot stop coming up with terrible ideas that none of their customers want, it’ll hasten the process of them making their software worse over time.
That’s exactly what I’m seeing at my current company.
That’s a fair point, but it’s not an issue with AI; it’s an issue with corporate culture. Corporate culture can and does change, especially with advances in technology, but there will be a churn period where it’s chaotic and mistakes are made.
I agree with that as well. A lot of the problem with my current company comes straight from the executive leadership level. I’m afraid that the culture will only change when they change (or more likely, the company will eventually just go bust).
They bought the lie that AI will replace all of software engineering, whereas I see the picture more like this:
A CEO that thinks that they’re going to develop all of the software, even with Claude code, is nuts. They simply do not have the necessary skill set to run a software project even if 100% of the hands-on programming is done by AI. They are not going to be sitting there telling a machine to move things around on a web app. They are going to believe the bot when it says that “it is implemented”.
In this, I think we more-or-less agree; I just don’t see that as a fault with AI, nor as a reason not to continue to develop/adopt AI.
And maybe your point is what Doctorow was trying to make all along, but he pushed too far in the other direction? Even now, Code Generation is a useful tool, as long as it’s used as only a tool by someone who knows what they’re doing.
I don’t need you to use you turn signals, but it’s helpful. I’m pretty sure I could come up with a multitude of situations where your first sentence is refuted without contest.
LLMs are like a dishwashers. You could wash all the dishes yourself and probably get them cleaner in less time, but it’s useful to let a machine do the work, even I though it’s mandatory inspect every single dish to make sure the machine got them clean enough and re-wash a certain percentage of them. Dishwashers are useful, but the world wouldn’t end if we didn’t have them. They also have the benefit of using less water than when do them yourself, which certainly isn’t the case with LLMs.
The other question Suresh implicitly raises is: “How can you reconcile the failure of AI in the enterprise with the individual claims of skilled technologists who insist that AI is helping them do great work?”
If you’re already experienced developer and you use it skillfully, validate produced code it can help.
If you aren’t (and unfortunately everyone thinks they are better than they actually are), it actually can do the opposite, it can help generate a lot of junk code.
Now when working in a team usually majority of people aren’t that great developers typically there might be one or two star developers. The problem is that the other people will still use AI and generate MRs. Reviewing those is extremely time consuming and no one wants to do it. It’s weird to say what’s exactly wrong with those MRs they seem to do things but they seem to do things in a more complicated way.
The thing is that no one wants to review those MRs, everyone is afraid to point AI slop, so the quality of code goes down and even the people who previously were good are getting lost in the code themselves.
Part of the problem is AI isn’t a literal thing with a fixed definition. It’s more of a marketing term that translates into “I want you to buy this thing”. So some things are considered AI that are legitimately useful and others are not and then there’s the debate if wether it’s because it really is AI or if it is and AI just sucks.
In other words, corporate leadership is starting from the premise that AI has (or will) radically change the business, and they’re working backwards from that premise to find the evidence to support this article of faith.
This quote is quite funny in this context, because it’s literally what people do with AI. Half of the frontpage of lemmy is AI. The other half is people saying AI is bad with no realization of the irony, because they don’t see good AI. It’s like CGI. Everybody hates CGI, except they don’t. CGI is everywhere. They just hate bad CGI.
What is AI? Explain as if i just woke up from a coma. We don’t have flying cars, we have dumpster deloreans, but everyone is talking about AI. What is it?
Like most things, meaning depends on context. In the most common context of “news about AI” we’re talking about generative AI: image/video generators, LLMs, and to a lesser degree coding assistants. If you want to know more about what these technologies share in common, look up what a “perceptron” is and how it works.
More generally AI could mean anything from a neural network based approach to problem solving, to a completely deterministic, hand coded heuristic. A pure decision tree could be AI in the case of video game NPCs, for example.
I’d say it’s more like a way to describe a certain kind of algorithm. One that adapts in some way to inputs that defy simple classification. Ultimately you’re probably just safe to replace AI in modern news and internet discussion with LLM or CNN.
AI is any compute model performing complex enough reasoning that the output does not always resemble the input. They are by definition non deterministic and the same ask can provide different outputs without being influenced by other inputs.
Since that was a lazy question I decided to be lazy and just copy paste it into Gemini. Enjoy! I have no idea what the point of this is!
Artificial Intelligence isn’t a single technology; it has been a massive umbrella term since the 1950s. Broadly, it means creating computer systems capable of performing tasks that typically require human intelligence.
If LLMs are just one tiny branch on the tree, here is what the rest of the tree looks like:
Machine Learning (ML): This is the engine driving most modern AI. Instead of a human programmer writing strict "if/then" rules, we feed the computer massive amounts of data and let it figure out the rules itself. This is what powers your Netflix recommendations, credit card fraud detection, and the algorithm deciding what you see on social media.
Computer Vision: Teaching computers to "see" and interpret the visual world. This is how self-driving cars identify stop signs versus pedestrians, how your phone unlocks when it sees your face, and how medical software spots anomalies in X-rays faster than human doctors.
Robotics: The physical application of AI. This isn't just mechanical engineering; it is the software that allows a machine to navigate the unpredictable, physical world. This covers everything from the Roomba vacuuming your floor to automated factory arms and those creepy, dog-like robots from Boston Dynamics.
Natural Language Processing (NLP): This is the branch focused on understanding and generating human language. LLMs live here, but so do older, simpler technologies like spellcheck, Google Translate, and the early versions of Siri or Alexa.
Expert Systems & Rule-Based AI: This is the older, "classic" AI. It relies on a massive database of human knowledge programmed as logical rules. When the IBM computer Deep Blue beat the world chess champion in 1997, it wasn't using an LLM; it was using raw computational power to calculate millions of possible moves and their outcomes based on strict rules.
Predictive Analytics & Optimization: The invisible math running the modern world. This is AI used by logistics companies to find the absolute most efficient routes for delivery trucks, or by hedge funds to execute high-frequency stock trades based on market micro-fluctuations.
I asked the question to demonstrate something. You didn’t want to participle in the discussion and that’s fine, but that doesn’t mean the question is “lazy”
It depends on the tool to be honest. If it’s Claude code and you’re a programmer, sure that’s helpful. But often it’s an “agentic workflow engine” that’s been developed in house that’s complete garbage, or a chatbot that doesn’t know anything telling you that it can’t answer your question that was put together by your company. These custom tools are almost always not helpful.
Doctorow knows this as well, he writes about this crap constantly and has broken it down by user type in other pieces.
They have uses in certain circumstances. They also have lots of negative aspects (that are broader and more systematic, as far as I can see). I think in a net-benefit sense they are not, in fact, helpful (to an organisation, or to a society).
This is stupid. The tools are helpful. Overhyped? Sure. But to pretend they are in no way helpful is just wrong.
OK, but the point still stands if you allow that: It has become impossible to tell managers mesmerised by artificial intelligence that the tools are often not, in fact, helpful.
Sure, although I would phrase it I think a bit more pointedly: “it has become impossible to tell managers mesmerized by artificial intelligence that the tools are not, in fact, capable of what they imagine they are capable of.”
This points, rightly, at it being a failure on the part of the managers - not artificial intelligence. And God knows that’s spot fucking on.
Nothing is helpful until you need help. The fact that you think AI is helpful for you don’t have to force me to use AI. If you pay me $100k+ per year and you force me to use your tools to do my job why you even hired me ? To force this cult on me or to do the job ?
It’s pretty normal for an employer to dictate what tools and applications an employee uses. If you prefer gitlab but your employer requires teamcity, you don’t really get a say, right?
However, if you think you can meet your deadlines without using a code generating AI tool, then don’t use it. Ideally, if they are as useless as you imply, no one will be able to tell whether you’re using it. The conflict should only really appear if they do increase productivity, and you refuse to use them, resulting in less productivity than your peers.
Company will be able to tell if you’re using it because companies behind sota models come with monitoring. You will have meeting with hr and your manager when you will be forced to use it even if you meet quotas. They will argument it that maybe you can do more and increase your normal quota with expected ai usage increase in productivity even if you had best productivity in team without ai and your productivity stays the same. Suddenly you will be under performing because you are refusing to use ai so you will be first to fire even if you are best employee. That’s how corporations work. They are monitoring usage because it costs them money. For big corporations they pay upfront to get discounts. Company also make many trainings and meetings to encourage everyone use AI models they pay for but nobody wanted.
While it should be easy to point out where this helps, it very much is not in reality because AI accelerates execution on ideas, but corporations nearly always suck much more at deciding which ideas to actually implement in the first place.
I predict that the longer this goes on, the more useless, untested half-features will be stuffed into software and the more bloated “fall back” implementations full of duplicated spaghetti code will exist.
If the tools don’t stick around because it’s too cost prohibitive to keep using them, we’re going to be cleaning up after the bots for a decade.
It’s been a boon for personal slopjects for me. But that’s because I could never find time for execution in the past. Now I just have the (free tier) AI slop up my ideas.
Which happened without AI, too.
Remember that AI, in whatever form or field, only has to be better than the average human in the field, to be useful to a company project.
Sure, but not at this speed. The bots can churn out a mountain of non-sense that does not work faster than people can review it and the bots themselves will lie to you and say “it’s all implemented”.
For people who have clear ideas of what to implement but struggle to find the time, this is a big gift. You can work hand-in-hand with the bot and say “nope, not that, this” until it implements what you had in mind. For aimless corporations with “ideation” meetings who cannot stop coming up with terrible ideas that none of their customers want, it’ll hasten the process of them making their software worse over time.
That’s exactly what I’m seeing at my current company.
That’s a fair point, but it’s not an issue with AI; it’s an issue with corporate culture. Corporate culture can and does change, especially with advances in technology, but there will be a churn period where it’s chaotic and mistakes are made.
I agree with that as well. A lot of the problem with my current company comes straight from the executive leadership level. I’m afraid that the culture will only change when they change (or more likely, the company will eventually just go bust).
They bought the lie that AI will replace all of software engineering, whereas I see the picture more like this:
https://www.normaltech.ai/p/why-ai-hasnt-replaced-software-engineers
A CEO that thinks that they’re going to develop all of the software, even with Claude code, is nuts. They simply do not have the necessary skill set to run a software project even if 100% of the hands-on programming is done by AI. They are not going to be sitting there telling a machine to move things around on a web app. They are going to believe the bot when it says that “it is implemented”.
In this, I think we more-or-less agree; I just don’t see that as a fault with AI, nor as a reason not to continue to develop/adopt AI.
And maybe your point is what Doctorow was trying to make all along, but he pushed too far in the other direction? Even now, Code Generation is a useful tool, as long as it’s used as only a tool by someone who knows what they’re doing.
Honestly if they hired someone who refuses to use AI in 2026 it’s on them.
I don’t need you to use you turn signals, but it’s helpful. I’m pretty sure I could come up with a multitude of situations where your first sentence is refuted without contest.
LLMs are like a dishwashers. You could wash all the dishes yourself and probably get them cleaner in less time, but it’s useful to let a machine do the work, even I though it’s mandatory inspect every single dish to make sure the machine got them clean enough and re-wash a certain percentage of them. Dishwashers are useful, but the world wouldn’t end if we didn’t have them. They also have the benefit of using less water than when do them yourself, which certainly isn’t the case with LLMs.
The later section addresses this
It is a double edged sword.
If you’re already experienced developer and you use it skillfully, validate produced code it can help.
If you aren’t (and unfortunately everyone thinks they are better than they actually are), it actually can do the opposite, it can help generate a lot of junk code.
Now when working in a team usually majority of people aren’t that great developers typically there might be one or two star developers. The problem is that the other people will still use AI and generate MRs. Reviewing those is extremely time consuming and no one wants to do it. It’s weird to say what’s exactly wrong with those MRs they seem to do things but they seem to do things in a more complicated way.
The thing is that no one wants to review those MRs, everyone is afraid to point AI slop, so the quality of code goes down and even the people who previously were good are getting lost in the code themselves.
Part of the problem is AI isn’t a literal thing with a fixed definition. It’s more of a marketing term that translates into “I want you to buy this thing”. So some things are considered AI that are legitimately useful and others are not and then there’s the debate if wether it’s because it really is AI or if it is and AI just sucks.
This quote is quite funny in this context, because it’s literally what people do with AI. Half of the frontpage of lemmy is AI. The other half is people saying AI is bad with no realization of the irony, because they don’t see good AI. It’s like CGI. Everybody hates CGI, except they don’t. CGI is everywhere. They just hate bad CGI.
What is AI? Explain as if i just woke up from a coma. We don’t have flying cars, we have dumpster deloreans, but everyone is talking about AI. What is it?
AI is a vague term used colloquially to describe a variety of dissimilar and unrelated technologies each carrying a unique mixture of pros and cons.
So it doesn’t actually mean anything.
Like most things, meaning depends on context. In the most common context of “news about AI” we’re talking about generative AI: image/video generators, LLMs, and to a lesser degree coding assistants. If you want to know more about what these technologies share in common, look up what a “perceptron” is and how it works.
More generally AI could mean anything from a neural network based approach to problem solving, to a completely deterministic, hand coded heuristic. A pure decision tree could be AI in the case of video game NPCs, for example.
So it’s a new synonym for algorithm.
Not quite. Algorithms are definite, you get the same guaranteed output if you give the same input every time. AI is generally more fuzzy logic.
I’d say it’s more like a way to describe a certain kind of algorithm. One that adapts in some way to inputs that defy simple classification. Ultimately you’re probably just safe to replace AI in modern news and internet discussion with LLM or CNN.
AI is any compute model performing complex enough reasoning that the output does not always resemble the input. They are by definition non deterministic and the same ask can provide different outputs without being influenced by other inputs.
So its a lottery
No
I put in a 5 and get a triangle. I put in the same 5 again and get a transvestite. This is intended behavior.
That system isn’t a magic box. It’s a bag of variables linked together by statistics and what’s basically automated guessing.
Since that was a lazy question I decided to be lazy and just copy paste it into Gemini. Enjoy! I have no idea what the point of this is!
Artificial Intelligence isn’t a single technology; it has been a massive umbrella term since the 1950s. Broadly, it means creating computer systems capable of performing tasks that typically require human intelligence.
If LLMs are just one tiny branch on the tree, here is what the rest of the tree looks like:
I asked the question to demonstrate something. You didn’t want to participle in the discussion and that’s fine, but that doesn’t mean the question is “lazy”
I didn’t provide you with an answer to your question?
This response is irrelevent to my post.
It depends on the tool to be honest. If it’s Claude code and you’re a programmer, sure that’s helpful. But often it’s an “agentic workflow engine” that’s been developed in house that’s complete garbage, or a chatbot that doesn’t know anything telling you that it can’t answer your question that was put together by your company. These custom tools are almost always not helpful.
Doctorow knows this as well, he writes about this crap constantly and has broken it down by user type in other pieces.
They have uses in certain circumstances. They also have lots of negative aspects (that are broader and more systematic, as far as I can see). I think in a net-benefit sense they are not, in fact, helpful (to an organisation, or to a society).