I have a coffee cup with the writing "Do stupid thing faster with cafe". That's how I feel about myself when I use AI carelessly... The speed with which I can make a mess is astronomical!
I think it depends on what area of the world you work. We recenty had one of our plant managers build a web portal to keep track of some of our operational tech, with features you wouldn't find in standard products. I've been turning it into a container app that can actually deploy safely into our cloud infrastrcture. It's quite frankly better quality than what most external software companies have provided us with in the past.
Don't get me wrong. It's not great. It would never pass any of our policies for things that actually operate stuff on the power grid, but as an administrative tool that can live in total isolation from the vital networks. It's perfectly fine. It's also not like we would have hired the best software companies to build it otherwise. We'd hire some low-level cheap consultant house who would then likely get cheap student labour to build it. With that in mind though, the AI is much better than what the realistic alternative would be.
Money wise it's also cheaper. It's been roughly €1000 + the time it's taken us both. If I had known they were doing it, I would have rolled out the developer cowork app/skills/whateveryoucallconfigurationsthesedays to them. This would have avoided their AI building it to be depoyed on a VM rather than in our managed k8s in our Azure. It would also have written the code a little different, used UV and maybe django rather than flask. But hey. For what it is, it's like a 95% cost saving compared to buying what would've been a less maintainable and lower quality system.
It is funny that only real research on productivity gains from AI shows at best very minimal gains, but AI bros will always tell you "no no no, you have used wrong model, try a different one, there are more of them, you have to try, trust me" and call that a "research".
“I wanted to see if I can get in on this 10x magic. I decided to put my money where my mouth was and I bought $10 worth of DeepSeek credits to use with a project I was working on.“
I'm sure DeepSeek isn't the point here. You can change the name to whatever you prefer and the article still holds.
Actually, I think the author put DeepSeek on purpose to avoid the obvious ChatGPT/Claude comparison — because whatever he chose, there would be a question of why model A and not B, while the point of the article isn't about models comparison at all.
Right. Better throw money at 5 different ones and then people come and tell you that you just need MORE agents and throw MORE money at it or you're not doing it right.
I got here and... I agreed with everything up to this point.
The author makes a good point. If you don't know what you're doing, AI accelerates that. No question.
But they put a whopping... ten bucks into using DeepSeek and weren't impressed with the initial results.
I know they try to cover this with "you just aren't prompting correctly!" but if, in 2026, you aren't able to have an LLM generate decent quality code... IDK what to tell you. Good luck I guess?
Nope. That would require the people paying for the code (those requesting the projects) to see something wrong with the code. As a coder, you would look in an see a mess. As a user they'll probably see something relatively nice, with some maybe strange behavior and non ideal, but what software sin't non ideal? It does most of what we wanted, and you finished it how fast!?
There are some good points, and I ask the question of where is the ground breaking stuff myself, but severely weakened by
* stretching the timeline: the actual real programming ability appeared in LLMs in the last 6-8 months, not 3-4 years,
* using the weakest possible tool: and I bought $10 worth of DeepSeek credits that is a far cry from Claude with Fable.
Also, I know nothing about marathons but for most uses putting the app, database, and background processes on the same server is very much the right starting point. With the next steps being employing Cloudflare or similar solutions long before managing a fleet of servers.
Even as someone using AI on the regular I'm starting to hate the "You didn't actually use this exact most expensive model so your point is invalid" argument.
This is fair to say if someones last experience with AI was copy-pasting code into GPT3 chat windows years ago, but Deepseek is a more than capabale model and enough for someone to get an informed opinion about the technology.
If people have actual counter argument, use those. And if some of those counter argument are "What you say isn't possible, the neweste model can do and here are examples of that", that is fine.
But a blanket "Nuh-uh, it wasn't Model X" is not only a poor argument but also automatically invalidates any criticism when a new, better model comes out - and that can't be the basis of a good argument.
I remember being told in early 2025 that only now has "real programming ability" appeared in LLMs.
And since then there's been 3 more "now real programming ability has been made available and previous stuff was just toy examples" cycles (summer 2025, winter 2025 and spring 2026)
Looking forward to the next "everything before this was trivial and bad, here's the good stuff" moment
I tried really hard to get senior management to understand this where I work. Yes, AI is an accelerator, but that doesn't necessarily mean it's going to accelerate you in the "right" direction.
Why does it have to lead to a 10x increase in revolutionary companies?
Next to maintaining and expanding my own network of websites I 10xd writing boring CRUD applications for companies that were otherwise unable to afford it, making all their employees more productive. There's true economic value in that.
'Or else admit this is a dopamine game that makes you feel like The Universe's Most Special Programmer™ when it's really just gamified mass-scale intellectual dependency.'
AI is like a tool used by mega-corporations to change the world according to what they want. We see this with the increase in RAM prices. I don't want to pay the overprice here - AI companies owe us money. People seem still mostly in the AI hype phase, but a lot more criticism has amplified in the last months. It is only a matter of time until the hype phase is over.
If one truly believes it's not in a bubble, then borrow and leverage an unlimited amount and bet the house & your family on creating a business with infinite growth and value. Don't know how to do your own prompts? Borrow and then hire others to do it for you. If those who you hire don't know, they can hire others too.*
[* This is not financial advice. Please don't actually do this.]
You could make the converse argument, too: why don't you borrow and leverage and bet and short these AI companies, if you so vehemently think it's a bubble?
The bottom line is that markets are complicated, useful technologies are often accompanied by bubbles, investors are not always rational, and people generally try to make the best decision with the information they have available. The answer is likely somewhere in the middle, but that's a lot more boring and a lot less inflammatory.
> You could make the converse argument, too: why don't you borrow and leverage and bet and short these AI companies, if you so vehemently think it's a bubble?
Because going long and going short are very different. For successfully shorting something you need to have a pretty precise estimate of when the crash will happen. Being a comparatively short time off can cost you everything.
At least once a week I have to drop what I'm doing and race in to stop the non dev manager from merging a fully vibe coded patch which will blow up production. Claude Code has made this guy a negative 10x developer.
My guess: forcing the hands of those who do/should have access by going above their heads using escalations with soothing words like 'velocity' and 'time to market', ignoring quality or aptitude entirely.
Wouldn't be the first change control procedure to be undermined by a single lunch or organization to regret the movements.
His AI experience is $10 of DeepSeek - but I think he is right anyway in the main points.
You can most definitely ship crap much faster than you used to. It's obvious to anyone when you're shipping crap. And it seems everywhere I look people are shipping crap. Both software and writing.
The hardest part of shipping quality software is not and has never been "writing the code". The hard parts are product taste, architecture and ensuring your product actually solves the problems it should in an efficient and secure manner.
If you don't have an intuition of those, you will likely still be shipping crap. Just faster.
Yep, using AI to remove your thinking process and judgement, and just let it generate stuff as fast as possible, will definitely make you ship crap faster! If you did the same thing with a junior developer you would get the same result.
Where AI shines for me is accelerating the learning and exploration process. I can get up to speed with new tech fast. It is good at spotting issues in designs and code. It can knock out quick tests or benchmarks to support me. The quality of what I can produce with AI support is much higher than I could without it.
So it really just depends on what you use it for. If the goal is "replace humans and ship fast" that's one thing. If the goal is "explore the problem space in greater depth", it's another.
> The chatbot recommended some of the dumbest shit you could possibly do
The "I tried it and it sucked" is borderline conspiratorial at this point. There are enough talented, thoughtful developers saying there's something real here, and it is worth believing them and investing some time to understand it, even if you come out the other side and decide you don't want to use LLMs.
Use a very good model. Set up a good harness. Spend some time on your system prompts and skills. Develop your intuitions about how the model works, what it's good at, how to scope the work, and how to steer it. Recognize when it's alleviating menial work and recognize when it's making choices you really need to understand yourself. Be patient and accept that the failures are going to be very painful for a while.
Don't write it off until you've genuinely seen the upsides.
You describe my experience with Claude (except my gut feeling is that system prompts and especially skills are useless, and I've even done limited testing that agrees with that).
However, your discourse is not the usual borderline religious discourse that's used by LLM advocates. You're not extreme enough either pro or against LLMs :)
> Don't write it off until you've genuinely seen the upsides.
This is ridiculous. Basically you're saying "if you try it and find it sucks, you're wrong, keep at it until you change your mind". That isn't a tool at that point, it's a religion.
Don't get me wrong. It's not great. It would never pass any of our policies for things that actually operate stuff on the power grid, but as an administrative tool that can live in total isolation from the vital networks. It's perfectly fine. It's also not like we would have hired the best software companies to build it otherwise. We'd hire some low-level cheap consultant house who would then likely get cheap student labour to build it. With that in mind though, the AI is much better than what the realistic alternative would be.
Money wise it's also cheaper. It's been roughly €1000 + the time it's taken us both. If I had known they were doing it, I would have rolled out the developer cowork app/skills/whateveryoucallconfigurationsthesedays to them. This would have avoided their AI building it to be depoyed on a VM rather than in our managed k8s in our Azure. It would also have written the code a little different, used UV and maybe django rather than flask. But hey. For what it is, it's like a 95% cost saving compared to buying what would've been a less maintainable and lower quality system.
Why not use actual frontier models, and you know do some real research, before writing a blog post?
It is funny that only real research on productivity gains from AI shows at best very minimal gains, but AI bros will always tell you "no no no, you have used wrong model, try a different one, there are more of them, you have to try, trust me" and call that a "research".
Wow. I guess that’s the punchline!
Actually, I think the author put DeepSeek on purpose to avoid the obvious ChatGPT/Claude comparison — because whatever he chose, there would be a question of why model A and not B, while the point of the article isn't about models comparison at all.
The author makes a good point. If you don't know what you're doing, AI accelerates that. No question.
But they put a whopping... ten bucks into using DeepSeek and weren't impressed with the initial results.
I know they try to cover this with "you just aren't prompting correctly!" but if, in 2026, you aren't able to have an LLM generate decent quality code... IDK what to tell you. Good luck I guess?
Now with AI I can 10x my output and 10x my bad code!
* stretching the timeline: the actual real programming ability appeared in LLMs in the last 6-8 months, not 3-4 years,
* using the weakest possible tool: and I bought $10 worth of DeepSeek credits that is a far cry from Claude with Fable.
Also, I know nothing about marathons but for most uses putting the app, database, and background processes on the same server is very much the right starting point. With the next steps being employing Cloudflare or similar solutions long before managing a fleet of servers.
This is fair to say if someones last experience with AI was copy-pasting code into GPT3 chat windows years ago, but Deepseek is a more than capabale model and enough for someone to get an informed opinion about the technology.
If people have actual counter argument, use those. And if some of those counter argument are "What you say isn't possible, the neweste model can do and here are examples of that", that is fine.
But a blanket "Nuh-uh, it wasn't Model X" is not only a poor argument but also automatically invalidates any criticism when a new, better model comes out - and that can't be the basis of a good argument.
Or B that the ideas are there but are not get released as the code is ai slop?
And since then there's been 3 more "now real programming ability has been made available and previous stuff was just toy examples" cycles (summer 2025, winter 2025 and spring 2026)
Looking forward to the next "everything before this was trivial and bad, here's the good stuff" moment
Next to maintaining and expanding my own network of websites I 10xd writing boring CRUD applications for companies that were otherwise unable to afford it, making all their employees more productive. There's true economic value in that.
Disesdi Shoshana Cox
[* This is not financial advice. Please don't actually do this.]
The bottom line is that markets are complicated, useful technologies are often accompanied by bubbles, investors are not always rational, and people generally try to make the best decision with the information they have available. The answer is likely somewhere in the middle, but that's a lot more boring and a lot less inflammatory.
Because going long and going short are very different. For successfully shorting something you need to have a pretty precise estimate of when the crash will happen. Being a comparatively short time off can cost you everything.
Seriously, that was the lowest level of skill I saw in 30 years of development.
Now we have people who can't even do that proudly showing off PRs to widely used products.
"B-b-but I do the systems design and hard thinking".
Sure, buddy.
Wouldn't be the first change control procedure to be undermined by a single lunch or organization to regret the movements.
You can most definitely ship crap much faster than you used to. It's obvious to anyone when you're shipping crap. And it seems everywhere I look people are shipping crap. Both software and writing.
The hardest part of shipping quality software is not and has never been "writing the code". The hard parts are product taste, architecture and ensuring your product actually solves the problems it should in an efficient and secure manner.
If you don't have an intuition of those, you will likely still be shipping crap. Just faster.
Where AI shines for me is accelerating the learning and exploration process. I can get up to speed with new tech fast. It is good at spotting issues in designs and code. It can knock out quick tests or benchmarks to support me. The quality of what I can produce with AI support is much higher than I could without it.
So it really just depends on what you use it for. If the goal is "replace humans and ship fast" that's one thing. If the goal is "explore the problem space in greater depth", it's another.
you want more SaaS?
The "I tried it and it sucked" is borderline conspiratorial at this point. There are enough talented, thoughtful developers saying there's something real here, and it is worth believing them and investing some time to understand it, even if you come out the other side and decide you don't want to use LLMs.
Use a very good model. Set up a good harness. Spend some time on your system prompts and skills. Develop your intuitions about how the model works, what it's good at, how to scope the work, and how to steer it. Recognize when it's alleviating menial work and recognize when it's making choices you really need to understand yourself. Be patient and accept that the failures are going to be very painful for a while.
Don't write it off until you've genuinely seen the upsides.
However, your discourse is not the usual borderline religious discourse that's used by LLM advocates. You're not extreme enough either pro or against LLMs :)
This is ridiculous. Basically you're saying "if you try it and find it sucks, you're wrong, keep at it until you change your mind". That isn't a tool at that point, it's a religion.