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- Hacker News
- 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.by shevy-java
- 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.
by blfr - Is the issue that nobody has come up with the idea for the great ground breaking ideas?
Or B that the ideas are there but are not get released as the code is ai slop?
by uxhacker - 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
by Marazan - > “after four years of open source LLMs, we should have three AirBnBs, two Stripes, and three Dropboxes thanks to the power of AI.”
Airbnb, Stripe and Dropbox were created in a different time when the market was much less competitive.
Saturation of software development velocity doesn’t increase large scale product opportunities in the market. It can also mean that opportunities get filled even more quickly by niche players, and nobody gets to grow to Airbnb scale.
IMO the latter is what’s currently happening. AI-powered companies are like little mammals scurrying around between the feet of the dinosaurs, and commentators like the OP look at the evolution of the brontosaurus as evidence that the mammals don’t seem to be growing as they should.
by pavlov - It’s laughable to compare fundraising today to 15 years ago.
You won’t get capital let alone VC if you’re not AI.
It’s infected everything much like crypto did just 3-4 years ago.
by grebc - Alternatively, AI teaches you lessons about technical debt, code maintainability, and architecture faster too. Traditionally it took at least one or two years to really bump into those problems. Now any student can get into these problems within one or two weeks.by whazor
- '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.'
Disesdi Shoshana Cox
by reconnecting - Pre-AI, the limiter on my bad code was how much code I could type in a day.....
Now with AI I can 10x my output and 10x my bad code!
by Lapalux - Whoever is giving a bad coder resources and access will eventually stopby bwhiting2356
- > Uses only DeepSeek and comes to the conclusion that LLM's are bad at coding?
Why not use actual frontier models, and you know do some real research, before writing a blog post?
by Zakis1 - It doesn't fit the narrative that they need to adhere to. I'm a skeptic through and through, but yeah... This article reads like propaganda.by cheeze
- > do some real research
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".
by wolvesechoes - > Why not use actual frontier models, and you know do some real research, before writing a blog post?
Seems like they've already done more research than you. Their results not matching your expectations does not indicate a lack of research. If you feel they missed something, why don't you go spend your own money on whatever frontier model you want and go publish a post with your own conclusions.
by solid_fuel - DeepSeek has been the most used model on open router by far, only temporarily overtaken by ox alpha when it was free, so it's the most representative experienceby big-chungus4
- In general, the frontier models are not capable of reliably authoring non-trivial code without careful oversight yet. They are great at producing code that can pass tests, but not neccessarily a code review. This means if you care about code quality you still need a human in a loop understanding what has been done, and that becomes the bottleneck. And less disciplined folks will indeed become increasingly dependent.
However, over time the complexity of problems where you can get away with less/no oversight is increasing. And the models are already great at solving certain classes of problems where one doesn't really care that much about code quality, that wouldn't have even been attempted in a pre-LLM world. Over the weekend I was using Claude to add features to the compiled (no source available) firmware of one of my audio devices, adding workflow features by patching assembly and custom DSP code.
In coding, as with other areas, what's emerging is jagged intelligence.
by MrScruff - “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.“
Wow. I guess that’s the punchline!
by dr_dshiv - 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?
by cheeze - 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.
by reconnecting - I started manual coding again at least 1 day a week.
Its good for the brain, but man it's really slow.
And the AI results prove it: Over the past couple years I've been able to bring several work projects to completion single handedly.
Our R&D company is now handling more clients and we are returning better outcomes/products faster than before.
So...what to do? Results don't lie.
However I will say LLM's can't write multi threaded double buffers by them selves. Probably because they are so application specific.
But I think the reason I can go do fast is because I went so slow before. I have an intuition I can transfer into an LLM. Question is if that intuition will become sloppy as time goes on...
by kooi - Bit of a humbling/jarring moment when I realized that people are doing real paid work using LLMs that they could not otherwise do. I mean, it's quite obvious I suppose. But up until now I just assumed it was only a (massive) catalyst for things people would already be able to do with enough time. But nope -- it seems people are right now employed in roles that they would not be able to fulfil the tasks within if AI wasn't there telling them what to write/say/produce. Nobody is really going to come out and say that ... it's not something the less-AI-literate superiors would take kindly to.by padolsey
- All those programmers who could not write fizzbuzz can ship something now.by Ampersander
- aka there are a lot more bullshit artists around these days
i know of several engineers who produce absolute slop and who probably would have produced nothing at all in pre AI times (which would have been preferable) and probably let go or never hired (even better).
they impose such an enormous drag on productivity that they more than wipe out any gains from people using the tools responsibly.
by pydry - But if the AI has a blindspot then they will fail hard since they rely on the LLM for everything.by Gepsens
FWIW, this is not exactly new; those same people were just using other sources like Stack Overflow, blog posts, etc. before, cobbling together random code snippets, libraries, and so on without actually understanding any of that at a relevant detail level.> people are doing real paid work using LLMs that they could not otherwise doSure, with LLMs, one can naturally tailor this much closer to the current need (or at least the need one thinks they have) and iterate ("spew") faster, but it's not a new phenomenon in general.
by tlamponi- I mentioned this then other day, my university class had maybe 80% of people who could not code. No joke. And a lot have gone onto to code professionally.
AI is a godsend to this cohort of code monkies.
Edit: we graduated in 2006.
by grebc - I now started to us AI to help review my juniors PRs, because I couldn't keep up with the amount of code they ship. It started poorly, but now I have my method: I first read the code and flag the lines I'm not sure about, then ask any frontier model (I like Claude here for analysis, even if I don't use it for the rest) to explain the PR and to put effort on the parts I flagged (basically explain in detail the code, not only the PR), and to search through the libraries. Sometimes it notices something I would have missed (like missing an 'order_by' or off by one errors, because the underlying lib wasn't coded like the original AI pretended it was).
I also changed the way I do review because it has been more than a year and the juniors/new hire are still lost, wether on domain knowledge for the older new hire, or just capabilities for the juniors, and discussing with other departments, it's the same for like 95% of them. Now, rather than correcting the PR or adding a request for change, I add a whole unit/functional test to the PR and let that as an exercise to pass the test. They can use AI but I tell them to try to find what part of the code doesn't work before generating the fix, hopefully they'll take ownership of the code if I keep doing that.
by orwin - where do u work that even hires juniors lolby Madmallard
- Wow, that painful AI aided review process, it's like you are computering with eyes closed.by wseqyrku