I don't know about other people, but to me these constant salvos of AI hype are like watching an old silent comedy where people are throwing custard pies at each other. The first couple of pies are funny and then it just gets tedious.
Over 50 years I have written over a million lines of code in over 20 languages. AI gives me a step up in blocking out preliminary solutions especially in the earliest stages. However it sucks at debugging and I mean really sucks. The worst is an inhuman 'proximity bias' that often, when asked for a simple solution to a small issue will offer a complete refactoring, entailing starting from scratch and when challenged offers a transparently self congratulatory "applogy".The hazards barely exceed the opportunities.
Agree about the debugging. I wrote my first computer program in 1958 (in Bell Floating Point Interpreter for the IBM 650) and have been at it ever since. I use AI a bit differently: I ask it to produce code snippets after I have blocked out the logic of what I want, which saves me cudgeling my ancient brain for the right set of syntax details. After one or two total time-wasters trying to debug a wrong 'un, if the code isn't transparently correct I rephrase the prompt and ask again.
And this, unfortunately if not tragically, is what will happen when those DOGE 'experts' walk away from the chaos they created across all government platforms, networks, and architectures.
I work in a company with a lot of people over 50, and even though I'm in my 30s, I trust them with just about everything more than I trust our younger colleagues.
Yeah. I'm so worried about the future at the moment. Elon is clearly high on ketamine, and that is no joke. I never took it, but I imagine it helps with his anxiety, at the expense of making him (even more) delusional.
They are totally going to feed massive government databases into an LLM and form public policy based on the results. I think till now the government has made limited use of "AI" even though palantir have wanted to change that. Now these companies have their entry point and free reign to just do what they like.
Roose and company are further evidence not just of "the death of expertise", but a disdain for the effort required to master a skill (or any skill other than marketing hype). The impact of this attitude is visible across the spectrum with the notion that all one needs is a few "prompts" to be a programmer being one of the most public and egregious, but the sentiment is visible in the declining desire to master skills as disparate as welding and accounting. Shipyards can't find people who have the skills to build ships, government agency can't find competent forensic accountants, hospitals scramble to find nurses, particularly those with specialties. Because "mastery is hard". According to the snake oil set we don't need cardiovascular surgeons, there's a prompt for that.
I'm sure it's been said but, to get AI to write correct and sufficient code requires that complete, unambiguous requirements are provided. Good luck with that.
So true. Those of us who work in software (data engineering and analysis in my case) know that most of the "secret sauce" of programming comes from turning vague user demands into concrete and maintainable solutions - not from typing out thousands of lines of code.
I used a pencil to write my Assembly Language code (or sometimes FORTRAN or COBOL or JCL or even channel programs) onto coding forms that were sent to (the all-woman) Keypunch Department to be, ummm, keypunched onto cards. The cards were rubber-banded together, then carried down the hall, where they waited patiently to be fed into our card reader, and run on our mainframe. The printed output (11 x 15) was rubber-banded together with my cards and returned to my desk via internal mail.
I wonder how long the whippersnappers would hang around
I must be a bit younger than you. By the time I was programming the Apple II, Commodore 64 and TRS-80 were things. Of course it was still easier to write out code on paper beforehand or print it out and check it over that way. Those black and green CRTs were an eyesore.
If you read Ethan Mollick’s post on this, it’s probably worse than Roose. He rhapsodizes about “vibecoding” (cringe) in which he was able to make something half assed that no one would want for only $13!
Let's take this back to 1975. Around then sci-fi writer Douglas Adams wrote "The hitch-hikers guide to the galaxy" a satire on Lonely Planet guidebooks.
As usual the book had androids .. built by the Sirius Cybernetics Corporation .. with Genuine People Personalities. The Sirius Cybernetics Corporation described them as "your plastic pals who are fun to be with".
Unfortunately, the SCC created personalities were all flawed (but in a comic way).
Marvin the Android was permanently pessimistic and depressed. He despised humans for giving him tasks that he thought beneath him. ("Brain the size of a planet and all you want me to do is compute a trajectory ....").
Self-opening doors and lifts were given AIs too .. all they could do, was open and shut the door and say "Glad to be of service" . All the doors chose to do this in a slow servile voice that soon got irritating.
A fully automated space craft, it's AI refused to authorise lift off as the passengers snacks hadn't been delivered ... It apologised to passengers for the delay. It was still apologising when the fossilised space ship was re discovered 300 years later, pax mummified.
You get the picture. PacMan wasn't even around in 1970s, , but already Silicon Valley was high on hype.
Shouldn't a good agentic reasoning model figure out for itself that it can't do a good job and just go on the web to grab the first plausible-seeming Pac-Man clone? Plagiarism is fully expected, not to mention the explicit forms of cheating reported recently. LLMs often say they're sorry, but they don't really mean it.
It makes you wonder why we (devs + PMs) spend hours understanding and formalizing a business feature request. In the end they usually are close to what the business actually wants but far from what goes into the code. I think it will require some pseudo code/LLM language to succinctly describe what AI should create.
o3-mini-high just solved it? I now have a perfectly fine pac man running. I don't think dario meant that literally anybody could code up anything (e.g., a networked air traffic control system). if you put in some effort into your prompt, one should not downplay what already can be achieved w/o any coding experience imho. I do not believe all coders will be replaced soon, but to be fair a lot of coders for the longest time could get away with pretending to be more skilled than they actually were. I'm convinced only people who are great at it will be coding in 2030, and it will be 80% less than are today.
The world is awash in frustrating code that often makes it necessary to call customer support. Banks, phone companies, others where actually talking to someone is hard to figure out. What possible use will the next gen of autocomplete software do to improve functionality, UX? What will AI produce but more frustrating software.
Trillion dollar company software sucks pre-AI and it will be like quicksand post-AI
I've been joining some "vibe coding" demos lately. Based on what I've seen, I felt The Guardian missed the mark on current capabilities.
To test this, I used Lovable. With just 3 prompts, on a free account, I built a basic Pacman game in minutes. I published it here for you to have a look https://pacman.lovable.app
My 3 prompts:
1. "Create a working pacman game."
2. "It doesn't work once I click 'start game'. Make sure it works after I click 'start game'." (AI self-debugged)
3. "When I start the game, it's immediately game over. Make sure that pacman starts at the bottom of the grid, and the ghosts start in the 'home' in the middle." (AI refactored)
It's far from perfect, but:
- a functional game from a non-coder in minutes shows real progress.
- If I'd spent an hour or so on it, I'm sure I'll get this in a pretty good shape.
- Skilled coders would probably achieve much more, super fast.
I think this is a much better representation of where AI tools are today in coding Pacman than the Guardian makes us believe. Still, per Gary's point: there's a long road ahead.
Already, there are some "best practices" in how to get an LLM to do a better job coding. Having a doc that describes general coding practices. Have an LLM generate PRD documents, that are then fed back into the LLM before generating code.
These demos aren't really detailed enough to evaluate how good the tools & techniques are... And at least you provided some details! This was quite impressive as it stood.
That said, I've been trying to get Claude to do some coding and it's a hot mess. It breaks things as often as it fixes them, the code requires a lot of hand-holding to make it look respectable, it often goes off in the wrong direction when fixing bugs... But still, it has improved a lot over the last 12 months.
Did you "build" a Pac-Man game? Or did it take you several tries to get a model reproduce an app that should be present, verbatim, in the training data?
I don't know about other people, but to me these constant salvos of AI hype are like watching an old silent comedy where people are throwing custard pies at each other. The first couple of pies are funny and then it just gets tedious.
Over 50 years I have written over a million lines of code in over 20 languages. AI gives me a step up in blocking out preliminary solutions especially in the earliest stages. However it sucks at debugging and I mean really sucks. The worst is an inhuman 'proximity bias' that often, when asked for a simple solution to a small issue will offer a complete refactoring, entailing starting from scratch and when challenged offers a transparently self congratulatory "applogy".The hazards barely exceed the opportunities.
Agree about the debugging. I wrote my first computer program in 1958 (in Bell Floating Point Interpreter for the IBM 650) and have been at it ever since. I use AI a bit differently: I ask it to produce code snippets after I have blocked out the logic of what I want, which saves me cudgeling my ancient brain for the right set of syntax details. After one or two total time-wasters trying to debug a wrong 'un, if the code isn't transparently correct I rephrase the prompt and ask again.
Earl, I was born in 1974, and you are my new hero.
And this, unfortunately if not tragically, is what will happen when those DOGE 'experts' walk away from the chaos they created across all government platforms, networks, and architectures.
I work in a company with a lot of people over 50, and even though I'm in my 30s, I trust them with just about everything more than I trust our younger colleagues.
The current neural network AI crowd are plug and pray practitioners.
They are merely tweaking LLMs without really understanding any of the stuff they are producing.
They are like the people who plug data into statistics packages without knowing anything about statistics.
This is what AI “science” has become
Yeah. I'm so worried about the future at the moment. Elon is clearly high on ketamine, and that is no joke. I never took it, but I imagine it helps with his anxiety, at the expense of making him (even more) delusional.
They are totally going to feed massive government databases into an LLM and form public policy based on the results. I think till now the government has made limited use of "AI" even though palantir have wanted to change that. Now these companies have their entry point and free reign to just do what they like.
Roose and company are further evidence not just of "the death of expertise", but a disdain for the effort required to master a skill (or any skill other than marketing hype). The impact of this attitude is visible across the spectrum with the notion that all one needs is a few "prompts" to be a programmer being one of the most public and egregious, but the sentiment is visible in the declining desire to master skills as disparate as welding and accounting. Shipyards can't find people who have the skills to build ships, government agency can't find competent forensic accountants, hospitals scramble to find nurses, particularly those with specialties. Because "mastery is hard". According to the snake oil set we don't need cardiovascular surgeons, there's a prompt for that.
I'm sure it's been said but, to get AI to write correct and sufficient code requires that complete, unambiguous requirements are provided. Good luck with that.
So true. Those of us who work in software (data engineering and analysis in my case) know that most of the "secret sauce" of programming comes from turning vague user demands into concrete and maintainable solutions - not from typing out thousands of lines of code.
You wrote assembly for the 6502? I'm duly impressed.
yep, on Commodore 64.
A great machine as was the Apple ][
I worked in the IBM mainframe ecosystem, developing database products for software vendors. Glad I got out before GPT 4.5 was released ...
In our day we had to use a pencil to program computers!
Not to write, but to adjust the tension of the audio tapes!
What's an audio tape?!?! Get off my lawn you little whippersnapper!
I used a pencil to write my Assembly Language code (or sometimes FORTRAN or COBOL or JCL or even channel programs) onto coding forms that were sent to (the all-woman) Keypunch Department to be, ummm, keypunched onto cards. The cards were rubber-banded together, then carried down the hall, where they waited patiently to be fed into our card reader, and run on our mainframe. The printed output (11 x 15) was rubber-banded together with my cards and returned to my desk via internal mail.
I wonder how long the whippersnappers would hang around
I must be a bit younger than you. By the time I was programming the Apple II, Commodore 64 and TRS-80 were things. Of course it was still easier to write out code on paper beforehand or print it out and check it over that way. Those black and green CRTs were an eyesore.
Just brilliant ! AIs can't even code a basic video game from 40 years ago !
I love these elegant debunkings of the AI hype
Complete history of AI in tl;dr:
We don't have jam today but we will have jam in three years! And it will BE GREAT!!!
If you read Ethan Mollick’s post on this, it’s probably worse than Roose. He rhapsodizes about “vibecoding” (cringe) in which he was able to make something half assed that no one would want for only $13!
Let's take this back to 1975. Around then sci-fi writer Douglas Adams wrote "The hitch-hikers guide to the galaxy" a satire on Lonely Planet guidebooks.
As usual the book had androids .. built by the Sirius Cybernetics Corporation .. with Genuine People Personalities. The Sirius Cybernetics Corporation described them as "your plastic pals who are fun to be with".
Unfortunately, the SCC created personalities were all flawed (but in a comic way).
Marvin the Android was permanently pessimistic and depressed. He despised humans for giving him tasks that he thought beneath him. ("Brain the size of a planet and all you want me to do is compute a trajectory ....").
Self-opening doors and lifts were given AIs too .. all they could do, was open and shut the door and say "Glad to be of service" . All the doors chose to do this in a slow servile voice that soon got irritating.
A fully automated space craft, it's AI refused to authorise lift off as the passengers snacks hadn't been delivered ... It apologised to passengers for the delay. It was still apologising when the fossilised space ship was re discovered 300 years later, pax mummified.
You get the picture. PacMan wasn't even around in 1970s, , but already Silicon Valley was high on hype.
Adams .. no means writer .. skewered them.
42
Shouldn't a good agentic reasoning model figure out for itself that it can't do a good job and just go on the web to grab the first plausible-seeming Pac-Man clone? Plagiarism is fully expected, not to mention the explicit forms of cheating reported recently. LLMs often say they're sorry, but they don't really mean it.
It makes you wonder why we (devs + PMs) spend hours understanding and formalizing a business feature request. In the end they usually are close to what the business actually wants but far from what goes into the code. I think it will require some pseudo code/LLM language to succinctly describe what AI should create.
o3-mini-high just solved it? I now have a perfectly fine pac man running. I don't think dario meant that literally anybody could code up anything (e.g., a networked air traffic control system). if you put in some effort into your prompt, one should not downplay what already can be achieved w/o any coding experience imho. I do not believe all coders will be replaced soon, but to be fair a lot of coders for the longest time could get away with pretending to be more skilled than they actually were. I'm convinced only people who are great at it will be coding in 2030, and it will be 80% less than are today.
To be fair, Dario also says we'll be immortal by 2030 so you'll have to forgive me for not giving a shit what he says
"o3-mini-high just solved it? I now have a perfectly fine pac man running"
What do you mean? Was this one-shot or multi-prompt?
The world is awash in frustrating code that often makes it necessary to call customer support. Banks, phone companies, others where actually talking to someone is hard to figure out. What possible use will the next gen of autocomplete software do to improve functionality, UX? What will AI produce but more frustrating software.
Trillion dollar company software sucks pre-AI and it will be like quicksand post-AI
You are likely right, but on the other hand, deep seek changed my perspective on how useful and accurate large language models can be.
The advances we've seen in the last couple of years are pretty dramatic.
Even in ancient evolution, the steps were often dramatic. Just ask ancient bacteria ..,
I've been joining some "vibe coding" demos lately. Based on what I've seen, I felt The Guardian missed the mark on current capabilities.
To test this, I used Lovable. With just 3 prompts, on a free account, I built a basic Pacman game in minutes. I published it here for you to have a look https://pacman.lovable.app
My 3 prompts:
1. "Create a working pacman game."
2. "It doesn't work once I click 'start game'. Make sure it works after I click 'start game'." (AI self-debugged)
3. "When I start the game, it's immediately game over. Make sure that pacman starts at the bottom of the grid, and the ghosts start in the 'home' in the middle." (AI refactored)
It's far from perfect, but:
- a functional game from a non-coder in minutes shows real progress.
- If I'd spent an hour or so on it, I'm sure I'll get this in a pretty good shape.
- Skilled coders would probably achieve much more, super fast.
I think this is a much better representation of where AI tools are today in coding Pacman than the Guardian makes us believe. Still, per Gary's point: there's a long road ahead.
Already, there are some "best practices" in how to get an LLM to do a better job coding. Having a doc that describes general coding practices. Have an LLM generate PRD documents, that are then fed back into the LLM before generating code.
These demos aren't really detailed enough to evaluate how good the tools & techniques are... And at least you provided some details! This was quite impressive as it stood.
That said, I've been trying to get Claude to do some coding and it's a hot mess. It breaks things as often as it fixes them, the code requires a lot of hand-holding to make it look respectable, it often goes off in the wrong direction when fixing bugs... But still, it has improved a lot over the last 12 months.
Did you "build" a Pac-Man game? Or did it take you several tries to get a model reproduce an app that should be present, verbatim, in the training data?