They can think and reason better than most humans. Most problems they're pointed at are not in their training set, but in certain ways they resemble things that are—maybe there are a few different resemblances to different problems in its training set—so it's able to pull these disparate similarities together and apply the patterns it finds to come up with a solution. Much like human brains do.
What? This is a massive misunderstanding. It’s easy to get truly novel ideas from LLMs, unless your definition of “new things” is so strict that no human can do so either.
The training set is about patterns, not facts or specific configurations. Yes, it’s possible to extract (some) of the training set verbatim, but that doesn’t mean it’s all you can do.
>unless your definition of “new things” is so strict that no human can do so either.
Humans rarely think of new things. We're a weak hivemind species. One or two individuals figure something out, and the rest of the troop of monkeys imitates. Brains are too fuel hungry for every brain to be innovating, "innovate and copy to the other brains" is the norm.
It does not think at all. It vibes based on its training and any additional bolted on constraints. It is a quite simple automation that only works by huge amount of existing data.
Modern man has grown quite dumb. He only seems to be able to "invent" by massive scaling things that are decades or centuries old..
Electricity runs from simple batteries (600 BCE) to today’s power grids.
RF was predicted but not demonstrated by Maxwell in the 1860’s. His work built on Faraday’s (1840’s) and Coulomb’s (1780’s). Coulomb built on Franklin and Newton, among others. Or do you mean Marconi and Tesla, who merely implemented what Maxwell predicted?
The same is true for lasers and transistors but it’s tedious. There was no single “back in the day people invented things from whole cloth” moment.
I would put it differently. Those inventions came from humans interacting with the physical world.
When LLMs were first introduced, they didn't have much of a feedback loop. They wrote code, but they couldn't compile it. Not surprisingly, the code had bugs.
Now, they run with harnesses that allow them to compile the code, and react to the issues they observe. They can fix their own bugs and solve problems that they create, just like humans.
Give an agent access to the physical world, and it seems highly likely that they will be able to "invent" things based on feedback they receive while working towards goals.
Of course, there are some well-known limitations of LLMs, one of the biggest being that they're pretrained. So there may be some things where they're not as good. Just like how some humans aren't as good at certain tasks, depending on their genetics and/or how they've been trained.
> it seems highly likely that they will be able to "invent" things based on feedback they receive while working towards goals...
I don't think so. Imagine a model trained on data from an Internet that believes in hypothesis that earth is the center of the world. Even if you feed all the physical data, I don't think it can come up with the idea that all of its training data was wrong.
This might be also a good argument for why this LLMs are not "intelligent". You can feed contradicting training data all day and it will accept it without bating an eye. But that won't work with an entity that is truly intelligent.
Those are not merely scaling. I can get “build upon other works”, but there’s a lot of scientific insights needed for observing and modeling a phenomena. It may even requires a boost of creativity to theorize an effect based on that model and then make it possible in an experiment.
In what way is electricity an invention? Electricity is a physical phenomenon. Various machines for doing work with electrical energy, storing electrical energy, converting other types of energy to electrical energy, etc. are certainly inventions... Heck, rubbing an amber rod with a fur is an invention. The static charge transferred is not.
Invention, discovery..does not matter. There was a point in time when humanity was oblivious to the phenomenon and then there was a point when we were not and we could generate and use it.
It is false to claim that there was a moment when electricity went from unknown and opaque to understood and producible. That “moment” was thousands of years and all incremental.
Individual brilliance has always been rare. If I booted your ass back 1000 years you'd have seen the same shade of grey in the pig farmers and peasants along with most of the nobles and kings. It turns out that in general the world is a shade of grey.
Hell, looking back at the brilliant individuals, they had many, many grey areas.
I was pointing out two things: first, your understanding of LLM capabilities is very outdated; and second, that in this respect, you're behaving much like an LLM with a training cutoff.
That further touches on the idea that the differences between you and an LLM may not be as large as you imagine. In particular, "cobbling something together if it's in their training set" is pretty much what all humans do.
This reminds me of the Go champion who announced he was giving up the game after a computer beat him.
It’s as if a runner were to give up running when beaten by a horse or a car. It suggests they may have had unexamined and perhaps somewhat strange reasons for doing the activity in the first place.
People have difficulty accepting just how significant their limitations actually are. We design our world to hide those limitations. As an example, it would be easy to make computer games that are unwinnable by humans because of our slow reaction times, low speed in general, and our cognitive limitations. But no-one makes such games, because few people would want to play them for very long.
The “terrible cost” in this specific case seems to be related to discovering that we were fooling ourselves about how good we were at software development.
I'm not giving up the career. And I certainly don't feel left behind: I'm good at programming, and I still have a substantial edge over non-programmers here in meaningfully using agents (as of June 2026). The terrible cost refers to sucking all the joy of the process as the mechanized activity makes the actual intellectual part of the work redundant, if you can understand.
Why is it bittersweet? Carpenters probably didn't cry when their tools improved.
It will be bittersweet when there's no human needed at the wheel but IMHO we are far, far from that. These models/agents are just mimicking human text and need guidance because they often get lost or stuck.
Carpenters would have cried if all their work was reduced to shoving the logs into CNC machines.
Yes there is still human input but it requires comparatively no skill or depth and it gets easier by the month. If I were lobotimized today I'd still be able to function as half-assed architect to AIs anyway.
When was the last time you read fighting distractions/getting "in the zone"/complaint about open space offices thread or comment? They used to be a weekly feature on HN frontpage.
> Yes there is still human input but it requires comparatively no skill or depth and it gets easier by the month. If I were lobotimized today I'd still be able to function as half-assed architect to AIs anyway.
Hard doubt, software engineering is so much more than just literal coding and typing. At least for many of us, the coding/typing part is the easy stuff, everything around that is where the actual engineering happens. If I were lobotomized, maybe I'd get ~10% done today as the day before, if I'm lucky. Even with my full mental capabilities, the agents end up on wild goose-chases unless I'm very specific with what I want, and even sometimes ignoring things if they're too complicated/takes too long, so a bit of thinking is still required to get the right prompts.
And considering how subjective programming is, since it's a creative endeavour after all, I'm not that worried somehow all programmers will be unemployed in just some years.
> When was the last time
Frequency of something doesn't tell you how big of an issue something is, for all we know, HN community (or even the moderators) could have been tired of all the circular conversations where nothing new is being said, and downvote it. Doesn't really tell us much.
Coding is literally writing code, instructions in plain text that control the behavior of computer. That implies knowing which instructions to write.
But creating software is much more than that. Just like writing an essay involves more than just typing words. Other activities include: Architecture, Requirements analysis, Debugging, Testing, Integration,…
Use whatever labels you want, apply charitable reading and I'm sure even you could understand what I mean here. Clearly there are at least two sorts of tasks (or used to anyways) in "software engineering" as a whole, one more mechanical and one more about thinking.
What exactly shows that? That I think thinking about code/design and typing code are two different activities? Maybe you disagree, around myself and my peers that'd be a minority perspective, but it's not speculative, based on real experience.
But it's not like "shoving the logs into CNC machines". You have to understand what they are doing and point them into the right direction. LLMs very often lack common sense once you move out of easy things.
I love programming CNC machines; I am a terrible carpenter. Someone still has to tell the LLMs what to build, specify design constraints and goals, etc
You're the second person itt using an expression "typing in code". Guys I understand your excitement now that you too finally can make computers do what you want but it's not how programming worked at all.
I think carpenters might cry if a company went around shoving every single piece of carpentry they could find into a machine, and then when you press a button on that machine, a chair comes out, and then they go around saying that this machine will replace carpenters forever, and they made this machine with no help from other carpenters, and furniture makers all went "who needs carpenters anymore, lets just use the chair machine"
Software isn't solved. 'Coding' is, according to the people of Claude.
Coding (programming) is a tedious and expensive part of software engineering. There's other parts AI isn't doing, such as understanding and refining requirements, and delivery + accountability.
> Coding (programming) is a tedious and expensive part of software engineering.
Why is that? Coding, for me, is kinda relaxing, and the fun part of developing software. Gathering requirements, especially in a corporate settings, is the tedious part and the most time consuming.
How is it solved? LLMs cannot think new things, they can only cobble something together if it's in their training set.
New things are made by cobbling together existing things.
They can think and reason better than most humans. Most problems they're pointed at are not in their training set, but in certain ways they resemble things that are—maybe there are a few different resemblances to different problems in its training set—so it's able to pull these disparate similarities together and apply the patterns it finds to come up with a solution. Much like human brains do.
What? This is a massive misunderstanding. It’s easy to get truly novel ideas from LLMs, unless your definition of “new things” is so strict that no human can do so either.
The training set is about patterns, not facts or specific configurations. Yes, it’s possible to extract (some) of the training set verbatim, but that doesn’t mean it’s all you can do.
>unless your definition of “new things” is so strict that no human can do so either.
Humans rarely think of new things. We're a weak hivemind species. One or two individuals figure something out, and the rest of the troop of monkeys imitates. Brains are too fuel hungry for every brain to be innovating, "innovate and copy to the other brains" is the norm.
I am not sure if claude had powerpc scripts in its training.
That "only" part used to be the hardest. Getting the ideas was never the hard part. I think someone here even wrote an essay on that.
It does not think at all. It vibes based on its training and any additional bolted on constraints. It is a quite simple automation that only works by huge amount of existing data.
Modern man has grown quite dumb. He only seems to be able to "invent" by massive scaling things that are decades or centuries old..
Out of curiousity, can you share a human invention that is not merely scaling things that were decades or centuries old at the time?
Fire? The wheel? Archimedes screw, maaaaybe?
Electricity, RF communication, LASERS, Transistors....
What specific inventions in those areas?
Electricity runs from simple batteries (600 BCE) to today’s power grids.
RF was predicted but not demonstrated by Maxwell in the 1860’s. His work built on Faraday’s (1840’s) and Coulomb’s (1780’s). Coulomb built on Franklin and Newton, among others. Or do you mean Marconi and Tesla, who merely implemented what Maxwell predicted?
The same is true for lasers and transistors but it’s tedious. There was no single “back in the day people invented things from whole cloth” moment.
I would put it differently. Those inventions came from humans interacting with the physical world.
When LLMs were first introduced, they didn't have much of a feedback loop. They wrote code, but they couldn't compile it. Not surprisingly, the code had bugs.
Now, they run with harnesses that allow them to compile the code, and react to the issues they observe. They can fix their own bugs and solve problems that they create, just like humans.
Give an agent access to the physical world, and it seems highly likely that they will be able to "invent" things based on feedback they receive while working towards goals.
Of course, there are some well-known limitations of LLMs, one of the biggest being that they're pretrained. So there may be some things where they're not as good. Just like how some humans aren't as good at certain tasks, depending on their genetics and/or how they've been trained.
> it seems highly likely that they will be able to "invent" things based on feedback they receive while working towards goals...
I don't think so. Imagine a model trained on data from an Internet that believes in hypothesis that earth is the center of the world. Even if you feed all the physical data, I don't think it can come up with the idea that all of its training data was wrong.
This might be also a good argument for why this LLMs are not "intelligent". You can feed contradicting training data all day and it will accept it without bating an eye. But that won't work with an entity that is truly intelligent.
Those are not merely scaling. I can get “build upon other works”, but there’s a lot of scientific insights needed for observing and modeling a phenomena. It may even requires a boost of creativity to theorize an effect based on that model and then make it possible in an experiment.
Those are the specific inventions.
> Those are the specific inventions.
In what way is electricity an invention? Electricity is a physical phenomenon. Various machines for doing work with electrical energy, storing electrical energy, converting other types of energy to electrical energy, etc. are certainly inventions... Heck, rubbing an amber rod with a fur is an invention. The static charge transferred is not.
Invention, discovery..does not matter. There was a point in time when humanity was oblivious to the phenomenon and then there was a point when we were not and we could generate and use it.
This is so false. Try doing the research to back up your risible claim.
Tell me the date when humanity went from oblivious to electricity to generating and using it.
What exactly is false?
It is false to claim that there was a moment when electricity went from unknown and opaque to understood and producible. That “moment” was thousands of years and all incremental.
I didn't make no such claims. I claimed that these "incremental" progress was not about simply doing more of the same stuff aka scaling.
Great. So when you say electricity, do you mean the batteries of 600BCE and the precursors before them?
>Modern man has grown quite dumb
Ah yes, that's why it only took 50 years instead of 100,000 years for homosapients to reach the space age....
Dude, there was no glorious past, we've always sucked.
We have always sucked, but there used to be individual brilliance. Now everyone is the same shade of grey...
Individual brilliance has always been rare. If I booted your ass back 1000 years you'd have seen the same shade of grey in the pig farmers and peasants along with most of the nobles and kings. It turns out that in general the world is a shade of grey.
Hell, looking back at the brilliant individuals, they had many, many grey areas.
>Hell, looking back at the brilliant individuals, they had many, many grey areas.
That is exactly the point. Back then that could exist. Now, we would just cancel them for one of the grey areas.
I take it that your training cutoff was early 2023.
the trope that everyone else you are talking to on the Internet is a bot is getting tiring real fast
I wasn't saying you were a bot.
I was pointing out two things: first, your understanding of LLM capabilities is very outdated; and second, that in this respect, you're behaving much like an LLM with a training cutoff.
That further touches on the idea that the differences between you and an LLM may not be as large as you imagine. In particular, "cobbling something together if it's in their training set" is pretty much what all humans do.
This reminds me of the Go champion who announced he was giving up the game after a computer beat him.
It’s as if a runner were to give up running when beaten by a horse or a car. It suggests they may have had unexamined and perhaps somewhat strange reasons for doing the activity in the first place.
People have difficulty accepting just how significant their limitations actually are. We design our world to hide those limitations. As an example, it would be easy to make computer games that are unwinnable by humans because of our slow reaction times, low speed in general, and our cognitive limitations. But no-one makes such games, because few people would want to play them for very long.
The “terrible cost” in this specific case seems to be related to discovering that we were fooling ourselves about how good we were at software development.
I'm not giving up the career. And I certainly don't feel left behind: I'm good at programming, and I still have a substantial edge over non-programmers here in meaningfully using agents (as of June 2026). The terrible cost refers to sucking all the joy of the process as the mechanized activity makes the actual intellectual part of the work redundant, if you can understand.
Software development is now another fake job.
Why is it bittersweet? Carpenters probably didn't cry when their tools improved.
It will be bittersweet when there's no human needed at the wheel but IMHO we are far, far from that. These models/agents are just mimicking human text and need guidance because they often get lost or stuck.
Carpenters would have cried if all their work was reduced to shoving the logs into CNC machines.
Yes there is still human input but it requires comparatively no skill or depth and it gets easier by the month. If I were lobotimized today I'd still be able to function as half-assed architect to AIs anyway.
When was the last time you read fighting distractions/getting "in the zone"/complaint about open space offices thread or comment? They used to be a weekly feature on HN frontpage.
> Yes there is still human input but it requires comparatively no skill or depth and it gets easier by the month. If I were lobotimized today I'd still be able to function as half-assed architect to AIs anyway.
Hard doubt, software engineering is so much more than just literal coding and typing. At least for many of us, the coding/typing part is the easy stuff, everything around that is where the actual engineering happens. If I were lobotomized, maybe I'd get ~10% done today as the day before, if I'm lucky. Even with my full mental capabilities, the agents end up on wild goose-chases unless I'm very specific with what I want, and even sometimes ignoring things if they're too complicated/takes too long, so a bit of thinking is still required to get the right prompts.
And considering how subjective programming is, since it's a creative endeavour after all, I'm not that worried somehow all programmers will be unemployed in just some years.
> When was the last time
Frequency of something doesn't tell you how big of an issue something is, for all we know, HN community (or even the moderators) could have been tired of all the circular conversations where nothing new is being said, and downvote it. Doesn't really tell us much.
Honestly conflating coding with typing tells me your idea of coding is very different to what I used to do.
Coding is literally writing code, instructions in plain text that control the behavior of computer. That implies knowing which instructions to write.
But creating software is much more than that. Just like writing an essay involves more than just typing words. Other activities include: Architecture, Requirements analysis, Debugging, Testing, Integration,…
Use whatever labels you want, apply charitable reading and I'm sure even you could understand what I mean here. Clearly there are at least two sorts of tasks (or used to anyways) in "software engineering" as a whole, one more mechanical and one more about thinking.
It just shows you haven't programmed computers much so your opinion is largely speculative.
What exactly shows that? That I think thinking about code/design and typing code are two different activities? Maybe you disagree, around myself and my peers that'd be a minority perspective, but it's not speculative, based on real experience.
> apply charitable reading and I'm sure even you could understand what I mean here.
Beautiful burn.
But it's not like "shoving the logs into CNC machines". You have to understand what they are doing and point them into the right direction. LLMs very often lack common sense once you move out of easy things.
Yes you have to understand when the log stuck in CNC machine, if you want to put the carpentry analogy to its extreme.
I love programming CNC machines; I am a terrible carpenter. Someone still has to tell the LLMs what to build, specify design constraints and goals, etc
Yes, the easy part is still there.
Funny, working in product I think designing the right thing is far more difficult and interesting than just typing in source code.
You're the second person itt using an expression "typing in code". Guys I understand your excitement now that you too finally can make computers do what you want but it's not how programming worked at all.
Yeah I cut my teeth on 6502 assembly and know IDK how many languages. I get it.
It’s still typing in code.
I think carpenters might cry if a company went around shoving every single piece of carpentry they could find into a machine, and then when you press a button on that machine, a chair comes out, and then they go around saying that this machine will replace carpenters forever, and they made this machine with no help from other carpenters, and furniture makers all went "who needs carpenters anymore, lets just use the chair machine"
The real problem is we built the genie in the lamp or the monkey's paw: it's a machine that gives you what you ask for!
Software isn't solved. 'Coding' is, according to the people of Claude.
Coding (programming) is a tedious and expensive part of software engineering. There's other parts AI isn't doing, such as understanding and refining requirements, and delivery + accountability.
> Coding (programming) is a tedious and expensive part of software engineering.
Why is that? Coding, for me, is kinda relaxing, and the fun part of developing software. Gathering requirements, especially in a corporate settings, is the tedious part and the most time consuming.
Accountability?!?! Outside medical software, and similar niches, I see little accountability in the software industry.
The cost is not terrible, calm down.