The way to think about coding agents is that a good one should in theory literally replace the developer entirely. No, a whole organisation of developers.

In theory a product owner should just be able to dictate how they want to product to function at a high level and the AI should take care of the rest in the same way a human programmer or team of programmers would have in the past. If there are conflicts in what's being requested, then the AI should be able to recognise that and ask for production direction.

As always with every generation of AI people seem to way over index on the now.

- "They're good for autocomplete, that's about it"

- "They're good for quickly mocking up small functions, but they make a lot of mistakes"

- "They're good for scaffolding some parts of the system if you're good at prompt engineering"

- "They're good at writing most of the code, but humans will always need to do the last 10%"

- "They can write all of the code, but humans will still need to architect the system"

You are here. Perhaps this is where progress stops. I wouldn't bet on that however.

AI is making programming an irrelevent field.

There are things I don't say online anymore, not because I don't think they're correct, but because my opinion could be deemed offensive.

Whenever I say something I think could risk being seen as offensive, I tend to add a lot of footnotes explaining my reasoning for the things I'm saying and why I'm not trying to offend.

I also never share remotely offensive humour to friends over social media or messaging apps anymore, which used to be fun. Lots of people have been arrested for jokes so just not worth it tbh. Even if I don't think it's that offensive the law is too subjective to take the risk.

I think this is probably first time ever I read one of these and was convinced immediately that I should probably look into using something else.

> LLM technology itself has nothing to do with general (human-like) intelligence.

Neural nets to the brain are like a plane to a bird. Saying LLMs have nothing to do with human-like intelligence is fundamentally ignorant of the field and the inspiration behind many of the algorithmic experiments.

LLMs clearly do things differently, but that doesn't mean they can't be generally intelligent, or they can't produce output that's remarkably similar to a human.

And to be clear, I have studied AI, published on AI and work in AI.

> Do you people get off by fantasizing about people losing their job, or worse? (whatever you are implying)

I'm the exact opposite. I've been terrified about AI for decades. I had nightmares last night as I do most nights about AI. I think humanity is years away from a disaster and I'm pleading for people to see.

But what I've learnt is that every step closer we get the goal posts just move a little more. I'll note just a few years ago HN was saying ChatGPT and LLMs were just stochastic parrots or advanced autocompletes. I pushed back against this and said within years they'll be raising PRs on their own from tickets. But everyone told me, "nooo, they couldn't even do basic maths!!"

Remember this comment when the time comes. We could have acted, but we didn't because every advancement people dismissed and seem to think that further improvements would not be made. You will be wrong.

Realistically you will almost certainly fail because almost all startups fail.

There was a post on Indie Hackers many many years ago now where someone looked through all of the projects posted there over the years and found that something like 1% of them succeed (may have been less tbh – it was so long ago).

You are more likely to succeed if you have serious money to throw behind it or you are able to get investment, but if you're just a dude trying to start a businesses online with some savings you're more or less guaranteed to fail statically. This wasn't true of in tech in the 90s and 00s, but things have matured a lot since then. The fact you have users is actually impressive and imo you've already done better than the vast majority do.

I'm saying this because the first thing you should be doing if you're not already is assuming failure with an extremely high confidence. If you have no plan for failure then you need to start coming up with one now.

I've been through this myself. Startups were my life in my late teens and early 20s. I had a breakdown in my mid 20s because after some early success in my teens, I just couldn't get anything to work anymore. I was also isolating myself from friends and family and the realisation that I had basically lost some of the best years of my life behind a screen and text editor for nothing ate away at me.

Quitting is not failure. Here's what you need to do now.

- Come up with plan assuming your startup will fail.

- Decide the point at which you will stop.

- When that time comes execute your plan like a zombie through the pain.

Your emotions will tell to keep going one more day and your plan however good will almost certainly not be what you want to be doing because if it was you'd already be doing it. Just keep going and you'll come out of it in the end.

Good luck. Wishing you the best bro.

The post-AGI world doesn't depend on people buying stuff.

As you say there will be no job to strike from. And pissing off the government probably isn't going to go down well when they're you're only hope at feeding your family.

Unfortunately in this world income taxes have dropped to 10% of their previous levels and the government is now primarily funded by AI. There are rumours some leaders are questioning why they're even redistributing wealth when they could just take it. Citizens are not needed anymore, they're just a burden and taking from those at the top.

Even if this were true you'd be silly not to see the larger trend.

LLMs and the transformer model were just a step function in AI capabilities upon the last generation of AI.

Whether it's LLMs or not is irrelevent. Major algorithmic improvements in AI have happened every 5-10 years over the last 50 or so years, and now they're happening maybe every 3-5.

The question you should be asking is what happens when the next step function in AI capabilities occurs?

Arguably people worrying about job loses are not worried enough.

What people always struggle to model with AI are the step functions that occur in capabilities as new algorithmic advancements are made. Historically those come maybe every ~5-10 years, although the pace has dramatically increase in the last decade and last 5 years.

Most people right now are plotting a linear improvement over the several years as models get bigger, harnesses become more complex and capable, more people adopt AI for efficiency, etc. Some are adding small exponents, but most are fundamentally modelling wrong.

What's more likely to happen is that in a few months someone at some AI lab will leak that they've made a breakthrough internally. Then another leak will come, and another. We'll know something big is going on because we'll see strange things happening within governments, then FOOM.

We're likely now one more step function away from something that's not just capable of taking your job as an intelligent and knowledgeable human, but surpasses your ability so significantly that you can't even comprehend what's happening around you.

This job concern is really just a concern perhaps of the next year, or maybe at a stretch, a few years.

It's not the purposelessness or job-loss that should have you concerned, but the pandoras box that we're opening. Once that box is opened every problem bottlenecked by intelligence is solvable practically over night, and therefore the way the society will look in a decade is almost impossible to imagine.

The problem of how to cure cancer is solved, but the problem of how to kill everyone with a super virus is too. The problem of how to cure alzheimers is solved, but so is the problem of how to hack the human neural activity is too.

I genuinely do not understand how people still don't see what's coming, but I try to remind myself that these are the good problems and we should enjoy this for as long as it lasts.

If you care about your career you should be one. If you care about engineering you might have other concerns.

I feel burnt out in spoken conversations because I find it very difficult to process sentences at speed. But I don't feel that at all when reading, writing or listening to podcasts because I can go at my own pace.

Similarly I love maths and it doesn't give burnt out when I do it myself, but in school I remember it being agonising trying to get my brain to keep up with everyone around me.

I think this is why AI burns out engineers. Agents can do things do much faster than us so we're no longer comprehending things at our own pace, but trying to keep pace with the AI.

I feel that useless thing too. It hurts me more than anything. I've poured my heart into so many blog posts, tutorials and open source projects over the years. They were genuinely hard at the time. Each tutorial or code project might have been weeks of effort – and it showed. Today an AI could do the same in 10 mins from a single prompt. What was a source of pride for me, now just feels like a major waste of the last 2 decades of my life.

Maybe that's for the best though. I think in hindsight I over index on the value of knowledge. Maybe there are more important things in life.

PayPal was worth 5x this a few years ago... Even pre-pandemic it was worth far more. Hell, just a year ago it was valued at ~$80 share.

$60.50 per share would value them at just 11x their current earnings. I get PayPal isn't exactly a growth company anymore, but I'm not sure I understand why shareholders would agree to this offer?

The UK (where I live) emits something like 0.5% of global CO2, but we're one of the largest economies in the world.

If we're going to do anything it seems we should really be doing everything we can to use our economic might to try to do something about that other 99.5%. Where as at the moment we're wasting our time obsessing about how we bring down that 0.5%, and providing an economic horror story for why no other country should replicate what we're doing.

For a specific technology to become viable, you often need progress in several individual technologies to occur. Some of these will be exponential and surprise us, but many will see slower progress.

Either way, I suspect progress in robotics will be slower than AI, but I also think we'll see a lot of investment in robotics over the next decade given that AI opens up a lot of new potential applications for robotics.

I suspect any task that doesn't require extreme battery life or extreme dexterity will be doable by robots much sooner than most people think today. I think we could have decent-ish humanoid robots within a decade – robots that can prepare food, clean hotel rooms, empty bins, etc. I think Elon's bet on Optimus is quite likely to be viewed as very ahead of the curve with time.

However, it will take much longer for robots to do everything a human body can, but then most jobs don't require we push the physical limits of human body.

That's why I think 60% is reasonable. And even then I'm not saying it will happen, I just don't think that's a bad bet if given even odds.

Europe cannot fix climate change on its own, and we already represent an increasingly small share of total emissions.

The question now is how we get other countries onboard fast, and if they continue to build out cheap coal-fired power stations what are we going to do about it? Something or nothing?

Unless we can get every nation onboard, we should switch strategies to one of managing the inevitable rather than hopeless trying to prevent it. Costly energy policies that reduce global emissions by roughly 0.5% (basically what will happen if the UK ever achieves net-zero) are a total waste of money and time.

Those who care about this issue need to get real and need to stop pretending that the solution is for a few more people in the UK putting solar panels on their roofs. Climate change is a global problem. If your solutions are domestic then they're not serious.

We have a story in the news currently about a foreign child gang rape leader (yes, those are things in the UK) who raped at least 30 children and was released early after serving just 14 years in prison.

We have major children sexual abuse scandals in this country basically every year too. Politicians never care about that though.

I'm sure, they can add a jitter, but then you just change how you detect / weight detection.

And similar things can be said about many technologies in recent history – cars replacing the horse, first flight to man on the moon, even the creation of early internet to its mass adoption.

You're talking generally a decade or 2 for society to completely change from the rapid advancement of a new technology.

I'm not saying I agree with the 2035 prediction, but it doesn't seem impossible to me, if AI can help us improve the pace that we're already developing disruptive robotics.

In 2010 the idea of self-driving cars and autonomous delivery drones seemed very sci-fi and a long way out. But today, just 15 years on, these things are increasingly starting to be rolled out.

If they dropped that 95% number to 50-60%, I think I'd probably lean towards agreeing. Not because it makes sense in my gut, but because the logical part of my brain knows exponential trends (if one exists) do things that we wouldn't instinctively predict. But even if you assume exponentials 95% does seem very high.

~15 years ago HN was full of really interesting deep dives into technical topics. There used to be articles about different algorithms, frameworks, programming languages, etc. Back then I even used to write tech posts and tutorials myself and share them here with some success.

The other thing I miss are the entrepreneurial posts... My friend introduced me to HN because I was interested in business and tech, but I didn't really get the appeal of HN for a while. But I remember when I was like 19, browsing HN during my lunch break at my crappy retail job and found this,

https://sofamoolah.com/2011/07/14/the-conclusion-a-6-figure-...

That post at the time got me totally hooked on HN... It was these real world posts about the struggles, successes and failures of normal people starting businesses online with their tech knowledge that I loved.

I literally never see articles like that here anymore. Although, I'm not sure that's just HN... I suspect the world has just changed. Those days when someone could start a successful company from writing some code in their bedroom has more or less gone.

I remember a couple of years back when people were saying how prompt engineering was a skill, and reading this prompt kinda took me back to that.

Were I to guess, the reason the model couldn't do this itself is because most of the time, for most problems, a lot of this is bad advice.

In search optimisation you're often trading between time and quality. A very broad search will return very bad results for a long time. Where as a more depth oriented search with some heuristic will tend to return a pretty good result (if not optimal or close to optimal) quickly.

I'd assume models naturally want to find some middle ground there because that's the best thing to do most of the time, but for very difficult problems where a decent attempt isn't good enough you want a much broader search that doesn't have the time constraints. Much of the prompt seemed to be in that direction – really encouraging broadness of the search, preventing early convergence, and remove pressure of time constraints.