I hope your recycling is net carbon neutral as well. Example: how much CO2 is released by a recycling program which sends big diesel trucks all over the city to collect recyclables including cardboard, sorting that cardboard at a facility, shipping a small fraction of that to a pulp recycling facility and making recycled cardboard from the post-consumer captured pulp? Consider the alternative to be: torching the cardboard at the endpoint of use - direct conversion to CO2 without the additional steps.

Don’t forget: new from pulpwood cardboard also is contributing to (temporary) carbon capture by growing the pulpwood trees which also provides groundwater recharge and wildlife habitat on the pulpwood tree farms - instead of the pavement, concrete, steel, electricity and fuel consumption of the recycling process.

maybe the resulting future is that the tools can only work with really popular libraries that have lots of people talking about them on stack overflow in the year 2024 or whatever, and new smaller potentially interesting libraries will have a harder time seeing adoption

Yeah, that’s the future I’ve been living since about 2005. The alternative to letting the world be your support desk via stack overflow and similar is to develop killer examples and API documentation for your own libraries so the AI (and everyone else) can learn from that. Qt was a great example of this starting in the early 2000s.

The dark future is where you have competitors “poisoning the well” spreading false information about your tech in the normally reliable channels, then having AI amplify that for them. This, too, is already happening to some extent - more in the political sphere than the technical space, but it’s everywhere to some extent.

Another way of looking at this: A “Daily AI Habit” on your table is about the same as driving a Tesla 10 miles, or a standard gas car about 3 miles.

Edit 4 AI videos, or detour and take the scenic route home from work… about the same impact.

I was “there” with Claude as you describe about 3 months ago. Since then, Claude has stepped up to being able to create fully functional microservices. It helps if you completely specify what you want, it helps if you don’t specify funky libraries or other tech that has poor support on the internet, it helps if your total ask amounts to 1000 lines of code or less - but I have gotten up around 3000 lines before Sonnet 4 choked a few times.

Before this, my AI queries were mostly limited to specific API function call syntax, and they would only be right about 2/3 of the time, which beats randomly trying things myself until I eventually guess the right variation… Yes, it’s better to consult the documentation - when it’s available - it’s not always available.

“AI” and related tech does a lot of useful translation work. It translates speech to text, one language to another, maybe skilled people can do these jobs more elegantly and correctly, but certainly not more cheaply.

I’ve also switched from plastic straws to paper,

The baby turtles thank you.

300,000 liters of jet fuel to send one 747 across the Atlantic Ocean - one time.

The statement strikes me as overblown extreme position staking.

I use AI in my work, not every day, not even every week, but once in a while I’ll run 20-30 queries in a multi-hour session. At the estimated 2Wh per query, that puts my long day of AI code work at 60Wh.

By comparison, driving an electric car consumes approximately 250Wh per mile. So… my evil day spent coding with AI has burned as much energy as a 1/4 mile of driving a relatively efficient car, something that happens every 15 seconds while cruising down the highway…

In other words, my conscience is clear about my personal AI energy usage, and my $20/month subscription fee would seem to amply pay for all the power consumed and then some.

Now, if you want to talk about the massive data mining operations taking place at global-multinational corporations, especially those trolling the internet to build population profiles for their own advantages and profit… that’s a very different scale than one person tapping away at a keyboard. Do they scale up to the same energy usage as the 12 million gallons of jet fuel burned hourly by the air travel (and cargo) industries? Probably not yet.

9.6kWh of energy in a gallon of jet fuel, so just jet fuel consumption is burning over 115 Gigawatts on average, 24-7-365.

This notion that healthy adults need mental herding is very pervasive

Need is a strong word, but it is very true that the environment you put people in will influence their behavior. Grocery stores filled with attractively packaged highly processed foods will drive more highly processed food consumption than if you had to show proof of age ID and sign a disclosure before being allowed into the back room to buy those same foods in plain brown wrapper containers blazoned with all the health warnings that apply to them.

Handheld screen tech delivers dopamine release as powerful as most recreational drugs / experiences. People are definitely “herded” by how that tech is delivered, default settings that most of them never take the time to learn how to change, other settings that annoyingly constantly reset themselves to undesired PAY ATTENTION TO ME configurations, etc.

So, yeah, mindfulness of how your devices are shaping your behavior is a “higher level of awareness” that we as a society should be collectively trying to attain.

If you’re talking about India / China working for US firms, it’s supply and demand again.

It’s clearly not. Otherwise, we wouldn’t have a software guy left standing inside the US.

India / China can do a lot of things. For my company, they’re very strong in terms of producing products for their domestic market. They’re not super helpful per-capita on the US market oriented tasks, but they’re cheap - so we try to use them where we can.

There’s not a lot of good US software employees standing around unemployed… A lot of what I have interviewed as “available” are not even as good as what we get from India, but we have a house full of good developers already.

That’s just a bad business.

While I might reflexively agree, you have to ask yourself: from what perspective? Their customers may not be the happiest with the quality of the product, but for some reason they keep buying it and the business keeps expanding and making more and more profit as the years go by… in my book that’s a better business than the upstanding shop I worked for for 12 years that eventually went bust because we put too much effort into making good stuff through hiring good people to make it, and not enough effort into selling the stuff so we could continue to operate.

Same. My “smartphone” usage is about 10% phone, 10% SMS service, 10% camera, 5% flashlight, 10% GPS + Map tool, 15% e-mail, and 40% web browser… I carried a pretty capable flip phone from 2006-2013, the things I liked best about it were its longevity and its long battery life (up to a week on standby, 3-4 days even with normal usage.) However, even upgraded with GPS capability, the small screen would have made for a poor map experience, and e-mail and web browser were just out of its practical reach.

Stop browsing social media, maybe install Tor if you want that level of privacy - Smartphones can do that…

You’ll need to explain why all the overseas contractors are getting paid so much less, in that case.

If you’re talking about India / China working for US firms, it’s supply and demand again. Indian and Chinese contractors provide a certain kind of value, while domestic US direct employees provide a different kind of value - as you say: ease of communication, time zone, etc. The Indians and Chinese have very high supply numbers, if they ask for more salary they’ll just be passed over for equivalent people who will do it for less. US software engineers with decades of experience are in shorter supply, and higher demand by many US firms, so…

Of course there’s also a huge amount of inertia in the system, which I believe is a very good thing for stability.

But then the boom busted and those salaries deflated down to the $50k range.

And that was a very uneven thing, but yes: starting salaries on the open market did deflate after .com busted. Luckly, I was in a niche where most engineers were retained after the boom and inertia kept our salaries high.

$200K for remedial code cleanup should be a transient phenomenon, when national median household income hovers around $50-60K. With good architecture and specification development, AI can do your remedial code cleanup now, but you need that architecture and specification skill…

I’ve watched businesses lose clients - I even watched a client go bankrupt - from bad coding decisions.

I interviewed with a shop in a University town that had a mean 6 month turnover rate for programmers, and they paid the fresh-out of school kids about 1/3 my previous salary. We were exploring the idea of me working for them for 1/2 my previous salary, basically until I found a better fit. Ultimately they decided not to hire me with the stated reason not being that my salary demands were too high, but that I’d just find something better and leave them. Well… my “find a new job in this town” period runs 3-6 months even when I have no job at all, how can you lose anything when you burn through new programmers every 6 months or less? I believe the real answer was that they were afraid I might break their culture, start retaining programmers and building up a sustained team like in the places I came from, and they were making plenty of money doing things the way they had been doing them for 10 years so far…

it’s a dangerous game I see a few other businesses executing without caution or comparable results.

From my perspective, I can do what needs doing without AI. Our whole team can, and nobody is downsizing us or demanding accelerated schedules. We are getting demands to keep the schedules the same while all kinds of new data privacy and cybersecurity documentation demands are being piled on top. We’re even getting teams in India who are allegedly helping us to fulfill those new demands, and I suppose when the paperwork in those areas is less than perfect we can “retrain” India instead of bringing the pain home here. Meanwhile, if AI can help to accelerate our normal work, there’s plenty of opportunity for exploratory development of new concepts that’s both more fun for the team and potentially profitable for the company. If AI turns out to be a bust, most engineers on this core team have been supporting similar products for 10-20 years… we handled it without AI before…

If you can’t hold on to them once they have experience, that’s a you problem.

I work at a large multi-national corp with competitive salaries, benefits, excellent working conditions, advancement opportunities, etc. I still have watched promising junior engineers hit the door just when they were starting to be truly valuable contributors.

you can have a shitty AI that will never grow beyond a ‘new hire.’

So, my perspective on this is that : over the past 12 months, AI has advanced more quickly than all the interns and new hires I have worked with over the past 3 decades. It may plateau here in a few months, even if it does it’s already better than half of the 2 year experienced software engineers I have worked with, at least at writing code based on natural language specs provided to it.

The future problem, though, is that without the experience of being a junior dev, where do you think senior devs come from?

And I absolutely agree, the junior dev pipeline needs to stay full, because writing code is less than half of the job. Knowing what code needs writing is a huge part of it, crafting implementable and testable requirements, learning the business and what is important to the business, that has always been more than half of my job when I had the title “Software Engineer”.

the world suffocated under the energy requirements of doing everything poorly.

While I sympathize, the energy argument is a pretty big red herring. What’s the energy cost of a human software engineer? They have a home that has to be built, maintained, powered, etc. Same for their transportation which is often a privately owned automobile, driving on roads that have to be built and maintained. They have to eat, they need air conditioning, medical care, dental care, clothes, they have children who need to spend 20 years in school, they take vacations on cruise ships or involving trans-oceanic jet travel… add up all that energy and divide it by their productive output writing code for their work… if AI starts helping them write that code even 2x faster, the energy consumed by AI is going to be trivial compared to the energy consumed by the software engineer per unit of code produced, even if producing code is only 20% of their total job.

I would say the same goes for Doctors, Teachers, Politicians, etc. AI is not going to replace 100% of any job, but it may be dramatically accelerating 30% or more of many of them, and that increase in productivity / efficiency / accuracy is going to pay off in terms of fewer ProfessionX required to meet demands and/or ProfessionX simply serving the world better than they used to.

My sister in law was a medical transcriptionist - made good money, for a while. Then doctors replaced her with automatic transcriptionists, essentially the doctors quit outsourcing their typing work to humans and started trusting machines to do it for them. All in all, the doctors are actually doing more work now than they did before when they had human transcriptionists they could trust, because now they are have the AI transcription that they need to check more closely for mistakes than they did their human transcriptionists, but the cost differential is just too big to ignore. That’s a job that was “eliminated” by automation, at least 90% or more in the last 20 years. But, it was really a “doctor accessory” job, we still have doctors, even though they are using AI assistants now…

Agreed… however:

The theory is that the new hire gets better over time as they learn the ins and outs of your business and your workplace style.

The practice is that over half of them move on to “other opportunities” within a couple of years, even if you give them good salary, benefits and working conditions.

And they’re commanding an $80k/year salary because they need to live in a country that demands an $80k/year cost of living

Not in the US. In the US they’re commanding $80k/yr because of supply and demand, it has very little to do with cost of living. I suppose when you get supply so high / demand so low, you eventually hit a floor where cost of living comes into play, but in many high supply / low demand fields that doesn’t happen until $30k/yr or even lower… Case in point: starting salaries for engineers in the U.S. were around $30-40k/yr up until the .com boom, at which point software engineering capable college graduates ramped up to $70k/yr in less than a year, due to demand outstripping supply.

stuffing your codebase with janky nonsense

Our codebase had plenty of janky nonsense before AI came around. Just ask anyone: their code is great, but everyone else’s code is a bunch of janky nonsense. I actually have some hope that AI generated code may improve to a point where it becomes at least more intelligible to everyone than those other programmers’ janky nonsense. In the past few months I have actually seen Anthropic/Claude’s code output improve significantly toward this goal.

Long term, its a death sentence.

Definitely is, the pipeline should continue to be filled and dismissing seasoned talent is a mistake. However, I suspect everyone in the pipeline would benefit from learning to work with the new tools, at least the “new tools” in a year or so, the stuff I saw coming out of AI a year ago? Not really worthwhile at that time, but today it is showing promise - at least at the microservice level.

Yes, this is the cost of training, and it is high, but also necessary if you are going to maintain a high level of capability in house.

Management loves the idea of outsourcing, my experience of outsourcing is that the ultimate costs are far higher than in house training.

while firing the rest of their dev team

That’s the complete mistake right there. AI can help code, it can’t replace the organizational knowledge your team has developed.

Some shops may think they don’t have/need organizational knowledge, but they all do. That’s one big reason why new hires take so long to start being productive.

Same, and AI isn’t as frustrating to deal with when it can’t do what it was hired for and your manager needs you to now find something it can do because the contract is funded…

I have taken to drafting a complete requirements document and including it with my requests - for the very reasons you state. it seems to help.

I am a firm believer in rubber ducky debugging, but AI is clearly better than the rubber duck. You don’t depend on either to do it for you, but as long as you have enough self-esteem to tell AI to stick it where the sun don’t shine when you know it’s wrong, it can help accelerate small tasks from a few hours down to a few minutes.

Trusting any new code blindly is foolish, even if you’re paying a senior dev $200K/yr for it, it should be reviewed and understood by other team members before accepting it. Same is true for an LLM, but of course most organizations never do real code reviews in either scenario…

20ish years ago, I was a proponent of pair programming. It’s not for everyone. It’s not for anyone 40 hours a week, but in appropriate circumstances for a few hours at a session it can be hugely beneficial. It’s like a real-time code review during development. I see that pair programming is as popular today as it was back then, maybe even less so, but… “Vibe coding” with LLMs in chat mode? That can be a very similar experience, up to a point.