In some cases, workers are also being asked to automate the parts of their jobs they enjoy most, Hinds said on the podcast, pointing to customer-service employees who enjoy building relationships but are increasingly expected to supervise AI agents instead.
"That's what gives you joy and meaning at work," she said. "That is very dangerous."
What's a 20% productivity gain if I constantly feel deflated by work that used to energize me? That's going to give back the productivity gain and more, while also decreasing my quality of life.
This is an important point. My light-bulb moment was when I talked to a product owner in a previous job, and I expressed surprise around an expensive planned change, because it didn't seem that valuable to our customers.
He said, "Almost half of what we do is not that valuable to our customers, but it's valuable to him, and her, and him", pointing through the conference-room window at my fellow programmers, "and that's why we do it. If we only did things that were very valuable to our customers, we wouldn't have nearly as many good engineers on the team as we do."
Do the engineers not derive enjoyment in their jobs from making the customer experience better? This does track with what I've experience in my career, where we've gone from everything being to better the user experience to tech companies sort of trying to out-do each other in their technical solutions while the software continuously gets worse and more antagonistic.
This is the danger of isolating engineering from customers, or even internal customer-interfacing employees.
If all they see is code, they will get satisfaction from tidy code, not user happiness. One good thing about AI is it elevates product engineers because they more directly bridge the customer-product-code divide.
Not just isolating them from customers but also from engineering-adjacent work that isn't code.
I've been at a place that is basically microservices slop (several dozen services per engineer). They're all poorly maintained and at least a solid 40% of all this code that they've written could have been just a traefik or nginx configuration/container.
When you have a lot of inexperienced (relative to industry) and overworked software engineers, the solution to every problem becomes to write code and writing new code should be a last resort.
Worse still, there's just a poor general understanding of the internet protocols they're working with and of how to do distributed systems right. Unfortunately with LLMs I've been seeing this get worse, not better.
They use the LLMs for code generation but not architecture review. Bad ideas are getting fully-baked quickly before anyone with good sense can intervene.
There are plenty of projects that are green lit that have good intent but are bone headed when it comes to solution and implementation. Good engineers hate these types of projects. Good PMs try to avoid these at all costs but sometimes your hand gets forced because some VIP, either internal or external volun-tells you to do it.
I always found pair programming a bit.. hellish. Chatting about things. Rubberducking. Playing code review ping pong. All great. But the feeling of being shoulder surfed killed my ability to play around with the freedom that I do when I'm alone -- and that playing around sometimes led to better/more interesting outcomes than I'd have gotten otherwise.
Yeah, I always bought the premise that it was good for the software, but it didn't work for me as a person, it drained my energy way too fast to spend hours of the day having to be "on" in conversation with another person.
In many ways, I think what's working for me with AI is that it is very similar to pair programming, but without the social-emotional investment required to interact with another person for long periods of time.
A better way to put it is that these things do have value to the customer, the customer just doesn't have a way to understand how the work you're doing provides value because it's the part of the product you don't see. If you clean up technical debt, improve test coverage, improve your deployment systems, etc, it doesn't change the immediate customer experience in a meaningful way, but it does allow you to deliver the changes that customers do see faster and with fewer risks.
This quote makes it seem like the work is self-indulgent, and I have seen that happen sometimes, but it's not half of what we do.
I think this is a larger question we should be asking. YES, we can build this world: a world where robots do our chores, serve our coffee, check us out at the grocery store, and let the AI agents do the parts of our jobs we love.
But SHOULD we? With great power comes great responsibility - and I'm getting the impression we're (quickly) building a world that isn't very fun to live in. We technically have a choice here - DO we want bots writing our prose and responding to our customer service inquiries?
When I was given a semi-ultimatum "use AI or get fired" kind of thing for writing code I had a brief bout of depression/sadness. Whereas my friend doesn't care/says "I get paid to not work". I have gotten past it, now I'm just like, I'll do what I need to do to get paid since unfortunately I'm in a lot of debt so I need this job. I learned to code in 2013 so I like typing the code myself but now it seems like a waste of time. I still write my own code for myself/hardware hobby.
If you're anything like me, and you stay in a coding/dev/IC track for your career because you like the work, you will eventually hit a point where you start thinking it's all meaningless. This happened before AI for me, but AI certainly reinforces it.
You come to a point where you realize that you're not doing anything that creative, or nothing you haven't done hundreds of times before, maybe every few years you switch to whatever new tech stack has gotten popular, but it's fundamentally all the same. And you start to realize that everything you do has a lifespan of a few years, and then you (or probably someone else) will re-do it.
As retirement starts feeling like it is something that will happen sooner than later, you look back and see that almost nothing you've built is still in use, or will be for very long after you're gone.
I hope to retire in about two years. At that point, I plan to not be using any technology or computers in my life for a while, or as little as possible. Maybe at some point I'll rediscover some of the fun I used to have writing programs for myself, but I suspect I'll need a long break before that happens.
I've definitely found what you're describing at bigger companies, but I also previously had experience writing software at smaller non-technology companies.
Legal marketing specifically. Weirdly, my work had more impact, respect and longevity there than the place where I'm a much more senior engineer supposedly directing the work of a whole organization of engineers. I had it better where I was a 1 of 2 than a leader among hundreds.
FWIW, I was just like you but then completely gave in and found enjoyment in the act of simply ideating and shipping. The gap now between idea and implementation is so small. At first I was depressed but now I'm in the acceptance phase of grief. We aren't going back, for better or for worse.
Heh, my employer kept pushing us to use Copilot. And over the last months the cli has actually gotten halfway decent... So I did start using it. Albeit sparingly because the token allotment was always pretty low.
Then they announced that they removed the limit/making further request just cost extra for them. That's when I started using it as I did for my personal projects I pay subscriptions for...
Then Copilot increased their pricing. Announced in April I think? But took effect this month. This Monday they announced that the limits are back in effect. So I guess I'll be going back to hand coding next week, as my tokens are about to run out ಥ ‿ ಥ
Corporate is always so silly. I mean I know how it happens: everyone just wants to get their bonus, so different management roles try to coerce the employees to do whatever best serves their bottomline - rarely related to whatever is good for the corporation... But it's always silly to live through it.
Yeah I definitely agree with this. AI has become very useful to me, but it has also definitely automated some of what used to be my favorite parts of my work.
I am having some success in working to acquire a taste for different parts of the work. But I suspect that this won't be an option for most people.
Most people don’t have jobs they enjoy, programmers have somehow escaped this; better pay and more “protected” time instead of doing what the rest of us were doing all along
I mean that sucks, but I have many tales of people, who were passionate and outstanding in what they did, and were rewarded with a leadership position for their efforts.
Now they get to fill out excel sheets, babysit people and sit in planning meetings.
Where did the 20% number come from? I’d argue it’s way more than that (or variable, i.e. dependent on who’s using it/how it’s being used/what it’s being used on).
Having said that, the number, to me, doesn’t even matter. You could replace that with 200%, and it’d be just as true.
> customer-service employees who enjoy building relationships but are increasingly expected to supervise AI agents instead.
It sucks for the employees, otoh it might be the only way we're going to beat Baumol's Cost Disease.
In the past few decades productivity has exploded, but service employees have largely failed to increase productivity in any way because it's harder to automate these tasks.
It's the reason the costs of things like education and healthcare are downright extortionate, the reason you're paying back your college well into your fifties, the reason you don't call an ambulance for someone in the US because you don't want to ruin their life financially.
We may have to trade the personal fulfillment in these jobs for the broader affordable access to these services.
Education and healthcare are both ridiculously overpriced in the US for reasons that have little to do with service costs. Questionable financial systems behind these services are much more to blame.
>It's the reason the costs of things like education and healthcare are downright extortionate, the reason you're paying back your college well into your fifties, the reason you don't call an ambulance for someone in the US because you don't want to ruin their life financially.
You might wanna think again on that line of reasoning, because plenty of other countries have the same dynamics with respect to service employees, but they don't suffer the very US-only problem of ridiculous education and healthcare costs where calling an ambulance can ruin someones life.
My point is simply this: a person who helps individual customers in any industry isn't much more productive today than they were fifty years ago.
That may change, and it may benefit everyone except the people who get fulfillment in their life from the one-on-one human interaction they get from people who need services.
As a former first responder, I'm interested in hearing more about how AI-powered ambulance services would work. (related question: will the 911 dispatchers be AI?)
I don't think first responders are ever going to be at risk.
Administrators, on the other hand, are a massive part of the costs in the health sector (IIRC the Obama administration chickened out on truly reforming healthcare exactly because the number of administrators that would be made redundant would tank the economy). A significant amount of administrative work can be automated.
The vast majority of jobs are not full-filling or enjoyable. Because there were way more job seekers than jobs.
Programming was one of the ones which was, because there were fewer programmers than openings. Now that's flipping, thus naturally, the enjoyment is going to be sucked out of it.
Many successful people in their 40s could quit work already if they only decreased their monthly costs.
I think it is more important than ever to manage your wealth in a way that sustains you from capital alone in a world where employment gets progressively more toxic.
The way to achieve it is buying maintenance efficient and cheap car, make renovations smart, make good choices all around to minimise expenses.
Operate your life like a corporation. First, cut the expenditures.
For me the ability to do whatever I am interested in at the moment, is worth almost any sacrifice.
Then I can seek one time contracts or short time jobs that fulfil my mental needs.
My monthly expenses are no more than 5000 dollars and mostly consistently less than that.
Which is okay because the money spending doesn’t bring me any joy nowadays. The money isn’t what gives me happiness. Only other people can provide that and activities that are dirt cheap usually, like reading or broadly understood hacking
Consumption is a short lived and deceptive joy that causes more guilt than whatever dopamine it is worth really. Governments hate people like me which means I must be doing something right.
I think that's a very simplistic take, it doesn't account for people who need to support children's education and/or healthcare for parents.
Both are areas where costs are going up at a rate which is much higher than official inflation rates, and comp increases often don't even match inflation!
So the need for working till you're forced to give up still remains.
Most people don't have the luxury of finding joy and meaning in their work. You aren't hired to have fun, you're hired to create value and wealth for your employer. Just do what literally everyone else does and grind through it until you get a pension and hope it's enough to let you die with a bit of dignity.
Here in stupid town we stab ourselves with knives. It hurts and we get infections but everybody does it. We don't even remember why we do it any more but we do so you have to as well.
The real problem is the amount of value that gets left on the table.
Also, mental health is just as much a part of health and well-being as the physical.
We know why we do it. We do it because we live under a system that requires most of us to bleed for our supper. And now tech is being normalized to work like every other job, and techies get to feel the knife. A lot of people are going to be shocked to realize what their actual relationship to capital has always been.
If we know, why would a lot of us be shocked? Seems contradictory.
That's probably too much a troll so while I get that you are grinding your anti-capitalism axe, you're also seeding hopelessness and trapped falsely fatalistic thinking. It has gone this way but it doesn't have to and the whole arrangement is a local optimum with much higher global optima available.
In fact there are many of us who have created a parallel life and extend ladders all the time, within our capacity) for others to join us.
For me it feels less like filling out reports, and more like mentoring an intern who can search for stuff really quickly but forgets everything at the end of the day due to anterograde amnesia.
Except the intern is trapped inside an iron lung and must communicate entirely by text. And also has zero real creativity or self-motivation.
> That's going to give back the productivity gain and more, while also decreasing my quality of life.
Unfortunately though, what does that matter? Your employer does not care how do you feel. You are paid to bring them benefits, they aren't running a charity. If you do feel down, that is your issue and you shouldn't let that influence how you work.
Just to be clear, I don't like that either. But it is what it is.
Driving everyone's QoL to be as bad as possible will lead to increasing enshittiffication in the entire market.
Consumers will be spoiled for choice between deeply mediocre options.
Besides, what's the point of adopting new technologies if it's not to increase the quality of life? If everyone just exists in service of the product development lifecycle, who and what are the products actually for?
In my experience, for every customer support agent that really wants to help people and cares about their problems, there are at least ten who don't even read what you wrote and answer with prefabricated blocks of text that have little to do with what you asked. If AI customer support actually tries to understand what I ask of it and help me, and there are still (motivated) humans available for the more tricky cases that AI can't handle, that might be a win...
I see some similarity to how I felt when library management/wrangling became a huge part of software development.
In the last century I enjoyed crafting my own 'libraries' of functions that I could then use on the projects I worked on. As time went on, there was less and less of a point doing that as the odds rose near to 100% that there was 'a library for that' thing I was working on, so I was encouraged/forced to download it and use it.
It solved problems and was quicker than writing bespoke code (and libraries were hardly a new idea), so the logic was hard to deny, but I enjoyed my job less over time. Now I've risen up the ranks and now code mostly for fun (yes, I use AI to write functions for me) I look at what it must be like to enter the industry and think it all looks very different to how it did when I started.
You could argue that AI has done this much faster than it did in my early career, so people have less of the 'boiling frog' experience I had, and more of a 'sudden shock' to the system.
It's sad, but I've been doing this to other industries all my career, so I can hardly complain.
6 hours a week is low, unless its the average spread across industries. I think I spend more time in Claude Code via the CLI versus any other app I have on my laptop.
Like others said, the frustration is when it gets something so wrong you just think "wow, how'd you mess that up?" but when it gets it right its kind of nice. I also dont like that I basically tell Claude what to do, and then either go to busy work or waste time on the internet.
I kind of enjoy exploring black boxes, trying how different inputs are mapping to differences in outputs. It's kind of like hacking. The problem is, they keep altering the box.
It feels like Greek mythology should have some metaphor for "apparently simple structure that is so complex it leads anybody that studies it into madness". But I can't think of any name to put there.
Working with AI is trying to reduce the probability it'll pick undesirable paths. It's an exercise in trying to avoid what you DON'T want.
I suppose it's the same as asking someone else to take care of a feature and hoping they understand what you have in mind. The difference is that there's a lot of context that's shared between you and a human developer that is simply absent with AI.
I theorise that many social ills come from workers having less pride in their skills and achievements, and a greater sense of social alienation, due to automation.
If you spend countless hours at work, and you partially define yourself by your work, and you realise you are easily replaceable then I cannot imagine this comes without mass social malaise that manifests itself elsewhere.
When you know you're essentially babysitting the workhorse to ensure it doesn't go off the rails, I can't see job satisfaction, and the social consequences of such, increasing.
> I theorise that many social ills come from workers having less pride in their skills and achievements, and a greater sense of social alienation, due to automation.
I agree entirely. Even in an idealistic fully egalitarian post-scarcity society, to truly be happy I think most people would need to do work that they can feel a sense of accomplishment about. The problem is that work at most jobs is increasingly just toil. Any possibility to scrape some tiny flakes of satisfaction out of the toil gets removed, often for no good reason.
You pay per token, even on subscription models the limit is tokens.
If I was valued at 1 trillion dollars, and I was in the hole enough to sink a couple small countries' GDP, maybe I would slowly start to optimize to maximize token usage.
I want to sell tokens, how do I sell more tokens? Not by doing the same work in less tokens, that's for sure.
This is like if you pay me by the hour and then excitedly tell me that you keep paying 10k a month and it's great. I will most certainly not work faster, in this hypothetical, if you tell me you love spending money because it gives you a dopamine rush. I would probably spend a couple more hours REALLY thinking about the task, maybe writing some docs nobody will read, maybe considering multiple options, doing benchmarks, doing research, and then later maybe ill do the actual task as well.
Im not saying these AI companies are scamming us, but the incentives are there and extremely clear. The only thing currently holding it back is that there is some vague kind of competition.
It'd probably still be worth it to make tokens cheaper. Jevons paradox [1] seems to apply here, where making compute cheaper unlocks use cases that were previously priced out, increasing overall demand.
I spend at least 6 hours a week arguing with bots owned by other teams, as I’m unable to reach a human before I bypass their bot. 10k person company, clients are paying for my time.
I've found that setting good guardrails, and running in a sandbox so that the agent doesn't keep asking tedious permission questions, makes things go a LOT smoother.
Generally, I spend anywhere between 15 mins and an hour setting things up (depending on how well the project is set up for AI work), and then set the agent going, coming back in a half-hour to an hour to check its progress. Generally, the tooling keeps it honest (for golang, forbidigo is AWESOME). 80% of the questions the agent asks me require a lot of thought. 20% of what it does needs correction.
The other thing to remember with LLMs is that they are NOT human, and won't react in a human way. So you'll see strikes of "brilliance" followed by the absolutely bizarre. But good guardrails keep that to a minimum.
> sandbox so that the agent doesn't keep asking tedious permission questions
> 80% of the questions the agent asks me require a lot of thought. 20% of what it does needs correction.
I've found even the permissions questions give me veto power over fruitless lines of exploration, especially in planning mode. For instance, it wants to use tools I don't have installed to access information that I have made available elsewhere? I get a chance to override this decision by declining the permissions check and redirecting it. Feels tedious, but helps me understand what information sources are influencing it. I head off a lot of bugs this way.
I never let it go into planning mode, other than to output a plan file that I can audit before giving it the go-ahead to implement. After that I don't want to be bothered, so --dangerously-skip-permissions keeps all but real questions out of the loop, and I can do something else while it works rather than babysit.
AI should be assisting us, instead it's doing the job and it's us being an assistant to it. This is a monumental shift that people seem to be missing in how knowledge working is changing and it's going beyond mere coding.
Guardrails, prompts, whatever, it's us helping it doing the job, not the other way around.
Opus 4.6 was the last genuinely good assistant LLM, but since then it's quite clear that the training/reinforcement is focused "given prompt -> do task" so it's behavior is more and more about doing it itself, not helping you. If you try to use it as an assistant it just sucks and is perma wired into finding the solution. Many times I want it to help me investigate, and his answer will still be focused on the fix, not answering my questions.
4.7 first, 4.8 later and fable are absolute disasters as assistants.
Fable in particular is so "intelligent" that it will push with very strong and intelligent takes even if it is completely wrong.
Wow... Our experiences have been very different, then. I've found each upgrade of Opus to be a noticeable improvement in its complex reasoning and delegation capabilities over its predecessor.
To me, this feels in many ways like a technical manager or team lead's job, where I guide the process along using my knowledge and experience, and then let the agent fill in the rest (to the best of its ability).
The agent can't really learn from its mistakes (at least, not without consuming precious context), so I apply a blameless postmortem process, updating the guardrails whenever it goes astray in the same way more than once.
And really, I'd rather be contemplating the more difficult and interesting questions of architecture, environment, ergonomics and market fit, so it suits me fine.
> Wow... Our experiences have been very different, then. I've found each upgrade of Opus to be a noticeable improvement in its complex reasoning and delegation capabilities over its predecessor.
I haven't stated that it's not more capable nor more "intelligent", it's the opposite.
I will try to expand on what I mean.
LLMs "character/persona/tendencies" are increasingly less about acting as an assistant and more about finding the solution itself.
I use AI in a specific way: he assists, investigates and answers my question. I do the coding. It is increasingly difficult to use it as such, because it quickly jumps into giving me solutions instead of answering my specific questions.
I'll give you few examples.
I asked it to investigate DNS handling details in phoenix emailer module work, he did very little investigation and jumped into why I should've used magic links instead. Instead of assisting me in my research, it was hard wired to solve the problem (the wrong one, with a very wrong solution).
Today at work, I had a problem with batching, I wanted to understand if batching was even needed at all for our use case, and he kept circling around how to fix the batching bug instead. That's not what I asked it to do, yet, it jumped to the "solution".
I am increasingly frustrated by these models "personality" and tendencies that are unhelpful to assist me doing the task at hand and more on it doing it and me merely assisting/supervising.
Sure, very detailed prompting on how he has to act helps, but wait few turns and he drifts again to his default solution vomiting state.
Which makes me think that these models are hard wired on this mode of operation by consistent training and reinforcement of jumping from prompt to code solution.
Ah yes, the agents by default are very "implementation" oriented, which is why I instruct mine to never implement something without formulating a plan first for me to approve.
Another thing they tend to do is rely on their own context -> memories -> training data. And if that's wrong then they'll continue with it until you instruct them to research, after which they usually get the right answer.
I've noticed that the newer models keep track of what you type so as to anticipate what you're likely to say. For example, today Opus 4.8 said "You usually don't want me to commit until you've checked, so the change remains uncommitted."
I think this is just a misunderstanding of how most technology has always worked?
Consider what is happening in most construction sites. The heavy work is absolutely from the technology on site. But without people there to oversee it and keep it working, it would fail.
And that is almost certainly true at any industrial site. Indeed, look up videos of high tech looms. A large portion of the technology added to them are so that the operators can locate the fault and fix it.
AI should be assisting us, instead it's doing the job and it's us being an assistant to it.
If you're a manager and you ask a report to do something and they come back with a question, does that mean you're now their assistant?
I give agents the tasks, I answer their questions, I make choices about the tradeoffs in their plan, I supervise their implementation, I review their output, I have them walk me through things. In what way is this not delegating to them and managing their work, just like a more junior employee?
The problem (okay, one of the problems) with renting other people's models is, as you mentioned, that they can and will change out the model without notifying you ahead of time, and you don't always get to control which model you use. (They might decide to retire it, and you won't be able to get it back if they do).
Which is why (well, part of why) I think the long-term trend will be towards self-hosting models. Right now the frontier models are far enough ahead of the self-hosted ones that there are lots of people willing to pay by the token to rent someone else's model, because they get more value for money from that than from self-hosting models.
But the frontier companies won't be able to keep up their current levels of expenditure forever. At some point the investors are going to say "Hey, so, um, when am I going to see some return on my investment?" and then the current subsidized subscriptions (including the one my employer uses) are going to go away, much like what happened with Copilot this month.
And then the locally-hosted models are going to suddenly look like a more attractive picture. Because where you might have been willing to spend $100/month/employee to rent time on models in someone else's data center, you might suddenly balk at spending $500/month/employee. You might say "Hey, you know what? A $50,000 up-front capital investment is only, what, one month's worth of subscriptions for our 100 employees? Yeah, okay, I'll approve the hardware purchase. Get that self-hosted model set up and then we'll cancel the subscription and switch over."
Not everyone is going to do that. But once the locally-hosted models are good enough, the first few people who do so and report success are going to start a snowball effect. And it will likely be driven by money first, but it will also have the effect, that people will slowly discover, of meaning that you can better predict the model you're using. It will continue to work the same way next year that it is working this year; or if it doesn't, it's because you chose to install the new version.
And when that happens (I'm saying "when", not "if" because although it might take some time, I think it's inevitable in the long run), the frontier-model rental companies are going to struggle to stay afloat. Except for the ones who saw this coming and transitioned to a non-subscription income source somehow (maybe by selling licenses to self-host their frontier models for $$BIGNUM), or who have some other revenue stream besides renting out models.
Well... as a human software engineer, I've been the one with very strong, intelligent, completely wrong takes. The question is, are the LLMs improving faster than you can improve a junior dev? And is their ceiling as high?
Your experience pretty much mirrors my own. I hate to be the 'they're holding it wrong' guy but there's certainly a lot of people out there that have no real idea how to effectively leverage AI.
That’s a problem with the tool not the people. AI is marketed literally as writing one sentence and having some app perfectly output. Just check any of the landing pages for Claude code or codex or GitHub copilot…
No, it literally isn't. I just looked at the landing pages for Claude Code, Codex, Cursor, and Copilot, and literally none of them have anything about "writing one sentence and having some app perfectly output", or anything remotely like that. In fact, just the opposite: they all make clear that they're built for ongoing collaboration with AI, and have detailed descriptions of what that looks like. No one advertising the idea that you can one-shot perfect apps with these tools.
i've seen a number of articles claiming things like "devs self report they'er +x% more productive with AI, but actually they're -y% LESS efficient!". and i think that this is explanation for why.
as a boss (or researcher) i'm going to measure productivity based on amount of output per hour that i'm paying you; as a workers, i'm going to measure productivity based on amount of output relative to the amount of effort i'm putting in.
so what may be happening is that bosses see that output is at 80% (productivity down!) but workers see that they can give that 80% output with 40% effort (productivity up!).
Not sure among devs, but I do know that in other positions in typical corporate bureaucracy, people have a propensity to not report their own automations or productivity gains upward, because the reward structure isn't there.
Early on in my days as a sysadmin, I automated a ton of my role when the rest of the team was still doing ClickOps. The reward for doing so was more work and expectations without the additional pay increase to justify my new found productivity. That happens all over the workforce, and so people will just keep it to themselves. I learned my lesson at that first job real fast that if I'm able to have the same, or greater output, for half the time, I keep that to myself so I can use the automation to free up my own time instead of have it filled by the company.
I wonder how much of that is happening now with AI in non-technical roles.
> so what may be happening is that bosses see that output is at 80% (productivity down!)
If an initiative produces only 80% of the previous results and you’re paying large token bills on top of the same wages, the AI is going to get cut off.
> i've seen a number of articles claiming things like "devs self report they'er +x% more productive with AI, but actually they're -y% LESS efficient!".
Are you thinking of the old METR evals? Their more recent evals showed an actual performance improvement.
The old report is still circulated as bait for AI skeptics.
> so what may be happening is that bosses see that output is at 80% (productivity down!) but workers see that they can give that 80% output with 40% effort (productivity up!).
So why is it that the bosses are the ones that are so enthusiastic about adoption?
Well the obvious is that, monkey-see-monkey-do, and they don't want to miss out. But the insidious externality is that they are the most likely ones (and higher ups) to be invested in nvidia and others, so when they push you to use, it creates a viscous cycle.
My challenge has been trying to manage my higher-level context. I've gotten a pretty good setup where I have project-level orchestrator agents that can spin up workers to implement tasks with minimal oversight, and the resulting work is usually quite good (especially after I give it the mandatory "make the comments less verbose" refining, etc.). But that means I'm doing even more context-switching. I've gotten to the point where I have a half-dozen draft PRs that just need my review before I tag my colleagues, and trying to dig up the context from all of those tasks can be paralyzing.
I just started using Claude Code for my work as a sysadmin. For my work, it's great. I don't need to wrestle with MySQL joins, claude gets even the most complex ones right WAY faster than I would. Same with new Terraform stuff. Things that would have taken me a day are cut to less than an hour.
So for my work, it's made me much better at my job. Much faster and more accurate.
I can write a simple query before Claude finishes reading, querying the semantic layer, checking my files, then writes a query that I have to approve, reads the results, hides them (ctrl+o usually works), and gives me a summary.
We’ve reached this inflection point where it’s faster for me to do most tasks again.
I’m sure fast mode costing more money plays a role.
Personally I find LLMs absolutely terrible at writing Terraform and full of hallucinations. But also Terraform is my bread and butter and our use/workflow is fairly advanced. And we're multi-cloud + baremetal. That wasn't an area where I was going to get a ton of value out of LLMs anyway.
This kind of reminds me of an article that I saw on HN ages back, there's like a subset of office workers who automated their Excel jobs, and just show up to work, read books, and do literally anything, while Excel does their work for them, and they collect their paycheck.
I don't see a lot of talk about how AI development breaks the old feedback loop of write code, watch it run, change it, repeat. I really hate sitting around waiting for the agent to get done planning, reading the plan, then waiting for the agent to get done coding. It's those 5-10 minute windows when its working that really sap my patience and suck all the fun out of our jobs. Writing code by hand is just more fun.
This is something that I don't see discussed a lot in these conversations, but its true for a ton of folks.
I didn't end up with a career in tech because I wanted to tell a bot to do the fun part of my job for me, leaving me only with the boring tedious parts. I didn't sign up to be a full time code reviewer, and I certainly never wanted to be a manager, yet alone a manager of bots.
It also can't help but spark feelings of "Why am I getting paid 6 figures for this??" and that makes me nervous for the future.
I imagine the engineers and assemblers in factories pre-assembly line felt the same when things started getting automated there. There's an element of craftsmanship that gets taken away as the product moves from being artisanal, hand crafted to mass produced.
I wonder if its too late for me to pivot to hardware
Yeah its hard to deny just the raw throughput from the AI. Like it really is doing work in hours that would take me days.
But those times when I had to drop down into a repl and play around with the output of a method. Or try different ways of doing what anyone else would think is boring, like array manipulation - that's a lot of what I actually LIKE to do.
A big part of me just hopes I can hang in there for another... decade, or two. Then I can retire! Maybe.
I think a lot of developers who enjoy writing code are in an internal battle knowing they could write it themselves or AI could do it and probably do at same speed or many times faster. It's a contradiction as a developer because we always want to do whatever it is we are doing at the optimal speeds but we also like writing code. So, you're being forced to choose where you stand at a fundamental level.
For me, AI can sometimes create a false sense of productivity. It's similar to how in the past, people would spend time creating the perfect setup with notion templates, pomodoro timers and productivity tools, or tweaking their environment for maximum productivity, instead of actually doing productive work.
But now it's happening at the company level: "We're going to add a chatbot to increase productivity! Now MCP tools! Then agentic workflows! We’ll add skills, and now productivity will go up! Maybe loops will do it?"
Understanding what is going on with AI productivity is … frustrating to say the least.
The best I can say is that genAI is a self reported a 20% efficiency boost, and for a very (very) small group of people, it’s maybe a 2-3x boost. (And if you are at a frontier lab, you go fly into the big bucket of exceptions)
At this point, for most use cases, AI productivity is either the equivalent of giving people 3D printers, and seeing little benefit, or signing up for an outsourcing service, just without the development of human capital anywhere.
I think it depends on how you measure the boost. If you are talking about generating a first draft then yes, the boost is there. If you’re talking about completing the project in all well tested and architected aspects, then overall there really isn’t a boost.
6 hours of debugging and docs reading is not equal to 6 hours of prompt fiddling. The return of value beyond the few fixes applied will be almost nil from the fiddling.
Yeah, Amazon warehouses are just the same. Humans are only used for tasks beyond the comprehension or physical ability of a machine at that point in time.
The problem is, we haven't had the debate on a societal level if we want to go the star trek route (aka, we give our darn best to automate everything so that humans have the time to do whatever they want) or the realcommunism route (we ward off automation so that we have jobs for people).
The result of that debate not having been made is the third possible outcome - rabid capitalism automates everything as soon as it is profitable and lays off the humans, focusing on getting higher margins out of less people if need be; the best example for that IMHO is Disneyland or Vegas going on ridiculous nickel-and-diming tours. In the end however, there will be no one left any more who has employment and we'll be in for quite the riots.
I don't know what they're complaining about. AI has freed us from the drudgery of craftsmanship, letting us focus on the important stuff—managerial and administrative work!
(There's a reason why I call it the MBA's stone. It transmutes all knowledge work into a problem of management.)
I could care less about bot sitting (haven’t we always written our own automation?), but it’s botsitting the unverified slop that people send you that fuels frustration. I thought I worked with competent people who respected me
Our product lead/manager recently sent me an AI generated PRD (complete with a Claude Code spec!) to build a core feature which we have had for over 2 years (and is a highly used core feature by our customers).
I just can't imagine tanking my trust with my coworkers by doing something like that.
So we're now in this world where everyone is instantly 10x more productive at turning their thoughts into code. Now, think about the coworkers you've had that are middling to mediocre. Do you want them to have a tool that makes them 10x more productive?
That's what I wonder about, what happens to all those folks.
Your coworkers haven't changed. What changed is that people can hand off work they never had to think through themselves. So you don't know what they checked and you don't know what you need to. You just have to read the whole thing.
In some cases, workers are also being asked to automate the parts of their jobs they enjoy most, Hinds said on the podcast, pointing to customer-service employees who enjoy building relationships but are increasingly expected to supervise AI agents instead.
"That's what gives you joy and meaning at work," she said. "That is very dangerous."
What's a 20% productivity gain if I constantly feel deflated by work that used to energize me? That's going to give back the productivity gain and more, while also decreasing my quality of life.
He said, "Almost half of what we do is not that valuable to our customers, but it's valuable to him, and her, and him", pointing through the conference-room window at my fellow programmers, "and that's why we do it. If we only did things that were very valuable to our customers, we wouldn't have nearly as many good engineers on the team as we do."
If all they see is code, they will get satisfaction from tidy code, not user happiness. One good thing about AI is it elevates product engineers because they more directly bridge the customer-product-code divide.
I've been at a place that is basically microservices slop (several dozen services per engineer). They're all poorly maintained and at least a solid 40% of all this code that they've written could have been just a traefik or nginx configuration/container.
When you have a lot of inexperienced (relative to industry) and overworked software engineers, the solution to every problem becomes to write code and writing new code should be a last resort.
Worse still, there's just a poor general understanding of the internet protocols they're working with and of how to do distributed systems right. Unfortunately with LLMs I've been seeing this get worse, not better.
They use the LLMs for code generation but not architecture review. Bad ideas are getting fully-baked quickly before anyone with good sense can intervene.
In many ways, I think what's working for me with AI is that it is very similar to pair programming, but without the social-emotional investment required to interact with another person for long periods of time.
This quote makes it seem like the work is self-indulgent, and I have seen that happen sometimes, but it's not half of what we do.
But SHOULD we? With great power comes great responsibility - and I'm getting the impression we're (quickly) building a world that isn't very fun to live in. We technically have a choice here - DO we want bots writing our prose and responding to our customer service inquiries?
You come to a point where you realize that you're not doing anything that creative, or nothing you haven't done hundreds of times before, maybe every few years you switch to whatever new tech stack has gotten popular, but it's fundamentally all the same. And you start to realize that everything you do has a lifespan of a few years, and then you (or probably someone else) will re-do it.
As retirement starts feeling like it is something that will happen sooner than later, you look back and see that almost nothing you've built is still in use, or will be for very long after you're gone.
I hope to retire in about two years. At that point, I plan to not be using any technology or computers in my life for a while, or as little as possible. Maybe at some point I'll rediscover some of the fun I used to have writing programs for myself, but I suspect I'll need a long break before that happens.
Legal marketing specifically. Weirdly, my work had more impact, respect and longevity there than the place where I'm a much more senior engineer supposedly directing the work of a whole organization of engineers. I had it better where I was a 1 of 2 than a leader among hundreds.
> Jeb: "If everybody's got one of these auto-whatsits, does anybody code anymore?"
> Doc Brown: "Of course we code. But for recreation. For fun."
> Jeb: "Code for fun? What the hell kind of fun is that?"
Then they announced that they removed the limit/making further request just cost extra for them. That's when I started using it as I did for my personal projects I pay subscriptions for...
Then Copilot increased their pricing. Announced in April I think? But took effect this month. This Monday they announced that the limits are back in effect. So I guess I'll be going back to hand coding next week, as my tokens are about to run out ಥ ‿ ಥ
Corporate is always so silly. I mean I know how it happens: everyone just wants to get their bonus, so different management roles try to coerce the employees to do whatever best serves their bottomline - rarely related to whatever is good for the corporation... But it's always silly to live through it.
I am having some success in working to acquire a taste for different parts of the work. But I suspect that this won't be an option for most people.
Now they get to fill out excel sheets, babysit people and sit in planning meetings.
Where did the 20% number come from? I’d argue it’s way more than that (or variable, i.e. dependent on who’s using it/how it’s being used/what it’s being used on).
Having said that, the number, to me, doesn’t even matter. You could replace that with 200%, and it’d be just as true.
It sucks for the employees, otoh it might be the only way we're going to beat Baumol's Cost Disease.
In the past few decades productivity has exploded, but service employees have largely failed to increase productivity in any way because it's harder to automate these tasks.
It's the reason the costs of things like education and healthcare are downright extortionate, the reason you're paying back your college well into your fifties, the reason you don't call an ambulance for someone in the US because you don't want to ruin their life financially.
We may have to trade the personal fulfillment in these jobs for the broader affordable access to these services.
You might wanna think again on that line of reasoning, because plenty of other countries have the same dynamics with respect to service employees, but they don't suffer the very US-only problem of ridiculous education and healthcare costs where calling an ambulance can ruin someones life.
That may change, and it may benefit everyone except the people who get fulfillment in their life from the one-on-one human interaction they get from people who need services.
Administrators, on the other hand, are a massive part of the costs in the health sector (IIRC the Obama administration chickened out on truly reforming healthcare exactly because the number of administrators that would be made redundant would tank the economy). A significant amount of administrative work can be automated.
Programming was one of the ones which was, because there were fewer programmers than openings. Now that's flipping, thus naturally, the enjoyment is going to be sucked out of it.
I think it is more important than ever to manage your wealth in a way that sustains you from capital alone in a world where employment gets progressively more toxic.
The way to achieve it is buying maintenance efficient and cheap car, make renovations smart, make good choices all around to minimise expenses. Operate your life like a corporation. First, cut the expenditures.
For me the ability to do whatever I am interested in at the moment, is worth almost any sacrifice.
Then I can seek one time contracts or short time jobs that fulfil my mental needs.
My monthly expenses are no more than 5000 dollars and mostly consistently less than that.
Which is okay because the money spending doesn’t bring me any joy nowadays. The money isn’t what gives me happiness. Only other people can provide that and activities that are dirt cheap usually, like reading or broadly understood hacking
Consumption is a short lived and deceptive joy that causes more guilt than whatever dopamine it is worth really. Governments hate people like me which means I must be doing something right.
Both are areas where costs are going up at a rate which is much higher than official inflation rates, and comp increases often don't even match inflation!
So the need for working till you're forced to give up still remains.
The real problem is the amount of value that gets left on the table.
Also, mental health is just as much a part of health and well-being as the physical.
That's probably too much a troll so while I get that you are grinding your anti-capitalism axe, you're also seeding hopelessness and trapped falsely fatalistic thinking. It has gone this way but it doesn't have to and the whole arrangement is a local optimum with much higher global optima available.
In fact there are many of us who have created a parallel life and extend ladders all the time, within our capacity) for others to join us.
Except the intern is trapped inside an iron lung and must communicate entirely by text. And also has zero real creativity or self-motivation.
Unfortunately though, what does that matter? Your employer does not care how do you feel. You are paid to bring them benefits, they aren't running a charity. If you do feel down, that is your issue and you shouldn't let that influence how you work.
Just to be clear, I don't like that either. But it is what it is.
Is everyone entitled to a high quality of life?
If not, then who draws the line as to who deserves what benefit in life? You?
Consumers will be spoiled for choice between deeply mediocre options.
Besides, what's the point of adopting new technologies if it's not to increase the quality of life? If everyone just exists in service of the product development lifecycle, who and what are the products actually for?
In the last century I enjoyed crafting my own 'libraries' of functions that I could then use on the projects I worked on. As time went on, there was less and less of a point doing that as the odds rose near to 100% that there was 'a library for that' thing I was working on, so I was encouraged/forced to download it and use it.
It solved problems and was quicker than writing bespoke code (and libraries were hardly a new idea), so the logic was hard to deny, but I enjoyed my job less over time. Now I've risen up the ranks and now code mostly for fun (yes, I use AI to write functions for me) I look at what it must be like to enter the industry and think it all looks very different to how it did when I started.
You could argue that AI has done this much faster than it did in my early career, so people have less of the 'boiling frog' experience I had, and more of a 'sudden shock' to the system.
It's sad, but I've been doing this to other industries all my career, so I can hardly complain.
Like others said, the frustration is when it gets something so wrong you just think "wow, how'd you mess that up?" but when it gets it right its kind of nice. I also dont like that I basically tell Claude what to do, and then either go to busy work or waste time on the internet.
It may be fun to look at inputs and outputs, but it's not hackable and trying to map one into the other is more like astrology than a science.
Maybe the idea of complexity is too modern.
(I spent too long by the horse racing track)
I suppose it's the same as asking someone else to take care of a feature and hoping they understand what you have in mind. The difference is that there's a lot of context that's shared between you and a human developer that is simply absent with AI.
If you spend countless hours at work, and you partially define yourself by your work, and you realise you are easily replaceable then I cannot imagine this comes without mass social malaise that manifests itself elsewhere.
When you know you're essentially babysitting the workhorse to ensure it doesn't go off the rails, I can't see job satisfaction, and the social consequences of such, increasing.
Welcome comrade. https://en.wikipedia.org/wiki/Marx%27s_theory_of_alienation
I agree entirely. Even in an idealistic fully egalitarian post-scarcity society, to truly be happy I think most people would need to do work that they can feel a sense of accomplishment about. The problem is that work at most jobs is increasingly just toil. Any possibility to scrape some tiny flakes of satisfaction out of the toil gets removed, often for no good reason.
If I was valued at 1 trillion dollars, and I was in the hole enough to sink a couple small countries' GDP, maybe I would slowly start to optimize to maximize token usage.
I want to sell tokens, how do I sell more tokens? Not by doing the same work in less tokens, that's for sure.
This is like if you pay me by the hour and then excitedly tell me that you keep paying 10k a month and it's great. I will most certainly not work faster, in this hypothetical, if you tell me you love spending money because it gives you a dopamine rush. I would probably spend a couple more hours REALLY thinking about the task, maybe writing some docs nobody will read, maybe considering multiple options, doing benchmarks, doing research, and then later maybe ill do the actual task as well.
Im not saying these AI companies are scamming us, but the incentives are there and extremely clear. The only thing currently holding it back is that there is some vague kind of competition.
[1] https://en.wikipedia.org/wiki/Jevons_paradox
Generally, I spend anywhere between 15 mins and an hour setting things up (depending on how well the project is set up for AI work), and then set the agent going, coming back in a half-hour to an hour to check its progress. Generally, the tooling keeps it honest (for golang, forbidigo is AWESOME). 80% of the questions the agent asks me require a lot of thought. 20% of what it does needs correction.
The other thing to remember with LLMs is that they are NOT human, and won't react in a human way. So you'll see strikes of "brilliance" followed by the absolutely bizarre. But good guardrails keep that to a minimum.
> 80% of the questions the agent asks me require a lot of thought. 20% of what it does needs correction.
I've found even the permissions questions give me veto power over fruitless lines of exploration, especially in planning mode. For instance, it wants to use tools I don't have installed to access information that I have made available elsewhere? I get a chance to override this decision by declining the permissions check and redirecting it. Feels tedious, but helps me understand what information sources are influencing it. I head off a lot of bugs this way.
AI should be assisting us, instead it's doing the job and it's us being an assistant to it. This is a monumental shift that people seem to be missing in how knowledge working is changing and it's going beyond mere coding.
Guardrails, prompts, whatever, it's us helping it doing the job, not the other way around.
Opus 4.6 was the last genuinely good assistant LLM, but since then it's quite clear that the training/reinforcement is focused "given prompt -> do task" so it's behavior is more and more about doing it itself, not helping you. If you try to use it as an assistant it just sucks and is perma wired into finding the solution. Many times I want it to help me investigate, and his answer will still be focused on the fix, not answering my questions.
4.7 first, 4.8 later and fable are absolute disasters as assistants.
Fable in particular is so "intelligent" that it will push with very strong and intelligent takes even if it is completely wrong.
I have never disliked our job more.
To me, this feels in many ways like a technical manager or team lead's job, where I guide the process along using my knowledge and experience, and then let the agent fill in the rest (to the best of its ability).
The agent can't really learn from its mistakes (at least, not without consuming precious context), so I apply a blameless postmortem process, updating the guardrails whenever it goes astray in the same way more than once.
And really, I'd rather be contemplating the more difficult and interesting questions of architecture, environment, ergonomics and market fit, so it suits me fine.
I haven't stated that it's not more capable nor more "intelligent", it's the opposite.
I will try to expand on what I mean.
LLMs "character/persona/tendencies" are increasingly less about acting as an assistant and more about finding the solution itself.
I use AI in a specific way: he assists, investigates and answers my question. I do the coding. It is increasingly difficult to use it as such, because it quickly jumps into giving me solutions instead of answering my specific questions.
I'll give you few examples.
I asked it to investigate DNS handling details in phoenix emailer module work, he did very little investigation and jumped into why I should've used magic links instead. Instead of assisting me in my research, it was hard wired to solve the problem (the wrong one, with a very wrong solution).
Today at work, I had a problem with batching, I wanted to understand if batching was even needed at all for our use case, and he kept circling around how to fix the batching bug instead. That's not what I asked it to do, yet, it jumped to the "solution".
I am increasingly frustrated by these models "personality" and tendencies that are unhelpful to assist me doing the task at hand and more on it doing it and me merely assisting/supervising.
Sure, very detailed prompting on how he has to act helps, but wait few turns and he drifts again to his default solution vomiting state.
Which makes me think that these models are hard wired on this mode of operation by consistent training and reinforcement of jumping from prompt to code solution.
Another thing they tend to do is rely on their own context -> memories -> training data. And if that's wrong then they'll continue with it until you instruct them to research, after which they usually get the right answer.
I've noticed that the newer models keep track of what you type so as to anticipate what you're likely to say. For example, today Opus 4.8 said "You usually don't want me to commit until you've checked, so the change remains uncommitted."
Consider what is happening in most construction sites. The heavy work is absolutely from the technology on site. But without people there to oversee it and keep it working, it would fail.
And that is almost certainly true at any industrial site. Indeed, look up videos of high tech looms. A large portion of the technology added to them are so that the operators can locate the fault and fix it.
If you're a manager and you ask a report to do something and they come back with a question, does that mean you're now their assistant?
I give agents the tasks, I answer their questions, I make choices about the tradeoffs in their plan, I supervise their implementation, I review their output, I have them walk me through things. In what way is this not delegating to them and managing their work, just like a more junior employee?
Which is why (well, part of why) I think the long-term trend will be towards self-hosting models. Right now the frontier models are far enough ahead of the self-hosted ones that there are lots of people willing to pay by the token to rent someone else's model, because they get more value for money from that than from self-hosting models.
But the frontier companies won't be able to keep up their current levels of expenditure forever. At some point the investors are going to say "Hey, so, um, when am I going to see some return on my investment?" and then the current subsidized subscriptions (including the one my employer uses) are going to go away, much like what happened with Copilot this month.
And then the locally-hosted models are going to suddenly look like a more attractive picture. Because where you might have been willing to spend $100/month/employee to rent time on models in someone else's data center, you might suddenly balk at spending $500/month/employee. You might say "Hey, you know what? A $50,000 up-front capital investment is only, what, one month's worth of subscriptions for our 100 employees? Yeah, okay, I'll approve the hardware purchase. Get that self-hosted model set up and then we'll cancel the subscription and switch over."
Not everyone is going to do that. But once the locally-hosted models are good enough, the first few people who do so and report success are going to start a snowball effect. And it will likely be driven by money first, but it will also have the effect, that people will slowly discover, of meaning that you can better predict the model you're using. It will continue to work the same way next year that it is working this year; or if it doesn't, it's because you chose to install the new version.
And when that happens (I'm saying "when", not "if" because although it might take some time, I think it's inevitable in the long run), the frontier-model rental companies are going to struggle to stay afloat. Except for the ones who saw this coming and transitioned to a non-subscription income source somehow (maybe by selling licenses to self-host their frontier models for $$BIGNUM), or who have some other revenue stream besides renting out models.
Are you getting LLMsplained? :)
as a boss (or researcher) i'm going to measure productivity based on amount of output per hour that i'm paying you; as a workers, i'm going to measure productivity based on amount of output relative to the amount of effort i'm putting in.
so what may be happening is that bosses see that output is at 80% (productivity down!) but workers see that they can give that 80% output with 40% effort (productivity up!).
Early on in my days as a sysadmin, I automated a ton of my role when the rest of the team was still doing ClickOps. The reward for doing so was more work and expectations without the additional pay increase to justify my new found productivity. That happens all over the workforce, and so people will just keep it to themselves. I learned my lesson at that first job real fast that if I'm able to have the same, or greater output, for half the time, I keep that to myself so I can use the automation to free up my own time instead of have it filled by the company.
I wonder how much of that is happening now with AI in non-technical roles.
If an initiative produces only 80% of the previous results and you’re paying large token bills on top of the same wages, the AI is going to get cut off.
> i've seen a number of articles claiming things like "devs self report they'er +x% more productive with AI, but actually they're -y% LESS efficient!".
Are you thinking of the old METR evals? Their more recent evals showed an actual performance improvement.
The old report is still circulated as bait for AI skeptics.
So why is it that the bosses are the ones that are so enthusiastic about adoption?
So for my work, it's made me much better at my job. Much faster and more accurate.
I can write a simple query before Claude finishes reading, querying the semantic layer, checking my files, then writes a query that I have to approve, reads the results, hides them (ctrl+o usually works), and gives me a summary.
We’ve reached this inflection point where it’s faster for me to do most tasks again.
I’m sure fast mode costing more money plays a role.
This is something that I don't see discussed a lot in these conversations, but its true for a ton of folks.
I didn't end up with a career in tech because I wanted to tell a bot to do the fun part of my job for me, leaving me only with the boring tedious parts. I didn't sign up to be a full time code reviewer, and I certainly never wanted to be a manager, yet alone a manager of bots.
It also can't help but spark feelings of "Why am I getting paid 6 figures for this??" and that makes me nervous for the future.
I imagine the engineers and assemblers in factories pre-assembly line felt the same when things started getting automated there. There's an element of craftsmanship that gets taken away as the product moves from being artisanal, hand crafted to mass produced.
I wonder if its too late for me to pivot to hardware
But those times when I had to drop down into a repl and play around with the output of a method. Or try different ways of doing what anyone else would think is boring, like array manipulation - that's a lot of what I actually LIKE to do.
A big part of me just hopes I can hang in there for another... decade, or two. Then I can retire! Maybe.
I’m rooting for two! :-)
It's actually kinda pleasant, especially when I consider all the tickets I'm not excited about doing. It's prob worth focusing on that aspect of it.
But now it's happening at the company level: "We're going to add a chatbot to increase productivity! Now MCP tools! Then agentic workflows! We’ll add skills, and now productivity will go up! Maybe loops will do it?"
The best I can say is that genAI is a self reported a 20% efficiency boost, and for a very (very) small group of people, it’s maybe a 2-3x boost. (And if you are at a frontier lab, you go fly into the big bucket of exceptions)
At this point, for most use cases, AI productivity is either the equivalent of giving people 3D printers, and seeing little benefit, or signing up for an outsourcing service, just without the development of human capital anywhere.
6 hours of debugging and docs reading is not equal to 6 hours of prompt fiddling. The return of value beyond the few fixes applied will be almost nil from the fiddling.
Welcome to the factory!
The problem is, we haven't had the debate on a societal level if we want to go the star trek route (aka, we give our darn best to automate everything so that humans have the time to do whatever they want) or the realcommunism route (we ward off automation so that we have jobs for people).
The result of that debate not having been made is the third possible outcome - rabid capitalism automates everything as soon as it is profitable and lays off the humans, focusing on getting higher margins out of less people if need be; the best example for that IMHO is Disneyland or Vegas going on ridiculous nickel-and-diming tours. In the end however, there will be no one left any more who has employment and we'll be in for quite the riots.
(There's a reason why I call it the MBA's stone. It transmutes all knowledge work into a problem of management.)
I’ve been told before.
This is all normal. It’s also well worth the time spent learning
I just can't imagine tanking my trust with my coworkers by doing something like that.
That's what I wonder about, what happens to all those folks.
Managers will be sure to tell you how much they respect you. Ask them if they respect the work and you'll get a blank stare.