People speak in relative terms and hear in absolutes. Engineers will never completely vanish, but it will certainly feel like it if labor demand is reduced enough.
Technically, there’s still a horse buggy whip market, an abacus market, and probably anything else you think technology consumed. It’s just a minuscule fraction of what it once was.
> Treat AI as force multiplication for your highest-judgment people. The ones who can design systems, navigate ambiguity, shape strategy, and smell risk before it hits. They’ll use AI to move faster, explore more options, and harden their decisions with better data.
Clever pitch. Don't alienate all the people who've hitched their wagons to AI, but push valuing highly-skilled ICs as an actionable leadership insight.
Incidentally, strategy and risk management sound like a pay grade bump may be due.
> The bottleneck isn’t code production, it is judgment.
It always surprises me that this isn't obvious to everyone. If AI wrote 100% of the code that I do at work, I wouldn't get any more work done because writing the code is usually the easy part.
I think it depends on the sort of work you do. We had some hubspot integration which hadn't been touched for three years break. Probably because someone at hubspot sunset their v1 api a few weeks too early... Our internal AI tool that I've build my own agents on updated our data transfer service to use the v3 api. It also added typing, but kept the rather insane way of delivering the data since... well... since it's worked fine for 3 years. It's still not a great piece of software that runs for us. It's better now than it was yesterday though and it'll now go back to just delivering business value in it's extremely imperfect form.
All I had to do was a two line prompt, and accept the pull request. It probably took 10 minutes out of my day, which was mostly the people I was helping explaining what they thought was wrong. I think it might've taken me all day if I had to go through all the code and the documentation and fixed it. It might have taken me a couple of days because I probably would've made it less insane.
For other tasks, like when I'm working on embedded software using AI would slow me down significantly. Except when the specifications are in German.
Sometimes people who don't work in software seem surprised that I don't type faster than I do given my line of work, and I explain to them that typing speed is never the bottleneck in the work that I do. I don't pretend to know for sure if this holds true for every possible software job but it's not a concept I've seen surprise many software engineers. This almost seems like the next level of that; they certainly do more than just write code I want faster, but except for problems where I have trouble figuring out how to express what I want in code, they're not necessarily the solution to any problem I have.
If they could write exactly what I wanted but faster, I'd probably stop writing code any other way at all because that would just be a free win with no downside even though the win might be small! They don't write exactly what I want though, so the tradeoff is whether the amount of time they save me writing it is lost from the extra time debugging the code they wrote rather than my own. It's not clear to me that the code produced by an LLM right now is going to be close enough to correct enough of the time that this will be a net increase in efficiency for me. Most of the arguments I've seen for why I might want to consider investing more of my own time into learning these tools seem to be based on extrapolation of trends to up to this point, but it's still not clear to me that it's likely that they'll become good enough to reach a positive ROI for me any time soon. Maybe if the effort to actually start using them more heavily was lower I'd be willing to try it, but from what I can tell, it would take a decent amount of work for me to get the point where I'm even producing anything close to what I'm currently producing, and I don't really see the point of doing that if it's still an open question if it will ever close the remaining gap.
Something about the way the article sets up the conversation nags at me a bit - even though it concludes with statements and reasoning I generally agree quite well with. It sets out what it wants to argue clearly at the start:
> Everyone’s heard the line: “AI will write all the code; engineering as you know it is finished... The Bun acquisition blows a hole in that story.”
But what the article actually discusses and demonstrates by the end of the article is how the aspects of engineering beyond writing the code is where the value in human engineers is at this point. To me that doesn't seem like an example of a revealed preference in this case. If you take it back to the first part of the original quote above it's just a different wording for AI being the code writer and engineering being different.
I think what the article really means to drive against is the claim/conclusion "because AI can generate lots of code we don't need any type of engineer" but that's just not what the quote they chose to set out against is saying. Without changing that claim the acquisition of Bun is not really a counterexample, Bun had just already changed the way they do engineering so the AI wrote the code and the engineers did the other things.
While I agree with the premise of the article, even if it was a bit shallow, this claim made at the beginning is also still true:
> Everyone’s heard the line: “AI will write all the code; engineering as you know it is finished.”
Software engineering pre-LLMs will never, ever come back. Lots of folks are not understanding that. What we're doing at the end of 2025 looks so much different than what we were doing at the end of 2024. Engineering as we knew it a year or two ago will never return.
I use AI as a smart auto complete - I’ve tried multiple tools on multiple models and I still _regularlt_ have it dump absolute nonsense into my editor - in thr best case it’s gone on a tangent, but in the most common case it’s assumed something (often times directly contradicting what I’ve asked it to do), gone with it, and lost the plot along the way. Of course when I correct it it says “you’re right, X doesn’t exist so we need to do X”…
Has it made me faster? Yes. Had it changed engineering - not even close. There’s absolutely no world where I would trust what I’ve seen out of these tools to run in the real world even with supervision.
Unfortunately this is a skill issue. And it's a totally different skill than reading and writing code, building solid systems, and general software engineering at large. That is annoying, but where we're currently at.
Assume you're writing code manually, and you personally make a mistake. It's often worthwhile to create a mechanism that prevents that class of mistake from cropping up again. Adding better LSP or refactoring support to your editor, better syntax highlighting, better type checking, etc.
That same exact game of whack a mole now has to be done for you and whatever agent you're building with. Some questions to ask: What caused the hallucination? Did you have the agent lay out its plan before it writes any code? Ask you questions and iterate on a spec before implementation? Have you given it all of the necessary tools, test harnesses, and context it needs to complete a request that you've made to it? How do you automate this so that it's impossible for these pieces to be missing for the next request? Are you using the right model for the task at hand?
I disagree with this article and what it attempts to do: frame the acquisition using a conjecture. The only thing to “believe” are the authors reasons - which are flimsy, because they are the very thing we need to be critical of.
I don’t know why the acquisition happened, or what the plans are. But it did happen, and for this we don’t have to suspend disbelief. I don’t doubt Anthropic has plans that they would rather not divulge. This isn’t a big stretch of imagination, either.
We will see how things play out, but people are definitely being displaced by AI software doing work, and people are productive with them. I know I am. The user count of Claude Code, Gemini and ChatGPT don’t lie, so let’s not kid ourselves.
Do people reading this post not understand that this is the output of a prompt like 'analyze <event> with <perspective> arriving at <conclusion>'? Tighten up your epistemology if you're arguing with an author who isn't there.
20 comments
[ 3.6 ms ] story [ 43.8 ms ] threadTechnically, there’s still a horse buggy whip market, an abacus market, and probably anything else you think technology consumed. It’s just a minuscule fraction of what it once was.
Clever pitch. Don't alienate all the people who've hitched their wagons to AI, but push valuing highly-skilled ICs as an actionable leadership insight.
Incidentally, strategy and risk management sound like a pay grade bump may be due.
It always surprises me that this isn't obvious to everyone. If AI wrote 100% of the code that I do at work, I wouldn't get any more work done because writing the code is usually the easy part.
Imperfectly fixing obvious problems in our processes could gain us 20%, easy.
Which one are we focusing on? AI. Duh.
All I had to do was a two line prompt, and accept the pull request. It probably took 10 minutes out of my day, which was mostly the people I was helping explaining what they thought was wrong. I think it might've taken me all day if I had to go through all the code and the documentation and fixed it. It might have taken me a couple of days because I probably would've made it less insane.
For other tasks, like when I'm working on embedded software using AI would slow me down significantly. Except when the specifications are in German.
If they could write exactly what I wanted but faster, I'd probably stop writing code any other way at all because that would just be a free win with no downside even though the win might be small! They don't write exactly what I want though, so the tradeoff is whether the amount of time they save me writing it is lost from the extra time debugging the code they wrote rather than my own. It's not clear to me that the code produced by an LLM right now is going to be close enough to correct enough of the time that this will be a net increase in efficiency for me. Most of the arguments I've seen for why I might want to consider investing more of my own time into learning these tools seem to be based on extrapolation of trends to up to this point, but it's still not clear to me that it's likely that they'll become good enough to reach a positive ROI for me any time soon. Maybe if the effort to actually start using them more heavily was lower I'd be willing to try it, but from what I can tell, it would take a decent amount of work for me to get the point where I'm even producing anything close to what I'm currently producing, and I don't really see the point of doing that if it's still an open question if it will ever close the remaining gap.
> Everyone’s heard the line: “AI will write all the code; engineering as you know it is finished... The Bun acquisition blows a hole in that story.”
But what the article actually discusses and demonstrates by the end of the article is how the aspects of engineering beyond writing the code is where the value in human engineers is at this point. To me that doesn't seem like an example of a revealed preference in this case. If you take it back to the first part of the original quote above it's just a different wording for AI being the code writer and engineering being different.
I think what the article really means to drive against is the claim/conclusion "because AI can generate lots of code we don't need any type of engineer" but that's just not what the quote they chose to set out against is saying. Without changing that claim the acquisition of Bun is not really a counterexample, Bun had just already changed the way they do engineering so the AI wrote the code and the engineers did the other things.
This argument requires us to believe that AI will just asymptote and not get materially better.
Five years from now, I don't think anyone will make these kinds of acquisitions anymore.
I assume this is at least partially a response to that. They wouldn't buy a company now if it would actually happen that fast.
> Everyone’s heard the line: “AI will write all the code; engineering as you know it is finished.”
Software engineering pre-LLMs will never, ever come back. Lots of folks are not understanding that. What we're doing at the end of 2025 looks so much different than what we were doing at the end of 2024. Engineering as we knew it a year or two ago will never return.
I use AI as a smart auto complete - I’ve tried multiple tools on multiple models and I still _regularlt_ have it dump absolute nonsense into my editor - in thr best case it’s gone on a tangent, but in the most common case it’s assumed something (often times directly contradicting what I’ve asked it to do), gone with it, and lost the plot along the way. Of course when I correct it it says “you’re right, X doesn’t exist so we need to do X”…
Has it made me faster? Yes. Had it changed engineering - not even close. There’s absolutely no world where I would trust what I’ve seen out of these tools to run in the real world even with supervision.
Assume you're writing code manually, and you personally make a mistake. It's often worthwhile to create a mechanism that prevents that class of mistake from cropping up again. Adding better LSP or refactoring support to your editor, better syntax highlighting, better type checking, etc.
That same exact game of whack a mole now has to be done for you and whatever agent you're building with. Some questions to ask: What caused the hallucination? Did you have the agent lay out its plan before it writes any code? Ask you questions and iterate on a spec before implementation? Have you given it all of the necessary tools, test harnesses, and context it needs to complete a request that you've made to it? How do you automate this so that it's impossible for these pieces to be missing for the next request? Are you using the right model for the task at hand?
I don’t know why the acquisition happened, or what the plans are. But it did happen, and for this we don’t have to suspend disbelief. I don’t doubt Anthropic has plans that they would rather not divulge. This isn’t a big stretch of imagination, either.
We will see how things play out, but people are definitely being displaced by AI software doing work, and people are productive with them. I know I am. The user count of Claude Code, Gemini and ChatGPT don’t lie, so let’s not kid ourselves.