5 ms·

Believe the Checkbook

171 points by rg81 9mo ago

hapless 9mo ago
The ten dollar word for this is “revealed preferences”
- recursive 9mo ago
  I learned that phrase from one of the bold sentences in this article.
conductr 9mo ago
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.
- marcosdumay 9mo ago
  > but it will certainly feel like it if labor demand is reduced enough All the last productivity multipliers in programming led to increased demand. Do you really think the market is saturated now? And what saturated it is one of the least impactful "revolutionary" tools we got in our profession? Keep in mind that looking at statistics won't lead to any real answer, everything is manipulated beyond recognition right now.
  - conductr 9mo ago
    Demand for software has been tied to demand for software engineering labor. That is no longer true. So demand for software may still go up while demand for labor goes another direction. Also I do hold a belief that most tech companies are taking a cost/labor reduction strategy for a reason, and I think that’s because we’re closing a period of innovation. Keeping the lights on, or protecting their moats, requires less labor.
  - 9rx 9mo ago
    Each of the last productivity multipliers coincided with greatly expanded markets (e.g. PC revolution, internet, mobile). Those are at the saturation point. And we've effectively built all the software those things need now. Of course there is still room for innovation in software, but it is not like in the past where we also had to build all the low-hanging fruit at the same time. That doesn't require nearly as many people — and that was already starting to become apparent before anyone knew what an LLM is. This AI craze swooped in at the right time to help hold up the industry and is the only thing keeping it together right now. We're quickly trying to build all the low-hanging fruit for it, keeping many developers busy (although not like it used to be), but there isn't much low-hanging fruit to build. LLMs don't have the breadth of need like previous computing revolutions had. Once we've added chat interfaces to everything, which is far from being a Herculean task, all the low-hanging fruit will be gone. That's quite unlike previous revolutions where we had to build all the software from scratch, effectively, not just slap some lipstick on existing software. If we want to begin to relive the past, we need a new hardware paradigm that needs all the software rewritten for it again. Not an impossible thought, but all the low-hanging hardware directions have also been picked at this point so the likelihood of that isn’t what it used to be either.
    - marcosdumay 9mo ago
      > Each of the last productivity multipliers coincided with greatly expanded markets They didn't. But it may be a relevant point that all of that was slow enough to spread that we can't clearly separate them. Anyway, the idea that any one of those large markets is at saturation point requires some data. AFAIK, anything from mainframe software to phones has (relatively) exploded in popularity every time somebody made them cheaper, so that is a claim that all of those just changed (too recently to measure), without any large thing to correlate them. > That's quite unlike previous revolutions where we had to build all the software from scratch We have rewritten everything from scratch exactly once since high-level languages were created in the 70s.
neilv 9mo ago
> 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.
Rakshath_1 9mo ago
[dead]
RandallBrown 9mo ago
> 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.
- add-sub-mul-div 9mo ago
  I'll stare at a blank editor for an hour with three different solutions in my head that I could implement, and type nothing until a good enough one comes to mind that will save/avoid time and trouble down the road. That last solution is not best for any simple reason like algorithmic complexity or anything that can be scraped from web sites.
  - aaroninsf 9mo ago
    No shade on your skills, but for most problems, this is already false; the solutions have already been scraped. All OSS has been ingested, and all the discussion in forum like this about it, and the personal blog posts and newsletters about it; and the bug tracking; and theh pull requests, and... and training etc. is only going to get better and filtering out what is "best."
    - al_borland 9mo ago
      A vast majority of the problems I’m asked to solve at work do not have open-source code I can simply copy or discussion forums that already decided the best answer. Enterprise customers rarely put that stuff out there. Even if they did, it doesn’t account for the environment the solution sit in, possible future integrations, off-the-wall requests from the boss, or knowing that internal customer X is going to want some other wacky thing, so we need to make life easy on our future selves. At best, what I find online are basic day 1 tutorials and proof on concept stuff. None of it could be used in production where we actually need to handle errors and possible failure situations.
      - jmtulloss 9mo ago
jollyllama 9mo ago
"Believe the checkbook? Why do that when I can get pump-faked into strip-mining my engineering org?"- VPs everywhere
zamadatix 9mo ago
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.
- croes 9mo ago
  But the engineers can do it because they have written lots of code before. Where will these engineers get their experience in the future. And what about vibe coding? The whole point and selling point of many AI companies is that you don’t need experience as a programmer. So they sell something that isn’t true, it’s not FSD for coding but driving assistance.
  - zamadatix 9mo ago
    These are all things I'd rather have seen the article set out to talk about as well, instead it opens up to disprove a statement saying AI can write the coding portion of the engineering problem by means of showing it being used that way with Bun to mean Anthropic must not actually think that.
  - imron 9mo ago
    > Where will these engineers get their experience in the future The house of the feeble minded: https://www.abelard.org/asimov.php https://www.abelard.org/asimov.php
drcode 9mo ago
The bun acquisition is driven by current AI capabilities. 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.
- 0x3f 9mo ago
  > This argument requires us to believe that AI will just asymptote and not get materially better. That's not what asymptote means. Presumably what you mean is the curve levelling off, which it already is.
  - SoftTalker 9mo ago
    This seems overly pedantic. The intended meaning is clear.
    - 0x3f 9mo ago
      Hardly, asymptotic behavior can be anything, in fact that's the whole question: what happens to AI performance as we tend to infinity? Asymptoting to `y = x` is very different to levelling off.
- bigstrat2003 9mo ago
  > This argument requires us to believe that AI will just asymptote and not get materially better. It hasn't gotten materially better in the last three years. Why would it do so in the next three or five years?
  - bitwize 9mo ago
    Deep learning and transformers have given step functions in AI's capabilities. It may not happen, but it's reasonable to expect another step-function development soon.
- nitwit005 9mo ago
  An Anthropic engineer was getting some attention for saying six months: https://www.reddit.com/r/ClaudeAI/comments/1p771rb/anthropic_engineer_says_software_engineering_is/ https://www.reddit.com/r/ClaudeAI/comments/1p771rb/anthropic... 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.
faxmeyourcode 9mo ago
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.
- maccard 9mo ago
  Does it? 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.
  - faxmeyourcode 9mo ago
    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?
fooqux 9mo ago
How do I know they didn't buy them just to make sure their competitors couldn't?
- kubb 9mo ago
  Can anyone tell me the leading theory explaining the acquisition? I can’t see how buying a runtime for the sake of Claude Code makes sense.
barfoure 9mo ago
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.
zmj 9mo ago
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.
- mk12 9mo ago
  This has been happening a lot recently, where an article immediately sets off all my AI alarm bells but most people seem to be happily engaging with it. I’m worried we’re headed for a dystopian future where all communication is outsourced to the slop machine. I hope instead there is a societal shift to better recognize it and stigmatize it.
  - integralid 9mo ago
    >instead there is a societal shift to better recognize it Unlikely. AI keeps improving, and we are already at the point where real people are accused of being AI.
  - duskdozer 9mo ago
    I've noticed some of this in recent months. I've also noticed people editing out some of the popular tells, like replacing em-dashes with commas, or at least I think so, because of odd formatting/errors in places where it sounds like the LLM would have used a dash. But at this point I'm not confident that I'm not failing to identify a lot of LLM-generated text and not making false positives.
  - marbro 9mo ago
    [dead]
- placebo 9mo ago
  The very fact that people are arguing with a non-existent author signals that whatever generated the content did a good enough job to fool them today. Tomorrow it will do a good enough job to fool you. I think the more important question is what this means in terms of what is really important and what we should invest in to remain anchored in what matters.

171 points by rg81 9mo ago

hapless 9mo ago

The ten dollar word for this is “revealed preferences”

recursive 9mo ago
I learned that phrase from one of the bold sentences in this article.

conductr 9mo ago

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.

marcosdumay 9mo ago
> but it will certainly feel like it if labor demand is reduced enough All the last productivity multipliers in programming led to increased demand. Do you really think the market is saturated now? And what saturated it is one of the least impactful "revolutionary" tools we got in our profession? Keep in mind that looking at statistics won't lead to any real answer, everything is manipulated beyond recognition right now.
- conductr 9mo ago
  Demand for software has been tied to demand for software engineering labor. That is no longer true. So demand for software may still go up while demand for labor goes another direction. Also I do hold a belief that most tech companies are taking a cost/labor reduction strategy for a reason, and I think that’s because we’re closing a period of innovation. Keeping the lights on, or protecting their moats, requires less labor.
- 9rx 9mo ago
  Each of the last productivity multipliers coincided with greatly expanded markets (e.g. PC revolution, internet, mobile). Those are at the saturation point. And we've effectively built all the software those things need now. Of course there is still room for innovation in software, but it is not like in the past where we also had to build all the low-hanging fruit at the same time. That doesn't require nearly as many people — and that was already starting to become apparent before anyone knew what an LLM is. This AI craze swooped in at the right time to help hold up the industry and is the only thing keeping it together right now. We're quickly trying to build all the low-hanging fruit for it, keeping many developers busy (although not like it used to be), but there isn't much low-hanging fruit to build. LLMs don't have the breadth of need like previous computing revolutions had. Once we've added chat interfaces to everything, which is far from being a Herculean task, all the low-hanging fruit will be gone. That's quite unlike previous revolutions where we had to build all the software from scratch, effectively, not just slap some lipstick on existing software. If we want to begin to relive the past, we need a new hardware paradigm that needs all the software rewritten for it again. Not an impossible thought, but all the low-hanging hardware directions have also been picked at this point so the likelihood of that isn’t what it used to be either.
  - marcosdumay 9mo ago
    > Each of the last productivity multipliers coincided with greatly expanded markets They didn't. But it may be a relevant point that all of that was slow enough to spread that we can't clearly separate them. Anyway, the idea that any one of those large markets is at saturation point requires some data. AFAIK, anything from mainframe software to phones has (relatively) exploded in popularity every time somebody made them cheaper, so that is a claim that all of those just changed (too recently to measure), without any large thing to correlate them. > That's quite unlike previous revolutions where we had to build all the software from scratch We have rewritten everything from scratch exactly once since high-level languages were created in the 70s.

neilv 9mo ago

> 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.

Rakshath_1 9mo ago

[dead]

RandallBrown 9mo ago

> 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.

add-sub-mul-div 9mo ago
I'll stare at a blank editor for an hour with three different solutions in my head that I could implement, and type nothing until a good enough one comes to mind that will save/avoid time and trouble down the road. That last solution is not best for any simple reason like algorithmic complexity or anything that can be scraped from web sites.
- aaroninsf 9mo ago
  No shade on your skills, but for most problems, this is already false; the solutions have already been scraped. All OSS has been ingested, and all the discussion in forum like this about it, and the personal blog posts and newsletters about it; and the bug tracking; and theh pull requests, and... and training etc. is only going to get better and filtering out what is "best."
  - al_borland 9mo ago
    A vast majority of the problems I’m asked to solve at work do not have open-source code I can simply copy or discussion forums that already decided the best answer. Enterprise customers rarely put that stuff out there. Even if they did, it doesn’t account for the environment the solution sit in, possible future integrations, off-the-wall requests from the boss, or knowing that internal customer X is going to want some other wacky thing, so we need to make life easy on our future selves. At best, what I find online are basic day 1 tutorials and proof on concept stuff. None of it could be used in production where we actually need to handle errors and possible failure situations.
    - jmtulloss 9mo ago

jollyllama 9mo ago

"Believe the checkbook? Why do that when I can get pump-faked into strip-mining my engineering org?"- VPs everywhere

zamadatix 9mo ago

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.

croes 9mo ago
But the engineers can do it because they have written lots of code before. Where will these engineers get their experience in the future. And what about vibe coding? The whole point and selling point of many AI companies is that you don’t need experience as a programmer. So they sell something that isn’t true, it’s not FSD for coding but driving assistance.
- zamadatix 9mo ago
  These are all things I'd rather have seen the article set out to talk about as well, instead it opens up to disprove a statement saying AI can write the coding portion of the engineering problem by means of showing it being used that way with Bun to mean Anthropic must not actually think that.
- imron 9mo ago
  > Where will these engineers get their experience in the future The house of the feeble minded: https://www.abelard.org/asimov.php https://www.abelard.org/asimov.php

drcode 9mo ago

The bun acquisition is driven by current AI capabilities. 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.

0x3f 9mo ago
> This argument requires us to believe that AI will just asymptote and not get materially better. That's not what asymptote means. Presumably what you mean is the curve levelling off, which it already is.
- SoftTalker 9mo ago
  This seems overly pedantic. The intended meaning is clear.
  - 0x3f 9mo ago
    Hardly, asymptotic behavior can be anything, in fact that's the whole question: what happens to AI performance as we tend to infinity? Asymptoting to `y = x` is very different to levelling off.
bigstrat2003 9mo ago
> This argument requires us to believe that AI will just asymptote and not get materially better. It hasn't gotten materially better in the last three years. Why would it do so in the next three or five years?
- bitwize 9mo ago
  Deep learning and transformers have given step functions in AI's capabilities. It may not happen, but it's reasonable to expect another step-function development soon.
nitwit005 9mo ago
An Anthropic engineer was getting some attention for saying six months: https://www.reddit.com/r/ClaudeAI/comments/1p771rb/anthropic_engineer_says_software_engineering_is/ https://www.reddit.com/r/ClaudeAI/comments/1p771rb/anthropic... 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.

faxmeyourcode 9mo ago

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.

maccard 9mo ago
Does it? 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.
- faxmeyourcode 9mo ago
  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?

fooqux 9mo ago

How do I know they didn't buy them just to make sure their competitors couldn't?

kubb 9mo ago
Can anyone tell me the leading theory explaining the acquisition? I can’t see how buying a runtime for the sake of Claude Code makes sense.

barfoure 9mo ago

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.

zmj 9mo ago

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.

mk12 9mo ago
This has been happening a lot recently, where an article immediately sets off all my AI alarm bells but most people seem to be happily engaging with it. I’m worried we’re headed for a dystopian future where all communication is outsourced to the slop machine. I hope instead there is a societal shift to better recognize it and stigmatize it.
- integralid 9mo ago
  >instead there is a societal shift to better recognize it Unlikely. AI keeps improving, and we are already at the point where real people are accused of being AI.
- duskdozer 9mo ago
  I've noticed some of this in recent months. I've also noticed people editing out some of the popular tells, like replacing em-dashes with commas, or at least I think so, because of odd formatting/errors in places where it sounds like the LLM would have used a dash. But at this point I'm not confident that I'm not failing to identify a lot of LLM-generated text and not making false positives.
- marbro 9mo ago
  [dead]
placebo 9mo ago
The very fact that people are arguing with a non-existent author signals that whatever generated the content did a good enough job to fool them today. Tomorrow it will do a good enough job to fool you. I think the more important question is what this means in terms of what is really important and what we should invest in to remain anchored in what matters.