2) They named one of the two authors of the Fascist Manifesto their patron saint
3) AI systems are built to function in ways that degrade and are likely to destroy our crucial civic institutions. (Quoted from
Professor Woodrow Hartzog "How AI Destroys Institutions"). Or to put it another way, being plausible but slightly wrong and un-auditable—at scale—is the killer feature of LLMs and this combination of properties makes it an essentially fascist technology meaning it is well suited to centralizing authority, eliminating checks on that authority and advancing an anti-science agenda (quoted from the A plausible, scalable and slightly wrong black box: why large language models are a fascist technology that cannot be redeemed post).
>> Anish Acharya says it is not worth it to use AI-assisted coding for all business functions. AI should focus on core business development, not rebuilding enterprise software.
I don't even know what this means, but my take: we should stop listening to VCs (especially those like A16Z) who have an obvious vested interest that doesn't match the rest of society. Granting these people an audience is totally unwarranted; nobody but other tech bros said "we will vibe code everything" in the first place. Best case scenario: they all go to the same exclusive conference, get the branded conference technical vest and that's were the asteroid hits.
Acharya’s framing is different from mine (he’s talking book on software stocks) but the conclusion is the same: the “innovation bazooka” pointed at rebuilding payroll is a bad allocation of resources. Benedict Evans called me out on LinkedIn for this (https://philippdubach.com/posts/is-ai-really-eating-the-worl...) take, which I take as a sign the argument is landing..
> investors are simultaneously punishing hyperscaler stocks because AI capex might generate weak returns, while destroying software stocks because AI adoption will be so pervasive it renders all existing software obsolete. Both cannot hold simultaneously.
I don't understand this point. Can't it be possible that the ultimate effect is to devalue, hugely, software? As in it can totally both be true that AI capex has weak returns and at the same time most SaaS companies go bankrupt. To take an analogy: if ever we manage to successfully mine asteroids, and find some vast quantity of platinum, it could both be true that every existing platinum miner loses their shirt, and also that the value of platinum sinks so far that the asteroid mining company cannot cover its costs.
The best take I've seen on the whole `AI will replace all devs' is a way for big tech to walk back the disastrous over hiring they did around Covid without getting slaughtered in the stock market.
All that is correct and well-written, however I fear in most cases "good enough" will be good enough for Business. If Business can do something to 80% the same but with a large cost cutting they likely go for it, we have seen this with shrinkflation (reduced portion sizes for the same price), to using cheaper ingredients to practically everything that is not a knowledge-heavy industry. The big change is now the "shrinkflation" is coming to knowledge domains too, which will likely lower the quality of healthcare, software etc.
AI being a next-token predictor will produce cheap and average products, we will likely see some (most?) software become a commodity, that goes through the same product development and "manufacturing" as a breakfast cereal. Made in a "dark factory", 24/7, with little supervision.
However I think down the line we will see many industries popping up that are like "organic food", "mechanical watchmaking" that provide above the usual slop that large businesses produce.
> Even a16z is walking this back now. I wrote about why the “vibe code everything” thesis doesn’t hold up in two recent pieces:
The next one a16z should walk back on is "AGI" given that they have just admitted that "vibe code everything" was just a sign of them being consumed by the hype.
How is AI code generation a "innovation bazooka"? Last time I checked, innovation required creativity, context, and insight. Not really fast boilerplate generators.
AI allows innovative people to create more innovations by reducing a lot of the non-innovative grunt work in an efficient manner. It isn't the AI doing the innovation, but allows innovators to focus more on innovating.
Or at least that is the theory. It is certainly true from observations of those around me. It also scales well. Even someone a bit innovative gets a multiplier by using AI intelligently. Those that just focus on the grunt work are the ones in trouble.
>In this article I will try to explain why I find his framing fascinating but incomplete. Evans structures technology history in cycles. Every 10-15 years, the industry reorganizes around a new platform: mainframes (1960s-70s), PCs (1980s), web (1990s), smartphones (2000s-2010s). Each shift pulls all innovation, investment, and company creation into its orbit. Generative AI appears to be the next platform shift, or it could break the cycle entirely.
A lot of the AI and LLM argument on whether it is really eating the world misses one point, and I think Evans implied but not pointed out explicitly.
Had it not been AI investment, we wouldn't have the current hardware improvement and innovation rate.
Most people have heard about the limit of Moore's law, but every single time it appeared in headline is an economic model limit rather than limit of physics. We were predicting a stop to growth in 90s because we couldn't see a 400M PC market shipment in 2010. Turns out Smartphone carried that forward, and it is what funded growth of TSMC when most on HN even knew much or heard of TSMC. The same goes with LPDDR RAM, Pure Play IP, Wireless, Network, etc. All the hardware improvements that came with Smartphone is now continued to be developed at rapid pace due to AI and Hyperscaler.
What Evan were suggesting is much simpler, could AI automate things that previously were not possible for 99% of business outside of Tech and Software. The answer is a simple yes. And worth pointing out ChartGPT is closing in on a billion weekly active user.
A lot of HN discussion about AI often centered around software development. And whether it is good enough of it. Most of the world outside are happy enjoying AI for many things. What used to require a mildly technical person to do on excel can not be done without one. It is opening up software to even more people. It is creating more value than people imagine, and users are willing to paid for it.
Both AI Fanatics and AI Luddites need to touch grass.
We work in Software ENGINEERING. Engineering is all about what tools makes sense to solve a specific problem. In some cases, AI tools do show immediate business value (eg. TTS for SDR) and in other cases this is less obvious.
This is all the more reason why learning about AI/ML fundamentals is critical in the same way understanding computer architecture, systems programming, algorithms, and design principles are critical to being a SWE, because then you can make a data-driven judgment on whether an approach works or not.
Given the number of throwaway accounts that commented, it clearly struck a nerve.
I really hate the expression "the new normal", because it sort of smuggles in the assumption that there exists such thing as "normal". It always felt like one of those truisms that people say to exploit emotions like "in these trying times" or "no one wants to work anymore".
But I really do think that vibe coding is the "new normal". These tools are already extremely useful, to a point where I don't really think we'll be able to go back. These tools are getting good enough that it's getting to a point where you have to use them. This might sound like I'm supportive of this, and I guess am to some extent, but I find it to be exceedingly disappointing because writing software isn't fun anymore.
One of my most upvoted comments on HN talks about how I don't enjoy programming, but instead I enjoy problem solving. This was written before I was aware of vibe coding stuff, and I think I was wrong. I guess I actually did enjoy the process of writing the code, instead of just delegating my work to a virtual intern while I just watch the AI do the fun stuff.
A very small part of me is kind of hoping that once AI has to be priced at "not losing money on every call" levels that I'll be forced to actually think about this stuff again.
Let's just look at Dijkstra's On the Foolishness of "Natural Language Programming". It really does a good job at explaining why natural language programming (and thus, Vibe Coding) is a dead end. It serves as a good reminder that we developed the languages of Math and Programming for a reason. The pedantic nature is a feature, not a flaw. It is because in programming (and math) we are dealing with high levels of abstraction constantly and thus ambiguity compounds. Isn't this something we learn early on as programmers? That a computer does exactly what you tell it to, not what you intend to tell it to? Think about how that phrase extends when we incorporate LLM Coding Agents.
| The virtue of formal texts is that their manipulations, in order to be legitimate, need to satisfy only a few simple rules; they are, when you come to think of it, an amazingly effective tool for ruling out all sorts of nonsense that, when we use our native tongues, are almost impossible to avoid.
- Dijkstra
All of you have experienced the ambiguity and annoyances of natural language. Have you ever:
- Had a boss give you confusing instructions?
- Argued with someone only to find you agree?
- Talked with someone and one of you doesn't actually understand the other?
- Talked with someone and the other person seems batshit insane but they also seem to have avoided a mental asylum?
- Use different words to describe the same thing?
- When standing next to someone and looking at the same thing?
- Adapted your message so you "talk to your audience"?
- Ever read/wrote something on the internet? (where "everyone" is the audience)
Congrats, you have experienced the frustrations and limitations of natural language. Natural language is incredibly powerful and the ambiguity is a feature and a flaw, just like how in formal languages the precision is both a feature and a flaw. I mean it can take an incredible amount of work to say even very simple and obvious things with formal languages[1], but the ambiguity disappears[2].
Vibe Coding has its uses and I'm sure that'll expand, but the idea of it replacing domain experts is outright laughable. You can't get it to resolve ambiguity if you aren't aware of the ambiguity. If you've ever argued with the LLM take a step back and ask yourself, is there ambiguity? It'll help you resolve the problem and make you recognize the limits. I mean just look at the legal system, that is probably one of the most serious efforts to create formalization in natural language and we still need lawyers and judges to sit around and argue all day about all the ambiguity that remains.
I seriously can't comprehend how on a site who's primary users are programmers this is an argument. If we somehow missed this in our education (formal or self) then how do we not intuit it from our everyday interactions?
[2] Most programming languages are some hybrid variant. e.g. Python uses duck typing: if it looks like a float, operates like a float, and works as a float, then it is probably a float. Or another example even is C, what used to be called a "high level programming language" (so is Python a celestial language?). Give up some precision/lack of ambiguity for ease.
All these articles seem to think people will vibe code by prompting:
make me my own Stripe
make me my own Salesforce
make me my own Shopify
It will be more like:
Look at how Lago, an open-source Stripe layer, works and make it work with Authorized.net directly
Look at Twenty, an open-source CRM, and make it work in our tech stack for our sales needs
Look at how Medusa, an open-source e-commerce platform, works and what features we would need and bring into our website
When doing the latter, getting a good enough alternative will reduce the need for commercial SaaS. On top of that, these commercial SaaS are bloated with features in their attempt to work with as many use cases as possible and configuring them is “coding” by another name. Throw in Enshittification and the above seems to the next logical move by companies looking to move off these apps.
Sensible people would do that (asking for just the features they need), but look at us, are we sensible?
Most of us* are working for places whose analytics software transitively asks the user for permission to be tracked by more "trusted" partners than the number of people in a typical high school, which transitively includes more bytes of code than the total size of DOOM including assets, with a performance hit so bad that it would be an improvement for everyone if the visitor remote desktop-ed into a VM running Win95 on the server.
And people were complaining about how wasteful software was when Win95 was new.
* Possibly an exaggeration, I don't know what business software is like; but websites and, in my experience at least, mobile apps do this.
First, a vendor will have the best context on the inner workings and best practices of extending the current state of their software. The pressure on vendors to make this accessible and digestable to agents/ LLMs will increase, though.
Secondly, if you have coded with LLM assistance (not vibe coding), you will have experienced the limited ability of one shot stochastic approaches to build out well architected solutions that go beyond immediate functionality encapsulated in a prompt.
Thirdly, as the article mentions, opportunity cost will never make this a favorable term - unless the SaaS vendor was extorting prices before. The direct cost of mental overhead and time of an internal team member to hand-hold an agent/ write specs/ debug/ firefight some LLM assisted/ vibe coded solution will not outweigh the upside potential of expanding your core business unless you're a stagnant enterprise product on life support.
People are overestimating the value on having AI create something given loose instructions, and underestimating the value of using AI as a tool for a human to learn and explore a problem space. The bias shows on the terminology (“agents”).
We finally made the computer able to speak “our” language - but we still see computers as just automation. There’s a lot of untapped potential in the other direction, in encoding and compressing knowledge IMO.
Exactly my thoughts - the value in AI is not auto-generating anything more than something trivial, but there's huge value in a more customized knowledge engine - a targeted, specific Google if you will. Get answers to your specific question instead of results that might contain what you were looking for if you slog through them.
AI is hugely beneficial in understanding a problem, or at least getting a good overview, so you can then go off and solve/do it yourself, but focusing on "just have the AI generate a solution" is going to hugely harm AI perception/adoption.
Because that would mean AI isn't going to replace entire industries, which is the only way to justify the, not billions, but trillions in market value that AI leaders keep trying to justify.
I hear and read so much shit by VCs. Both in LinkedIn and in private meetings. Specially Menlo says a lot of shit (check LinkedIn). Deloitte and McKinsey, also full of crap. Really.
Vcs are choke full of companies that can be cloned over night, SaaS companies that will face ridiculously fast substitution, and a whoooole lotta capital deployed on lousy RAGs and OpenAI Wrappers.
Anyone who's seen an enterprise deal close or dealt with enterprise customer requests will know this, the build vs buy calculus has always been there yet companies still buy. Until you can get AI to the point where it equivalent to a 20 person engineering team, people are not going to build their own Snowflake, Salesforce, Slack or ATS. Maybe that day is 3 years away but when that happens the world will be very different
There was a short moment in history where it seemed that the sentiment was: people will soon 3D-print 99% of their household items themselves instead of buying them.
You absolutely could print things like cups, soap holders, picture frames, the small shovel you use for gardening, and so on an so on.
I just recreated most of Linear for my company in a few days. Making it hyper specific to what we want (metrics driven, lean startup style).
All state changes are made with MCP so it saved me from having to spend time on any forms and most interactions other than filtering searching sorting etc.
Means we will be ditching Linear soon.
I know I’m an outlier but this sort of thing will get more common.
> He said that software accounts for 8% to 12% of a company's expenses, so using vibe coding to build the company's resource planning or payroll tools would only save about 10%. Relying on AI to write code also carries risks, he said.
> "You have this innovation bazooka with these models. Why would you point it at rebuilding payroll or ERP or CRM," Acharya said
> Instead, companies are better off using AI to develop their core businesses or optimize the remaining 90% of their costs
72 comments
[ 2451 ms ] story [ 2947 ms ] threadThis is your regular reminder that
1) a16z is one the largest backers of LLMs
2) They named one of the two authors of the Fascist Manifesto their patron saint
3) AI systems are built to function in ways that degrade and are likely to destroy our crucial civic institutions. (Quoted from Professor Woodrow Hartzog "How AI Destroys Institutions"). Or to put it another way, being plausible but slightly wrong and un-auditable—at scale—is the killer feature of LLMs and this combination of properties makes it an essentially fascist technology meaning it is well suited to centralizing authority, eliminating checks on that authority and advancing an anti-science agenda (quoted from the A plausible, scalable and slightly wrong black box: why large language models are a fascist technology that cannot be redeemed post).
I don't even know what this means, but my take: we should stop listening to VCs (especially those like A16Z) who have an obvious vested interest that doesn't match the rest of society. Granting these people an audience is totally unwarranted; nobody but other tech bros said "we will vibe code everything" in the first place. Best case scenario: they all go to the same exclusive conference, get the branded conference technical vest and that's were the asteroid hits.
(1) https://philippdubach.com/posts/the-saaspocalypse-paradox/
(2) https://philippdubach.com/posts/the-impossible-backhand/
Acharya’s framing is different from mine (he’s talking book on software stocks) but the conclusion is the same: the “innovation bazooka” pointed at rebuilding payroll is a bad allocation of resources. Benedict Evans called me out on LinkedIn for this (https://philippdubach.com/posts/is-ai-really-eating-the-worl...) take, which I take as a sign the argument is landing..
I don't understand this point. Can't it be possible that the ultimate effect is to devalue, hugely, software? As in it can totally both be true that AI capex has weak returns and at the same time most SaaS companies go bankrupt. To take an analogy: if ever we manage to successfully mine asteroids, and find some vast quantity of platinum, it could both be true that every existing platinum miner loses their shirt, and also that the value of platinum sinks so far that the asteroid mining company cannot cover its costs.
AI being a next-token predictor will produce cheap and average products, we will likely see some (most?) software become a commodity, that goes through the same product development and "manufacturing" as a breakfast cereal. Made in a "dark factory", 24/7, with little supervision.
However I think down the line we will see many industries popping up that are like "organic food", "mechanical watchmaking" that provide above the usual slop that large businesses produce.
The next one a16z should walk back on is "AGI" given that they have just admitted that "vibe code everything" was just a sign of them being consumed by the hype.
Or at least that is the theory. It is certainly true from observations of those around me. It also scales well. Even someone a bit innovative gets a multiplier by using AI intelligently. Those that just focus on the grunt work are the ones in trouble.
A lot of the AI and LLM argument on whether it is really eating the world misses one point, and I think Evans implied but not pointed out explicitly.
Had it not been AI investment, we wouldn't have the current hardware improvement and innovation rate.
Most people have heard about the limit of Moore's law, but every single time it appeared in headline is an economic model limit rather than limit of physics. We were predicting a stop to growth in 90s because we couldn't see a 400M PC market shipment in 2010. Turns out Smartphone carried that forward, and it is what funded growth of TSMC when most on HN even knew much or heard of TSMC. The same goes with LPDDR RAM, Pure Play IP, Wireless, Network, etc. All the hardware improvements that came with Smartphone is now continued to be developed at rapid pace due to AI and Hyperscaler.
What Evan were suggesting is much simpler, could AI automate things that previously were not possible for 99% of business outside of Tech and Software. The answer is a simple yes. And worth pointing out ChartGPT is closing in on a billion weekly active user.
A lot of HN discussion about AI often centered around software development. And whether it is good enough of it. Most of the world outside are happy enjoying AI for many things. What used to require a mildly technical person to do on excel can not be done without one. It is opening up software to even more people. It is creating more value than people imagine, and users are willing to paid for it.
We work in Software ENGINEERING. Engineering is all about what tools makes sense to solve a specific problem. In some cases, AI tools do show immediate business value (eg. TTS for SDR) and in other cases this is less obvious.
This is all the more reason why learning about AI/ML fundamentals is critical in the same way understanding computer architecture, systems programming, algorithms, and design principles are critical to being a SWE, because then you can make a data-driven judgment on whether an approach works or not.
Given the number of throwaway accounts that commented, it clearly struck a nerve.
Or maybe they own the debt.
Listen to some of the Marc Andreessen interviews promoting cryptocurrency in 2021.
Do that and you will never listen to him or his associates again.
I really hate the expression "the new normal", because it sort of smuggles in the assumption that there exists such thing as "normal". It always felt like one of those truisms that people say to exploit emotions like "in these trying times" or "no one wants to work anymore".
But I really do think that vibe coding is the "new normal". These tools are already extremely useful, to a point where I don't really think we'll be able to go back. These tools are getting good enough that it's getting to a point where you have to use them. This might sound like I'm supportive of this, and I guess am to some extent, but I find it to be exceedingly disappointing because writing software isn't fun anymore.
One of my most upvoted comments on HN talks about how I don't enjoy programming, but instead I enjoy problem solving. This was written before I was aware of vibe coding stuff, and I think I was wrong. I guess I actually did enjoy the process of writing the code, instead of just delegating my work to a virtual intern while I just watch the AI do the fun stuff.
A very small part of me is kind of hoping that once AI has to be priced at "not losing money on every call" levels that I'll be forced to actually think about this stuff again.
Vibe Coding has its uses and I'm sure that'll expand, but the idea of it replacing domain experts is outright laughable. You can't get it to resolve ambiguity if you aren't aware of the ambiguity. If you've ever argued with the LLM take a step back and ask yourself, is there ambiguity? It'll help you resolve the problem and make you recognize the limits. I mean just look at the legal system, that is probably one of the most serious efforts to create formalization in natural language and we still need lawyers and judges to sit around and argue all day about all the ambiguity that remains.
I seriously can't comprehend how on a site who's primary users are programmers this is an argument. If we somehow missed this in our education (formal or self) then how do we not intuit it from our everyday interactions?
[0] https://www.cs.utexas.edu/~EWD/transcriptions/EWD06xx/EWD667...
[1] https://en.wikipedia.org/wiki/Principia_Mathematica
[2] Most programming languages are some hybrid variant. e.g. Python uses duck typing: if it looks like a float, operates like a float, and works as a float, then it is probably a float. Or another example even is C, what used to be called a "high level programming language" (so is Python a celestial language?). Give up some precision/lack of ambiguity for ease.
Machine assisted rigorous software engineering is an even bigger wealth transfer from unscrupulous people to passionate computer scientists.
make me my own Stripe
make me my own Salesforce
make me my own Shopify
It will be more like:
Look at how Lago, an open-source Stripe layer, works and make it work with Authorized.net directly
Look at Twenty, an open-source CRM, and make it work in our tech stack for our sales needs
Look at how Medusa, an open-source e-commerce platform, works and what features we would need and bring into our website
When doing the latter, getting a good enough alternative will reduce the need for commercial SaaS. On top of that, these commercial SaaS are bloated with features in their attempt to work with as many use cases as possible and configuring them is “coding” by another name. Throw in Enshittification and the above seems to the next logical move by companies looking to move off these apps.
Most of us* are working for places whose analytics software transitively asks the user for permission to be tracked by more "trusted" partners than the number of people in a typical high school, which transitively includes more bytes of code than the total size of DOOM including assets, with a performance hit so bad that it would be an improvement for everyone if the visitor remote desktop-ed into a VM running Win95 on the server.
And people were complaining about how wasteful software was when Win95 was new.
* Possibly an exaggeration, I don't know what business software is like; but websites and, in my experience at least, mobile apps do this.
First, a vendor will have the best context on the inner workings and best practices of extending the current state of their software. The pressure on vendors to make this accessible and digestable to agents/ LLMs will increase, though.
Secondly, if you have coded with LLM assistance (not vibe coding), you will have experienced the limited ability of one shot stochastic approaches to build out well architected solutions that go beyond immediate functionality encapsulated in a prompt.
Thirdly, as the article mentions, opportunity cost will never make this a favorable term - unless the SaaS vendor was extorting prices before. The direct cost of mental overhead and time of an internal team member to hand-hold an agent/ write specs/ debug/ firefight some LLM assisted/ vibe coded solution will not outweigh the upside potential of expanding your core business unless you're a stagnant enterprise product on life support.
We finally made the computer able to speak “our” language - but we still see computers as just automation. There’s a lot of untapped potential in the other direction, in encoding and compressing knowledge IMO.
To have AI recreate something that was already in it's training set.
> in encoding and compressing knowledge IMO.
I'd rather have the knowledge encoded in a way that doesn't generate hallucinations.
AI is hugely beneficial in understanding a problem, or at least getting a good overview, so you can then go off and solve/do it yourself, but focusing on "just have the AI generate a solution" is going to hugely harm AI perception/adoption.
Vcs are choke full of companies that can be cloned over night, SaaS companies that will face ridiculously fast substitution, and a whoooole lotta capital deployed on lousy RAGs and OpenAI Wrappers.
- JIRA/trello/monday.com - benchling - obsidian
this is what i buy and have no intent to replace:
- carta - docusign - gusto/rippling - bank
this is what might be on the chopping block:
- gsuite
You absolutely could print things like cups, soap holders, picture frames, the small shovel you use for gardening, and so on an so on.
99% of people still just buy this stuff.
All state changes are made with MCP so it saved me from having to spend time on any forms and most interactions other than filtering searching sorting etc.
Means we will be ditching Linear soon.
I know I’m an outlier but this sort of thing will get more common.
> "You have this innovation bazooka with these models. Why would you point it at rebuilding payroll or ERP or CRM," Acharya said
> Instead, companies are better off using AI to develop their core businesses or optimize the remaining 90% of their costs