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.

> Benedict Evans called me out on LinkedIn for this take, which I take as a sign the argument is landing.

Excellent. And correct lol.

> 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.

How is AI code generation a "innovation bazooka"? Last time I checked, innovation required creativity, context, and insight. Not really fast boilerplate generators.

> 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.

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.

>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.

The question is how much further and faster can these tools evolve.

Right now, you may not be faced with a valid choice to vibe code your own hubspot, but maybe some contractor firm will do it for you and sell an ultra low cost version.

Will opus 6 do the same thing without the contractors while managing the deployment and maintenance as a claw?

The Matrix folks have covered the "replace Slack internal chat" case already. They will give you the code so that you can bring the service up internally, or you can use any 3rd party hosted solution that provides the usual support and "enterprise" guarantees, for a price. Why can't this model generalize to sector-specific SaaS offerings that can now be prototyped cheaply via AI vibecoding?

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.

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.

> AI create something

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.

Problem space is rich. The thing doesnt actually know what a problem is.

The thing is incredibly good at searching through large spaces of information.

Right! It's like maybe the AI is more of a threat to the accounts payable person than the accounts payable software. At least in terms of head count.

100% agree. I’d add we are underestimating our contributions in making the code agents do the right thing as well.

Yup, my experience has been that vibe-coding is very time-consuming. It reminds me very much of how LLMs are great at creating mind-blowing images, but you get what you get. Once you decide that you need to modify the image you get, it becomes a time sink. You might be able to change it and get what you need, but there is no guarantee and it's a never ending task.

The same thing happens with code; you may get great results from your prompt, but trying to customize it will drive you nuts and you may never get what you want.

Maintenance is another hurdle. How do you maintain code you might not have the skills to maintain?

Vibe-coding may reduce software creation time, but it's not taking over software engineering. The SaaS business is going nowhere. Most people, by far, will continue to rely on someone else for their software needs. But be very aware that the software business will change. We are seeing that already.

It doesn't make sense for every company to make their own Salesforce clone.

The key is that it makes new companies entering the market to compete with Salesforce immensely easier. More competition will just force lower overall margins in SAAS.

To avoid CRAZY SaaS charges. I left a comment further down about how the challenge is first getting a reliable stack running underneath whatever ends up being fast-coded. The trend will be more decentralization - I think that'll be AI 2.0. Increasing centralization is AI 1.0.

Every company that I’ve worked at has had to do significant additional development work on their instance of salesforce to make it work for them. Like 6-12 months of work with 1-3 people. I don’t know if this is common but in that case maybe going custom might be the way to go. You get something lean, without all the cruft, specifically built for your usecase and nothing more.

Well the answer is because the cost of that software is lower than somebody building the other software. What happens is that all these SaaS drop in value because it is now realistic to build them internally

Slack is a good example. When the cost of Slack is an unreasonable amount of your operating costs then it makes sense to clone and maintain. The product is simple, you can basically recreate the main functionality in a sitting. Why would you pay hundreds of thousands of dollars for it?

Companies do make/buy decisions on everything, it just software. Cleaning services are not expensive, yet companies contract them instead of hiring staff.

This is called transaction cost economics, if anyone’s interested.

We’ve also got to consider the fourth dimension, what happens over time.

Salesforce is getting LLM superpowers at the same time the Enterprise is, so customizing and maintaining and extending Salesforce are all getting cheaper and better and easier for customers, consultants, and Salesforce in parallel.

Unless the LLMs are managing the entire process there’s still a value proposition around liability, focus, feature updates, integrations, etc. Over time that tech should make Salesforce get way cheaper, or, start helping them upsell bigger and badder Sales things that are harder to recreate.

And, big picture, the LLMs are well trained on Salesforce API code. Homegrown “free” versus industry-standard with clear billing, whatever we know versus man-decades of learning at a vendor, months of effort and all the risk & liability versus turnkey with built-in escape goats… at some point you’re paying money not to own, not to learn, not to be distracted, and to have jerks to sue if something goes bad.

I agree generally, but some of these enterprise contracts are eye-watering. If the choice is $2M/year with a 3-year minimum contract, or rolling your own, I think calculus really has shifted.

With that said, the entire business world does not understand that software is more than just code. Even if you could write code instantly, making enterprise software would still take time, because there are simply so many high-stakes decisions to make, and so much fractal detail.

> Until you can get AI to the point where it equivalent to a 20 person engineering team

I think that’s gonna happen when you don’t need software and AI just does it all.

If an AI agent ever became as productive at writing code as a well-organized 20 person engineering team you'd still need to run it for a year or more to replicate any nontrivial SaaS product.

And the thing about many of these products isn't their feature set, it's their stability. It's their uptime. It's how they handle scaling invisibly and with no effort on your part. These are things you can't just write down from whole cloth, they are properties that emerge over time by adapting the the reality of scale. Coding isn't the whole deal, and your 20x clanker which can do nothing but re-arrange text in interesting patterns is going to have some trouble with the realities of taking that PoC to production. You'll still need experienced, capable people for that. And lots of time.

A lot of this "ermahgerd everything will change" drivel is based on some magical fundamentally new technology emerging in the near future that can do things that LLMs cannot do. But as far as anyone knows, that future may be never.

So even given a large improvement in agentic coding I'm not convinced it really changes the build vs buy equation much.

Imagine a 20 person engineering team that hallucinates on a regular basis and is incapable of innovation.

But have you ever tried to clone a product or tool for yourself before? At first it’s great because you think that you saved money but then you start having to maintain it… fixing problems, filling in gaps… you now realize that you made a mistake. Just because AI can do it now doesn’t mean you aren’t just now having to use AI to do the same thing…

Also, agents are not deterministic. If you use it to analyze data, it will get it right most of the time but, once in a blue moon, it will make shit up, except you can’t tell which time it was. You could make it deterministic by having AI write a tool instead… except you now have the first problem of maintaining a tool.

That isn’t to say that there isn’t small low hanging fruit that AI will replace, but it’s a bit different when you need a real product with support.

At the end of the day, you hire a plumber or use a SaaS not because you can’t do it yourself, but because you don’t want to do it and rather want someone else who is committed to it to handle it.

Insightful points!

It would be interesting if, with all the anxiety about vibe coding becoming the new normal, its only lasting effect is the emergence of smaller B2B companies that quickly razzle dazzle together a bespoke replacement for Concur, SAP, Workday, the crappy company sharepoint - whatever. Reminds me of what people say Palantir is doing, but now supercharged by the AI-driven workflows to stand up the “forward deployed” “solution” even faster.

My first thought as well - they suddenly realized they have an interest in AI not cannibalizing their existing SaaS portfolio