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by 7777777phil·5mo ago·view on hn ↗
Even a16z is walking this back now. I wrote about why the “vibe code everything” thesis doesn’t hold up in two recent pieces:

(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..

7 comments
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.
I don't understand this take. The market tends to positively value layoffs.
However, admitting to have massively over hired and wasted a lot of money does not make the management involved look good. No one wants to admit they made a massive blunder.
The market doubly rewards companies that lay off workers and have a story about how they're automating everything with AI, even if that story is just a story.
> 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.

SaaS companies were just overvalued. They had crazy multiples. Not even an AI thing.
It is an AI thing though. AI makes it far easier to create bespoke software targeted at narrow specialized domains, which is the mainstay of modern SaaS. We'll probably see "proper" FLOSS expand into these sectors too, such that the software won't be simply a matter of internal vibecoding by any single business - instead, the maintenance work will be shared.
AI makes it easier to create something, but that thing is not enterprise software with support contracts and conformance to mandatory regulations and 4 hour bug turnarounds and real people on the end of the phone who understand how it works.

Sometimes I just wonder at how HN has no idea what enterprise software involves.

With this kind of niche sector-specific offering, creating a prototype that works properly for what the industry needs is the main hurdle. The rest is just the same sort of ordinary software engineering work that applies to any FLOSS project already - and we know that FLOSS (with optional 3rd party support covering "enterprise" needs) is quite viable.
I don't see AI easily creating a DataDog. You need it for reliability for example.

You can always also deploy open source since forever. What happens when it randomly drops logs or changes the text? If you get an alert and it is noise it starts becoming pointless.

And yet these type of stocks were at 50-100x earnings etc.

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.

> 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.