Software Is Becoming Marketing

> Implication 1: Lower entry barrier makes software lower-respect field

Maybe? This one's kind of subjective. I'm sure there are some people who will feel this way, and many who won't.

Do you respect artists less, now that you can make AI images?

As for pay, it seems unlikely to me that the job title of "software engineer" is going to see a significant decrease in median wage as a result of AI. Though there may simply be fewer "software engineer" jobs and more "prompt engineer" jobs.

> Implication 2: Optionality changes the commitment to software products

It's not clear to me that the typical decision-making process the average company was using to choose (for example) project management software, is going to be significantly different in the AI era than before. "Let's use JIRA, since that's what everyone else uses."

Making decisions this way is low-risk, and lower-cost than the token cost of vibe-coding something custom. The analogy to dating apps doesn't work - dating apps reward searching far and wide for something perfect, whereas the business world rewards going with what you know and making decisions quickly.

> Implication 3: The middle class of software products will disappear

I don't believe the cost of software creation is approaching zero. People are taking this concept too far and too literally. First of all, obviously there are token costs. And secondly, obviously there is still a time and effort requirement involved in maintaining anything, even via vibe-coding. Most companies have absolutely no reason to prefer to incur these costs rather than simply paying the man his $50/month.

But thirdly, and probably most importantly, there's the inherent cost of merely being responsible for something. Like I wrote earlier, decisionmakers want to minimize risk. The mere fact of being responsible for something - of it being someone's fault if something goes wrong - is a dire political cost, which most business leaders try to avoid by buying external rather than creating in-house. The SaaS market isn't going anywhere.

> Implication 4: If you want to win, sell services, not products

Service automation is a fruit that has already been mostly squeezed by conventional software.

That is to say - the space of things that traditional software can't already automate, that LLMs would be capable of automating, and that LLMs would be reliable and efficient enough at to significantly move the needle on real productivity - is small.

(Ironically, software development is one of the few things in that space. Since when you automate software development you can also automate the creation of tests that (at least attempt to) validate the correctness of the software itself. Not so much for legal documents.)

It's because GLM 5.2 is offered on many inference providers, including providers in the US. Those companies only make their money by charging for inference, and yet they seem to be doing quite well while charging the exact same prices as Z.AI / GLM.

In fact, there's a price war where some of the US inference providers are undercutting the pricing of Z.AI's own GLM hosting. Novita & AtlasCloud are both offering 8% and 5% discounts on GLM 5.2 respectively. GMICloud is charging 30% less - but getting so hammered with demand that it only has 80% uptime & 7 tokens per second, so you get what you pay for.

You can find a list of providers & their pricing through OpenRouter here:

https://openrouter.ai/z-ai/glm-5.2#providers

The people saying "anyone can build software now" often seem to mean "anyone can generate code now"... which is not quite the same thing

Nice write-up... but with strong opinions that seem plausible, yet are highly debatable.

"The rise of the long tail" -> To my knowledge the 'long tail' was years ago a subject of many scientific business studies. The conclusion: proof was never found for this economic theory. And yes, the book of Chris Anderson (20 years ago!) was an attractive read that also seems plausible.

"The barrier to entry for software has fallen." -> This is the marketing mantra since 4GL and IDEs. Visual coding IDEs, so coding without knowing coding never worked out as marketers promised, Same with nocode things years later.

Truth is programming in a natural language is very hard, that's why we have programming languages. And the hard part was never programming, but problems solving and gathering requirements before programming. Or during programming if you are fan of the agile community. AI/ML technology is a great tool for solving some problems, but certainly many problems can not be solved with AI for coming years. AI can not replace people, but people who do not add much value are, have been, and always will be the first to encounter technology progress.

Take away the maximalist points and this post rings true.

> It is now possible to vibecode your own SaaS instead of paying someone $50/month for theirs.

I have yet to see proof of this playing out this way.

You do have highly competent engineers vibing big things in record time and you have noobs one-shotting a prototype with Claude and then getting stuck.

I remain convinced that LLMs are an amplifier and you can't turn a zero in to something useful.

This of course barely changes how LLMs shifted much of programming from a mystical realm to top bike shedding territory, as Tereze here points out.