True, but if the coding becomes trivial then you'll be replaced by a good PM who can work with an agent team.

Coding was always trivial (see code generators, snippets, templates). The issue is making all the little pieces work and adjust them as needed.

No-code database work was solved with Filemaker Pro decades ago. It turned out that you also need an attention span and an interest in the subject.

Most of the flowchart automation software I've been playing around with is already good enough. The Python ecosystem is good enough. Ollama is good enough. The small, purpose built models people seem compelled to make are good enough.

If I can replicate your SaaS business model by crawling your site for a description of services, what does that do to the landscape?

As always, the edge cases, which you will be aware of by talking to domain experts or the experience of managing the production services for years. There's a reason we're still running decades old software written in no longer maintained programming languages. The only valuable specs was always the code.

Totally agree with your point, and in fact my first programming gig was encapsulating COBOL next to these domain experts. Very generally speaking the edge cases exist because you are trying to be all things to all people.

Rebuilding an existing, predefined service for exactly one use case is straightforward. The tools available are "good enough" to do the job for one person. That person hasn't been building another SaaS, they've been posting well designed documentation on github.

And that's why software engineering =/= coding

I'm currently reading Modern Software Engineering by David Farley and I can say that we won't see programmers replaced unless all the concerns pointed out in this book and others has been resolved.

> Not my quote but: "The trillion dollar problem AI is trying to solve is wages. Your wages."

You know that your job as software engineer is automating tasks that other people could be doing manually, right?

> The 10% of my job which is coding just isn't the difficult part.

Even so, is there any reason to believe that the other 90% won't also be automated?

As you said, the goal of these systems is to replace wages.

I'd describe a lot of my job and my team's job as "figuring out what to do". Lots of talking to people, debating options, weighing up trade-offs.

Customer support, "pre sales" stuff too.

Distilling complex situations involving tech but also people into bullet-point reports for management.

To reference another one of these neat little phrases: building the right system != building the system right. The former is hard to automate, the latter is indeed more open to AI involvement.