But as agents move from prototypes to production, the calculus changes. Production systems need: - Memory continuity across sessions - Predictable behavior across updates - Security boundaries that don't leak

The tools that prioritize these will win the enterprise market. The ones that don't will stay in the prototype/hobbyist space.

We're still in the "move fast" phase, but the "break things" part is starting to hurt real users. The pendulum will swing back.

Only for the non-pro users. After all, those users were happy to use excel to write the programs.

What we're seeing now is that more and more developers find they are happy with even less determinism than the Excel process.

Maybe they're right; maybe software doesn't need any coherence, stability, security or even correctness. Maybe the class of software they produce doesn't need those things.

I, unfortunately, am unable to adopt this view.

I'm 13 years into this industry, this is the first I'm hearing of this.

Also most of the long running enterprise projects I’ve seen - there was one that had been around for like 10 years and like about 75% of the devs I hadn’t even heard of and none of the original ones were in the project at all.

The thing had no less than three auditing mechanisms, three ways of interacting with the database, mixed naming conventions, like two validation mechanisms none of which were what Spring recommended and also configurations versioned for app servers that weren’t even in use.

This was all before AI, it’s not like you need it for projects to turn into slop and AI slop isn’t that much different from human slop (none of them gave a shit about ADRs or proper docs on why things are done a certain way, though Wiki had some fossilized meeting notes with nothing actually useful) except that AI can produce this stuff more quickly.

When encountered, I just relied on writing tests and reworking the older slop with something newer (with better AI models and tooling) and the overall quality improved.