I worked on a somewhat similar system in a fringe language (Scheme, and later, Racket) that got huge, but that remained manageable and high-velocity over a long period by a small team.

We didn't create many bugs, and usually functionality could be added very rapidly (e.g., we were the first to achieve a certain certification for hosting sensitive data on AWS).

Though occasionally functionality had to be added more slowly, because we had to write from scratch what would be an off-the-shelf component in a more popular platform. But once we did it, it worked, and we were back to our old velocity, and not slowed by the bloat and complexity of dozens of off-the-shelf frameworks. We could also adapt rapidly because we controlled a manageable platform, which is how we were able to move fast to AWS when there was a need.

The system also had some technical bits of architectural secret sauce from the start (for complex data, and Web interaction), which enabled a lot of rapid development of functionality, and also set the tone for later empowering smartness.

One difference with our system, from the Haskell fintech, was that our team size was very small (only 2-3 software engineers at a time, and someone who managed all the ops). So we didn't have the challenges of hundreds of people trying to coordinate and have a coherent system while getting their things done. Instead, there was usually one person doing more technical and architectural changes to the code, and a prolific other person doing huge amounts business logic functionality for complex processes.

With careful use of current/near-term LLM-ish AI tools, software development might find some related efficiencies of very small and incredibly effective teams. But the model that comes to mind is having a small number of very sharp thinkers keeping things on an empowering and manageable path -- not churning massive bloat to knock off story points and letting sustainability be someone else's problem.