Agreed.

Even in the case of a single agent, the compounding of errors [1] can easily make your "flow" unacceptable for your use case. The deterministic where possibe/decoupled/well tested approach is key.

With such a fast moving space I'm always wary of adopting optimization techniques that I can't easily prove and pivot from (which means measuring/evals are necessary).

Slowly but surely, abstractions allow us to use others' deep investments in the matter of coordination without losing control (e.g. pyspark worker/driver coordination) and we can invest on friction removal and direct value generation in our domains (e.g. banking/retail/legal payments, etc)

- [1] https://alexhans.github.io/posts/series/evals/error-compound...