Really interesting take on the idea of putting a lightweight decision layer in front of an AI agent. I especially liked the principle of “Jev chooses, code decides”—that separation makes a lot of sense when you’re dealing with actions where the cost of a wrong decision can be high.

The finance example was also a great way to make the architecture concrete. Having the model narrow down intent while leaving limits, balances, permissions, idempotency, and final confirmation to deterministic code feels like a much more realistic approach than asking an LLM to handle everything.

The cost discussion is interesting too. Saving money on routing only really matters if the extra dependency and latency don’t introduce new problems, so I appreciated that the post acknowledges that trade-off rather than presenting the decision layer as a free optimization. Great practical read!