Workflows versus agents: how much autonomy should you actually give an AI system, and how do you decide?
The industry uses 'agent' for anything that calls an LLM. The distinction that matters is how much control you hand to the model, and more autonomy is not better. Here is the spectrum and the decision rule.
Updated Sep 2026 · Grounded in real GenAI, LLM, and AI/ML engineering interview loops and written to a senior-engineer editorial bar.
The industry uses 'agent' for anything that calls an LLM. The distinction that matters is how much control you hand to the model, and more autonomy is not better. Here is the spectrum and the decision rule.
Lead with where the obvious approach breaks, because that is the judgment they are screening for — most candidates jump straight to the happy path and lose the room.
Then walk the failure back through the pipeline in order, naming the one metric the customer's exec sponsor actually cares about before you propose the fix.
