Most teams build their first agentic workflow in Python almost by accident. A script sends support tickets to a model, the demo sorts twenty of them nicely, and then the real queue shows up. Soon one prompt has become five jobs: read the ticket, pull out the facts, spot customers who might leave, draft a reply, and have someone check it before it goes out.
Now the hard part is the wiring, not the prompt: what runs first, what can run side by side, what happens when a step breaks, and what it all costs each month. It's tempting to grab the biggest framework you've heard of. Often you don't need it.
This guide builds the few shapes that nearly every multi-step AI process takes, from ticket triage to content work to research briefs, in short readable code. Then it helps you decide whether a lighter tool can carry your process or a heavier framework is worth the weight.
