A client asked me to build an "agent" that makes their weekly decks. It was three connector steps and one API call.

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Summary

The author recounts a client request for an AI agent to build weekly campaign decks, which turned out to be overkill; they implemented a simple scheduled connector pulling fixed metrics into a template via an API call, arguing that deterministic pipelines often deliver more value than autonomous agents when the output structure is constant.

This is in the same spirit as the "I charge more to NOT build an agent" posts, because it happened again and I think the pattern is worth naming. Marketing lead comes to me wanting an "AI agent" that builds their weekly campaign recap deck. He'd seen a demo and was picturing something autonomous that watches everything and just knows. I asked what actually goes into the deck today. Answer: the same five metrics pulled from the same dashboard, arranged the same way, every single week. There was nothing for an agent to decide. The structure never changes. So I didn't build an agent. I built a scheduled connector flow. Trigger fires every Friday, pulls the five numbers, drops them into a fixed outline (headline per section, prior-week delta, one line of context), and hands that outline to a deck-generation API that returns a link. No model deciding structure, because the structure is a constant. It runs itself and costs him almost nothing. Where a real agent would've earned its keep is if the input were messy, like free-text notes or unpredictable campaign types where something has to interpret each one. His input wasn't messy. It was five numbers and a template. That's a cron job, not a brain. I used gamma's API behind the connector for the render because it plugs into the no-code tools without custom glue, though the honest catch is the card format doesn't give a clean PPTX if his team ever wants to hand-edit in PowerPoint, and the credit cap means this only works because the volume is low. For a fixed weekly recap it's the right amount of machinery. An agent would've been more cost, more failure modes, and zero more value. The reframe I keep coming back to: before you build an agent, check whether the decision actually varies. If the shape of the output is a constant, you want a deterministic pipeline, not a model. Where's the line for everyone else, when do you decide a recurring deck task genuinely needs agentic behavior instead of a connector and a template?
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