Loops vs. graphs: a new way to structure agent workflows around company memory
femke_plantinga · x · 2026-07-23
The post lays out two ways to run an agent on the same support task: loops and graphs.
- Loops: you define the goal and quality bar, and the agent owns the path, drafting, checking, and retrying until it passes.
- Graphs: you define the workflow up front — read → triage → draft → QA → send — and the agent fills each node.
Both rely on a shared company brain: past tickets, policies, and product docs that each step can pull from as the work moves through the process. The takeaway is simple: use loops for one-off, exploratory work; use graphs when the work is repeatable and the path is already known.
Related event: Evolution of AI Agent Architecture: From Loops to Graph Engineering(8 posts)→
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