Build a store ops agent that turns notes into next steps
They used an open-source agent to digest voice notes, track store activity, and surface one task to do next across several online businesses.
- What they did
- They based the system on Nous Research’s Hermes Agent, added a third-party LLM gateway, and set up a three-level router: a low-cost model for routine work, a stronger one for unclear cases, and a local option for outages or private tasks. The agent took in voice notes or rough text from two crowdfunding campaigns, an Amazon shop, and a Shopify site, then ran every five minutes to review orders, ad spend, inbox flags, and a task list. It also kept one memory file current and returned a single recommended next action, along with weekly and monthly summaries.
- How it went
- After six months, they said this loop kept working in a way Notion, Todoist, and simple CRMs had not. The routing setup cost about 60–70% less than sending everything to a top-tier model, and it was more dependable overall, though it still sometimes misclassified tasks, missed details, or produced reports and automations that were not useful.
- Tips
- They found it was better to begin with only three working automations: a daily report, a next-task suggestion, and a weekly recap. They also learned that overbuilding too early made the setup brittle.
Try it yourself with OpenClaw
You are my operations agent for [Shopify store / Amazon store / crowdfunding campaign]. Every five minutes, review [orders], [ad spend], [inbox flags], and my [task list]. Turn any [voice notes / messy text] I add into a short report, update a single memory file, and suggest one next task I should do. Use a cheaper model for routine checks, a stronger model when the situation is unclear, and a local fallback if the main service is down or the task is private. Before you change any ad budget, send any message, delete anything, or submit any listing or form, pause and ask for my approval. Also send me a daily summary and a weekly recap.
Fill in the [brackets]. Agents can make mistakes, so review anything before it is sent, paid or deleted.
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