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Claude and Muse handle meal planning, pantry inventory and recipe tracking, then Muse reads a Google Doc and places the grocery order in a browser, with the poster confirming payment from their phone.
Claude and Muse handle meal planning, pantry inventory and recipe tracking, then Muse reads a Google Doc and places the grocery order in a browser, with the poster confirming payment from their phone.
The poster says they built a workflow with Claude and Muse to run a two-week household meal cycle. Claude uses household preferences plus feedback from prior meals to draft the plan, then after the person approves it, Claude makes a Walmart grocery list, adds low pantry staples and other requested items, and writes the shopping list to a Google Doc that Muse reads to place the order in its browser; the person only supervises and confirms final payment from their phone.
It was functional enough that the poster says they now use it for meal planning, grocery orders, recipe tracking, pantry inventory, meal feedback, and a kitchen display. No savings, accuracy metrics, or ordering error rates were given.
The main catch is that checkout was not fully autonomous: the poster still had to supervise and approve the final pay step from their phone.
Read my meal plan and grocery list in this Google Doc: [link]. Check the items against my pantry list, then add what is missing to my cart at [grocery store] in the browser. Stop at checkout and show me the cart and total so I can confirm payment myself.
Score every demo request against your ICP, update HubSpot and ping the right rep in Slack within a minute of the form submit.
Every new Zendesk ticket gets a category, priority and sentiment tag plus a draft reply in an internal note before an agent opens it.
Copilot and Claude review each PR for bugs, missing tests and risky changes before a human looks, so reviewers can focus on design.