Manus builds a smokehouse order and prep system
Chan reports using Manus to build a meat-preparation calculator and FLAME order system for Mandai Smoke Co, combining website and WhatsApp orders with delivery planning.
manus.im
Suggested prompt
Suggested prompt written by Agents In Use, not the source author. Replace bracketed inputs and review tool permissions first.
Build a prep calculator from [our order data] and [verified yield and ingredient rules]. Make the calculations inspectable. After I validate it, add order consolidation and flags for missing delivery-address fields.
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Sourced account- Source author
- Manus interview with Royston Chan
- Original account
- Read the source ↗
- Published
- Source link checked
- Reported result
- Chan reports using Manus to build a meat-preparation calculator and FLAME order system for Mandai Smoke Co, combining website and WhatsApp orders with delivery planning.
- Human involvement
- Chan iterates on the calculator and the family handles cooking and fulfilment. The source’s order volume is self-reported, and no independent operational audit is provided.
A linked account supports attribution. It does not mean we independently reproduced its result.
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How the agent did it
- Supply the smokehouse’s order and preparation rules to Manus.
- Build and iterate on a raw-meat and ingredient calculator.
- Combine website and WhatsApp order information in the operational system.
Royston Chan operates Mandai Smoke Co, a home-based Texas barbecue business in Singapore. He starts with a practical preparation problem: translate incoming orders into the raw-meat and ingredient quantities needed for a cook. Manus builds a calculator, and Chan iterates on it until it works for his process.
The project grows into FLAME, a food-logistics and management system. It combines website and WhatsApp orders, flags incomplete delivery addresses such as missing condominium unit numbers, and helps group delivery routes geographically. A custom inbox using Twilio's WhatsApp Business API supports order communication and customer segmentation.
Chan reports handling around three hundred monthly orders with the system; that figure is a customer report in Manus's promotional interview, not an independently audited measure. The family still cooks and fulfils the orders. Manus is credited with building operational software, not autonomously preparing food or driving deliveries. The useful starting point is the specific prep calculation before adding broader order-management features. The source does not disclose meat-yield formulas, quantities for a real order or an original prompt, so the suggested instruction below asks a reader to supply those business rules rather than inventing them.
Prompt
Suggested prompt (written by Agents In Use, not the author's)
Source: Blog · Manus interview with Royston Chan
Frequently asked questions
What was the first useful tool?
A calculator translating incoming orders into raw-meat and ingredient preparation quantities.
Which address problem was caught?
The system flags incomplete addresses, including missing condominium unit numbers, before delivery planning.
Did Manus cook or deliver orders?
No. The reported agent work is building the software; the family operates the smokehouse and fulfils orders.
More details
Remaining steps
- Flag incomplete addresses and group deliveries geographically.
- Have the family use the resulting preparation and order workflow.
About this account
Manus builds and revises the operational software from the owner’s requirements; the resulting system supports order preparation and delivery planning.
Firsthand account by Manus interview with Royston Chan; original publication date verified against Primary customer-story date May 11, 2026. Outcomes are the author’s reports, not independently reproduced. Suggested prompt written by Agents In Use; not the author’s original prompt.
Credit: Manus interview with Royston Chan
Source published
Added to Agents In Use
Source checked
Tools and topics
Manus · FLAME · Website orders · WhatsApp Business API · Twilio
Smokehouse preparation · Order consolidation · Delivery addresses
Editorial completeness: 100/100. Measures documented fields, not agent performance or verified outcomes.