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Detailed case study from the Nanchang meetup: Lu Tu's hands-on navigation station project, seed keyword research, and AI work methods.

On October 30, I attended the Shengcai Youshu Nanchang local meetup. There, Lu Tu, a group leader in Jiangxi's business circle, shared his navigation station project and explained how he integrates AI into research, operations, and daily work. The session was packed with content. I organized it around these themes: How to launch the project, how to conduct research, how to execute, how to operate, and how AI supports the process.

Contributor: Lao Lian2026.10.31
Summary

Review the results before exploring further

On October 30, I attended the Shengcai Youshu Nanchang local meetup. There, Lu Tu, a group leader in Jiangxi's business circle, shared his navigation station project and explained how he integrates AI into research, operations, and daily work. The session was packed with content. I organized it around these themes: How to launch the project, how to conduct research, how to execute, how to operate, and how AI supports the process. I've also preserved the Q&A and key insights from the event. All quotes are based on a transcription of the live recording, with minor omissions for spoken pauses and repetitions. My biggest takeaway comes first: I frequently use the Transit Station tool and often compare prices to find cheaper tokens, but I never considered turning this need into a business until Lu Tu showed me...

Our Take

Three things to consider about this case

Why it matters
First, run a small, verifiable task, recording the outcome, manual modifications, and maintenance effort.
Who it suits
Suitable for reference by those who already have similar needs and can verify effectiveness through small tasks.
What to check first
The achievements mentioned in the summary belong to the author's self-report; distinguish between revenue and profit, and consider costs, man-hours, and reproduction conditions.

What should you ask before trying this?

  • What specific need does this practice solve for you?
  • How should the minimum viable test be accepted, and how much time needs to be invested?
  • Which steps still require human processing and continuous maintenance?
Still deciding? Read our decision guides
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