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From product selection to content creation: My practice sharing on building an AI workspace for text and image recommendations

Last Saturday, I shared at an offline gathering how I use [tool]. My presentation was a bit fast-paced, especially regarding the practical steps, which I didn't have time to elaborate on. Over the past two days, I've revised a written draft that includes the complete workflow and operation screenshots: from product selection to content creation, finally building an AI workstation.

Presenter: Magical Sangsang 😄😄😄2026.10.20
Summary

Review the results before exploring further

Last Saturday, I shared at an offline gathering how I use . The session moved quickly, especially the practical parts, so some steps weren't fully covered. Over the past two days, I've revised a written draft that includes the complete workflow and operation screenshots: from selecting products in the virtual data niche, to finding benchmarks on Xiaohongshu (Red) and sourcing/tracing items on Xianyu (Idle Fish), then moving through content creation and platform publishing. Finally, I use Obsidian to organize materials, connecting scattered operations into an AI workspace. Besides how it works specifically, I also kept the bottlenecks encountered during the process and questions asked by attendees in person: This piece is more like a complete practice case study. If you are also exploring AI content production,

Our Take

Three things to consider about this case

Why it matters
Complete one piece of content first, check quality and manual revision time, then consider batch production.
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.
Our Suggestions / Try This
Who it suits
Individuals who need to process images and assets
What to try first
Run the processing workflow using one piece of real material and compare the effects before and after processing.
What to measure
Check clarity, text accuracy, and whether results can be directly used for actual tasks.
Try Image Text Extraction ↗

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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