@huoshan007: Hey guys, if you're still only selling material packs on Xianyu and manually processing each one, it's time to upgrade. Recently, my friend has been combining AI-generated materials with Codex automation, which has doubled efficiency and earnings—at least five figures per month. The core is selling virtual finished products: Xiaohongshu cover template packs, e-commerce detail page long images, emoji collection…

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Summary

This article shares methods for using AI image generation and Codex automation tools to batch process digital materials and sell them on the Xianyu platform to improve efficiency and earnings.

Hey guys, if you're still only selling material packs on Xianyu and manually processing each one, it's time to upgrade. Recently, my friend has been combining AI-generated materials with Codex automation, which has doubled efficiency and earnings—at least five figures per month. The core is selling virtual finished products: Xiaohongshu cover template packs, e-commerce detail page long images, emoji collection, wallpaper packs, editable poster source files… These can be listed for sale; customers purchase and automatically receive a link, with almost no after-sales needed. But previously, the most annoying part was post-processing: After generating hundreds of images, you still have to batch resize, uniformly rename, add watermarks, create zip packages, make preview collages, write usage instructions. Doing this manually for a set takes half an hour, and with large volumes, it's unbearable. Now the process is like this: 1. First, use AI (any image model) to batch generate images, producing 50-200 at a time. 2. Hand the requirements directly to Codex: 'Write a Python script that batch scales all images in a folder to specified sizes, uniformly names them as 'style-number', automatically adds watermarks, generates a 9-grid preview image, packs everything into a zip, and outputs a simple usage instruction txt.' 3. Codex produces a complete script in a few minutes; run it locally, and the entire material set becomes a ready-to-list finished pack. 4. When listing on Xianyu, use a hot-selling structure for titles and main images, set prices between 9.9 and 29.9, and go for volume. The most critical point: Many processing logic can be turned into templates. Next time, just change a few parameters and run the script again. Generation → processing → packaging, the entire process compressed to within 10 minutes. Previously, with pure manual work, you could list at most 3-5 packs per day. Now, with Codex, you can easily list 15-20 per day, and orders keep coming. Customers are completely unaware. They only see 'instant use, commercially viable, large quantity' and don't care what tools you used behind the scenes. On platforms like Xianyu, what truly allows for sustained earnings is never the most complex technology, but maximizing delivery speed and replicability. Materials are generated with AI, processing is handled by Codex automation; combining the two minimizes time and effort costs. If you're still manually grinding materials, you should really try adding Codex. Not to write business code, but to handle those repetitive, dirty tasks in one go. Playing this way is more like a sustainable Xianyu strategy.
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Cached at: 08/17/26, 12:04 AM

Guys, if you’re still manually processing assets one by one to sell on Xianyu, it’s time to level up.

My friend recently doubled both efficiency and monthly earnings (now consistently five figures) by combining AI-generated assets with Codex automation.

The core remains selling virtual finished products: Xiaohongshu cover template packs, e-commerce product detail long images, sticker collections, wallpaper packs, editable poster source files…

These can be listed directly. Once a customer purchases, a link is sent automatically, with almost no after-sales support needed.

But the biggest headache used to be post-processing: After generating hundreds of images, you’d still need to batch resize, uniformly rename, add watermarks, create ZIP archives, make preview collages, and write usage instructions.

Doing this manually for one set took half an hour—completely unsustainable at scale.

Now the workflow is streamlined:

  1. Use any AI image model to batch-generate 50-200 images at once.

  2. Feed the requirements directly to Codex: “Write a Python script that: batch resizes all images in a folder to specified dimensions, uniformly names them in the format ‘style-number’, automatically adds a watermark, generates a 9-grid preview image, packages everything into a ZIP file, and outputs a simple usage instruction text file.”

  3. Codex delivers a complete script in minutes. Run it locally, and the entire asset set transforms into a ready-to-list product package.

  4. When listing on Xianyu, use proven high-performing structures for the title and main image. Price it between ¥9.9-¥29.9 and focus on volume.

The crucial point: Many processing logic steps can become templates.
Next time, just change the style, tweak a few parameters, and rerun the script.
Generation → Processing → Packaging: the entire workflow compresses to under 10 minutes.

Previously, with pure manual work, you could list at most 3-5 packs per day.
Now, with Codex, you can easily list 15-20 per day, and orders keep coming in.

Customers are none the wiser.
They only see “instant download, commercially usable, vast quantity”—they don’t care what tools you used behind the scenes.

On platforms like Xianyu, what truly sustains profit isn’t the most complex technology,
but maximizing delivery speed and replicability.

Generate assets with AI, automate the processing with Codex.
Combining the two minimizes both time and effort costs.

Guys, if you’re still manually grinding on assets, seriously try integrating Codex.
Not to write business logic, but to eliminate all that repetitive, dirty work in one go.

This is how you build a truly sustainable Xianyu operation.

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