AI Phone Control for Short Video Publishing: Workflow Template Guide

The publish chain is the bottleneck

Bulk short-video posting gets stuck on a fixed publish chain. A standard flow has 7 to 10 steps: open the app, log in, enter the publish page, pick the video, fill the title, add topics, set the cover, and submit for review. Doing it by hand takes 3 to 5 minutes. At 5 to 10 posts a day, the repetition eats a large share of the time. When you are still posting the eighth one by hand after midnight, the thought of publishing short video with AI shows up for almost everyone running a matrix.

Stage	Time by hand	After AI automation
Log in on each phone	30 seconds per phone	One authorization, valid for the long term
Pick the video and fill the details	3 minutes per video	A preset template, applied in one step
Add topics and set the cover	2 minutes per video	Filled from a preconfigured list
Submit and confirm success	1 minute per video	Checked in the background and reported back

Prepare four things before you use it:

• Account context. Which account this video is for. Avatar, display name, and bio affect how the AI judges the screen.
• Copy. The title text for the video. Prepare several alternatives.
• Where the media comes from. The video is in the local gallery, or it has to be downloaded from a URL.
• Target app. Douyin, Xiaohongshu, or WeChat Channels, according to the matrix you run.

Two ways to dispatch, then running and scheduling

iEasyRun uses the short-video publish workflow in two ways.

1. Natural-language dispatch, which is the path for someone new to it. Say one sentence in the conversation box, for example: “Tomorrow at 9:00, use phone 2 to post a Douyin video. The copy is ‘xxx’, and the video is in my phone gallery.” The system parses that and creates the task.
2. API integration, for developers. Call run_workflow in the MCP tools, pass the parameters yourself, and control it from a program.

After the task is dispatched, the console shows progress:

• Status moves from pending to running, then to succeeded or failed. A failure comes with a readable error, such as “video resource not found”.
• The log timeline has the finish time, duration, and assertion result for each step.
• The result can come back through a webhook, or through the MCP get_task interface.

If it fails in the middle, the system reports the step that stalled so a person can step in or adjust the flow. That reporting is more reliable than a traditional automation script.

These are planned for the P1 stage:

• Scheduled publishing. Set an exact time, or publish on an interval, such as one video every 30 minutes, and the AI runs it when the time arrives.
• Multi-device batch. One instruction dispatches the same or different tasks to 5 phones, or more, at once. For bulk short-video posting, this is the least fuss.
• Failure retry. Set a retry count and interval, for example stop after 3 consecutive failures and notify an admin.

Turn the working pattern into a template and let the AI run the template. What publishing short video with AI gives back is those two or three hours a day. Installation is in the deployment guide.