Build a Short Form Video Farm with Higgsfield + Claude Code

In this guide, you will learn how to set up a Codex project that lets you test, generate, and improve short-form video with Higgsfield from your terminal. Instead of making one-off clips, you will create a video workstation with campaign folders, saved outputs, reusable skills, and a feedback loop.

• **Creators and marketers** who want a faster way to test short-form video ideas without rebuilding the same prompts every time
• **Operators and agencies** who need campaign folders, saved outputs, and tracking files instead of scattered generations
• **Anyone building agent workflows** who wants a practical example of CLI tools, skills, feedback, and automation working together

You will build a Higgsfield video generation workstation inside a normal project folder. The folder gives Claude Code or Codex a place to create campaigns, save generated videos, track feedback, and turn the process into reusable skills.

By the end, you will have a working setup that can create a campaign, generate two Higgsfield videos from the terminal, save the outputs, improve the prompts from your feedback, and eventually run the same process on a schedule.

• Claude Code, Codex, or another agent that can work inside a local project folder
• A Higgsfield account
• The Higgsfield CLI from `https://higgsfield.ai/cli`
• A brand, product, or campaign idea to use for the first test
• A few minutes to review prompts before any generation spends credits

Use the system manually for about five days or five campaigns before you automate it. That gives Claude enough examples to learn from your real feedback instead of guessing your taste.

After that, ask Claude to create a daily automation:

Create a daily automation for this Higgsfield video workstation.

Every day, it should:
1. Review the previous campaigns and my feedback.
2. Identify patterns in what worked and what failed.
3. Come up with one new campaign idea.
4. Create the campaign folder.
5. Generate one set of videos.
6. Save the outputs and update tracking.md.
7. Suggest one improvement to the generation or iteration skill.

Before spending Higgsfield credits, show the planned campaign and commands for approval unless I explicitly turn on automatic generation.

Do not automate blind generation on day one. Start by automating the review, idea generation, and skill-improvement loop. Once the campaigns are consistently good, you can decide whether daily generation should run automatically or wait for approval.

The reusable pattern is simple:

1. Create the workstation.
2. Generate two videos.
3. Save the outputs.
4. Turn the workflow into a skill.
5. Give feedback.
6. Turn the improvement loop into a skill.
7. Automate after the system has examples to learn from.

That is how you move from one-off Higgsfield experiments to a short-form video system you can keep scaling from the terminal.