AI Fire Weekly Webinar

Hands-on AI workshop for real work use cases every week

88 followers

Hands-on AI workshop for real work use cases every week

88 followers

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AI Generative Media

AI Fire Weekly Workshop is a hands-on session focused on applying AI to real work. Each week, we explore practical use cases such as content creation, workflow automation, AI agents, and productivity systems. You will learn how to structure prompts, build repeatable workflows, and choose the right tools for your needs. The workshop includes live demos, real examples, and clear frameworks so you can apply AI immediately in your daily work. Suitable for beginners and professionals.

This is the 63rd launch from AI Fire Weekly Webinar. View more

Build AI Marketing Team In ChatGPT Work

Launching today

ChatGPT Work for Marketing: Skills, Agents, Automation

This webinar explains how ChatGPT Work, Skills, Workspace Agents, and Subagents fit together, when to use each one, and how they differ from normal Chat. Alex covers the core mindset and terminology, then Eric shows a practical marketing workflow using specialized agents and the Review Now Skill. You’ll also see how the same delegation mindset carries over to Claude Cowork.

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Free

Launch tags:Marketing•Artificial Intelligence•YouTube

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Hi Product Hunt 👋 This webinar is a practical beginner-friendly guide to ChatGPT Work, Skills, Agents, and Subagents. The main question is simple: when should you use normal Chat, when should you use Work, and where do Skills and Agents fit into the picture? Alex first breaks down the key concepts and differences. Then Eric shows how those ideas work together inside a real marketing workflow. Inside the webinar, we cover: - What ChatGPT Work is and when to use it - The difference between Chat, Work, Workspace Agents, and Subagents - How Skills store reusable methods and instructions - How specialized agents can handle repeatable marketing roles - How the Review Now Skill fits into a real content workflow The goal is to give beginners a clear mental model before they start building more advanced AI workflows. Curious to hear from you: which part would you want us to turn into a deeper follow-up tutorial?

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