Writing detailed documentation is a task most employees avoid. By recording a quick video walkthrough of a process (e.g., how to pull a report), that video can be shared, referenced, and then automatically transcribed by AI into a structured SOP, eliminating the friction of manual writing.

Instead of starting with a tool like Zapier and searching for ideas, first meticulously document every step of a specific workflow. This reveals the actual opportunities for automation and prevents "blank cursor syndrome."

Instead of writing a lead magnet from scratch, record a 2-hour session of you performing an expert task. Use AI tools to transcribe the session and then extract the core frameworks, prompts, and thought processes into a detailed playbook.

"Skills" are markdown files that provide an AI agent with an expert-level instruction manual for a specific task. By encoding best practices, do's/don'ts, and references into a skill, you create a persistent, reusable asset that elevates the AI's performance almost instantly.

To find tasks ripe for AI automation, simply screen record yourself performing a repetitive, hour-long task. Then, upload the video to a multimodal LLM like Gemini 3 and ask it what parts can be automated and how much time you could save. This provides concrete, actionable suggestions.

To discover prime candidates for automation, record a screen video of yourself performing a repetitive, manual task. You can upload this video (up to an hour long) to Google Gemini, which will analyze the workflow, break it down into steps, and provide a concrete plan for how to automate it.

Overcome the hurdle of documenting processes by recording a screen-share video of yourself performing a task while talking through the steps. AI tools can then automatically convert the recording into a written playbook, eliminating the need to set aside dedicated writing time.

The most effective way to build a powerful automation prompt is to interview a human expert, document their step-by-step process and decision criteria, and translate that knowledge directly into the AI's instructions. Don't invent; document and translate.

Instead of pre-designing a complex AI system, first achieve your desired output through a manual, iterative conversation. Then, instruct the AI to review the entire session and convert that successful workflow into a reusable "skill." This reverse-engineers a perfect system from a proven process.