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Hands-on AI Playbook

Workflow Example: AI Collaborative

AI involvement: AI handles research and drafting; the human steers, reviews, and decides.

What This Workflow Type Is

Section titled “What This Workflow Type Is”

An AI collaborative workflow is one where the human and AI work together — the AI performs tasks like research, analysis, or drafting, and the human provides judgment, context, and final decisions. Neither operates alone. The human sets the direction; the AI handles the legwork.

Characteristics

Section titled “Characteristics”
  • Iterative — the human and AI go back and forth, refining the output
  • Judgment-dependent — the AI can gather and organize information, but the human decides what matters
  • Context-rich — the AI benefits from knowing the human’s goals, preferences, and constraints
  • Quality-gated — the human reviews before the output is used

When to Use

Section titled “When to Use”

Use AI collaborative workflows when the task:

  • Requires research, synthesis, or analysis that’s time-consuming for a human
  • Involves subjective judgment that can’t be fully encoded in rules
  • Benefits from a draft that the human can refine rather than create from scratch
  • Produces higher-quality output when a human reviews and adjusts

Example Scenario

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The problem: Before important meetings — sales calls, partnership discussions, interviews — a professional spends 20-45 minutes manually researching attendees on LinkedIn, scanning company news, and assembling talking points. The research is necessary but tedious, and the quality varies depending on how much time is available.

The solution: An AI agent that handles the research and produces a structured meeting prep brief. The human reviews the brief, adjusts the talking points, and walks into the meeting prepared — with a fraction of the manual effort.

Building Blocks

Section titled “Building Blocks”
Building BlockTypeDescriptionSource
meeting-prep-researcherAgentResearches attendees and companies, produces a meeting prep briefView on GitHub
preparing-meeting-briefsSkillStep-by-step research workflow for the agent to followView on GitHub
meeting-prep-quickPromptPortable one-shot prompt for quick meeting prep in any AI toolView on GitHub

How It Works

Section titled “How It Works”
graph LR
    A[User provides<br>meeting details] --> B[AI researches<br>attendees & company]
    B --> C[AI drafts<br>prep brief]
    C --> D[Human reviews<br>and refines]
    D --> E[Final prep brief<br>ready for meeting]

Step-by-step:

  1. User provides context — who the meeting is with, what company, what the meeting is about, and what outcome they want.
  2. AI researches attendees — searches for LinkedIn profiles, recent posts, and public activity for each person.
  3. AI researches the company — finds recent news, strategic direction, and relevant industry context.
  4. AI drafts the prep brief — produces a structured document with attendee profiles, company snapshot, suggested talking points, questions to ask, and potential landmines.
  5. Human reviews and refines — the user reads the brief, adjusts talking points to match their style and goals, and decides what to use in the meeting.

Usage

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Use the meeting-prep-quick prompt for a lightweight, one-shot version in any AI tool.

  1. Open the meeting-prep-quick prompt on GitHub
  2. Copy the prompt from the code block
  3. Paste it into Claude, ChatGPT, Gemini, or M365 Copilot
  4. Fill in the meeting details and send
  5. Review the output and adjust talking points to match your style

Adapting This Example

Section titled “Adapting This Example”

Meeting prep is one scenario, but the collaborative pattern applies to any task where AI handles research and drafting while the human provides judgment:

  • Competitive analysis — AI researches competitors, drafts a comparison matrix; human validates and adds strategic context
  • Proposal drafting — AI structures a proposal based on requirements; human refines messaging and adds relationship context
  • Job candidate screening — AI summarizes resumes and flags qualifications; human makes interview decisions
  • Customer research — AI compiles account history and recent activity; human identifies upsell opportunities

To adapt: identify tasks where you spend significant time gathering information before applying judgment. The gathering is AI work; the judgment is human work.

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