Git for Product Requirements: A Team Collaboration Workflow Powered by AI

It’s Tuesday morning. Your engineering lead emails you: “Which version of the checkout redesign requirements should we follow? Sarah sent PRD_v3_final.docx last week, but I see comments in the Jira ticket that contradict it, and the Confluence page was updated yesterday with different acceptance criteria. Also, nobody responded to my inline comment in the Word doc—did anyone even see it?” You open your inbox: 47 unread messages, three different requirement documents with similar names, and a nagging feeling that critical feedback from the support team got lost somewhere in a comment thread. Sound familiar?

Product requirements shouldn’t live in siloed Word docs sent over email, Jira tickets with sprawling comment threads you can’t track, or Confluence pages where version history is a maze of “Page edited by…” notifications. If your code lives in git with clear diffs, version control, and collaborative PRs, why shouldn’t your requirements?

This post presents a practical workflow that brings product requirements into git-based collaboration, leveraging AI to bridge the gap for non-technical team members and transform how teams capture, refine, and align on product direction.

The Complete Workflow

Here’s the entire process at a glance:

graph TB
    A[Prepare Kickoff Document<br/>PRD v0.1] --> B[Share with Diverse Team<br/>Upfront]
    B --> C[Record Kickoff Meeting<br/>Diverse Audience]
    C --> D[Generate AI Transcript]
    D --> E[AI Knowledge Extraction]
    E --> F[Update Document<br/>PRD v0.2]
    F --> G[Create Pull Request]
    G --> H[Team Reviews & Comments]
    H --> I{Feedback<br/>Complete?}
    I -->|No| H
    I -->|Yes| J[AI Prototype Creation<br/>Low-Fidelity]
    J --> K[Share for Feedback]
    K --> L{Consensus<br/>Reached?}
    L -->|No| J
    L -->|Yes| M[Handoff to Engineering]
    M --> N[Real Implementation]

    style A fill:#e1f5ff
    style F fill:#e1f5ff
    style J fill:#fff4e1
    style M fill:#e1ffe1

Let’s break down each phase of this workflow.

Step 1: Prepare the Kickoff Document (PRD v0.1)

The journey begins with a brief, focused document that serves as both meeting agenda and initial requirements capture.

graph LR
    A[Identify Problem Space] --> B[Draft Brief Document<br/>1-2 pages]
    B --> C[Key Questions<br/>to Answer]
    C --> D[PRD v0.1<br/>Kickoff Doc]
    D --> E[Commit to Git Branch]

    style D fill:#e1f5ff
    style E fill:#d4edff

What makes this work:

Keep it brief—1-2 pages maximum
Focus on questions, not answers
Include context: what problem are we solving, for whom, and why now
Store in a feature branch: requirements/feature-name

Key principle: The kickoff doc is intentionally incomplete. It’s designed to spark conversation, not provide all answers.

Distribute the kickoff document before the meeting to maximize meeting effectiveness.

graph LR
    A[PRD v0.1 Ready] --> B[Identify Stakeholders]
    B --> C[Engineers, Designers,<br/>Product, Support,<br/>Sales, Users]
    C --> D[Share via PR Link or<br/>Direct File Access]
    D --> E[Give 24-48h Review Time]

    style C fill:#fff4e1

Why diversity matters:

Engineers spot technical constraints
Designers identify UX implications
Support knows customer pain points
Sales understands market dynamics
Actual users provide ground truth

Non-technical participation: Share the GitHub PR link with a rendered view, or export to PDF if needed. The goal is input, not git expertise.

Step 3: Conduct and Record the Kickoff Meeting

Host a collaborative kickoff meeting with your diverse audience and capture everything.

graph TB
    A[Schedule 60-90 min Meeting] --> B[Ensure Recording Consent]
    B --> C[Facilitate Discussion<br/>of PRD v0.1]
    C --> D[Capture Decisions,<br/>Questions, Concerns]
    D --> E[Record Audio/Video]
    E --> F[Save Recording]

    style C fill:#e1ffe1
    style E fill:#ffe1e1

Meeting best practices:

Start with the document structure
Encourage debate and disagreement
Capture “why” behind decisions
Don’t try to document everything in real-time—that’s what the recording is for

Step 4: AI-Powered Transcription and Knowledge Extraction

This is where AI becomes your collaboration superpower.

graph LR
    A[Meeting Recording] --> B[AI Transcription<br/>Whisper, Otter, etc.]
    B --> C[Raw Transcript]
    C --> D[AI Analysis<br/>Claude, GPT-4]
    D --> E[Extract:<br/>Decisions, Questions,<br/>Action Items, Context]
    E --> F[Structured Knowledge]

    style D fill:#fff4e1
    style F fill:#e1f5ff

AI prompt framework:

Analyze this product kickoff meeting transcript and extract:
1. Key decisions made and their reasoning
2. Open questions that need resolution
3. User needs and pain points discussed
4. Technical constraints or considerations mentioned
5. Stakeholder concerns and objections
6. Action items and owners

Format this to update our PRD v0.1 document.

The magic: Non-technical stakeholders contributed via conversation, and AI translates that into structured documentation. No one needs to master markdown or git.

Step 5: Create PRD v0.2

Update the initial document with AI-extracted insights and push a new version.

graph TB
    A[AI-Extracted Knowledge] --> B[Human Reviews<br/>AI Output]
    B --> C[Update PRD Document<br/>Add Decisions & Context]
    C --> D[Commit Changes]
    D --> E[PRD v0.2]
    E --> F[Push to Branch]

    style E fill:#e1f5ff
    style B fill:#ffe1e1

Critical: A human (you) reviews and curates the AI output. AI is a research assistant, not the decision-maker.

Git commit message example:

Update PRD with kickoff meeting insights

- Added user pain points from support team
- Documented technical constraints from engineering
- Captured design considerations
- Added open questions for resolution

Based on 2025-11-18 kickoff meeting transcript.

Step 6: Pull Request Reviews and Iteration

Now the document lives in a PR where team members can comment, suggest changes, and build consensus.

graph TB
    A[Create Pull Request<br/>PRD v0.2] --> B[Notify Team]
    B --> C[Team Reviews Document]
    C --> D[Inline Comments<br/>on Specific Sections]
    D --> E[Suggestion Commits]
    E --> F{Changes<br/>Needed?}
    F -->|Yes| G[Update Document]
    G --> C
    F -->|No| H[PR Approved]

    style D fill:#e1ffe1
    style H fill:#d4edff

Why PR reviews are powerful:

Line-by-line feedback: Comment on specific requirements
Version control: See exactly what changed and why
Threaded discussions: Conversations stay attached to context
Approval workflow: Clear sign-off from stakeholders
Async collaboration: Not everyone needs to be in the same meeting

For non-technical reviewers: GitHub’s web interface makes this accessible. They can click “Add a comment” on any line, suggest text changes, or add general comments. No command line required.

Step 7: AI Prototype Creation

With aligned requirements, create a low-fidelity prototype to validate the direction.

graph LR
    A[Approved PRD v0.2] --> B[AI Generates Prototype<br/>Figma, HTML, or Sketch]
    B --> C[Low-Fidelity Mock<br/>Focus on Flow]
    C --> D[Review Internally]
    D --> E[Share with<br/>Stakeholders]

    style B fill:#fff4e1
    style C fill:#ffe1e1

AI tools for prototyping:

Claude or GPT-4: Generate HTML/CSS prototypes from requirements
Midjourney/DALL-E: Create UI mockups from descriptions
v0.dev or similar: Turn text into interactive components

Important: This is internal, low-fidelity, and focused on validating direction, not shipping quality. The goal is buy-in, not beauty.

Step 8: Iterate to Consensus

Share the prototype, gather feedback, and iterate until the team aligns.

graph TB
    A[Share Prototype] --> B[Collect Feedback<br/>via PR Comments]
    B --> C[Update Requirements<br/>Based on Feedback]
    C --> D[Revise Prototype<br/>if Needed]
    D --> E{Team<br/>Consensus?}
    E -->|No| B
    E -->|Yes| F[Lock Requirements<br/>PRD v1.0]

    style E fill:#fff4e1
    style F fill:#e1ffe1

Consensus doesn’t mean unanimous love. It means:

Key stakeholders are aligned
Major objections are addressed
Everyone understands the trade-offs
The team commits to the direction

Step 9: Handoff to Engineering

With consensus reached, merge the PR and hand off to engineering for real implementation.

graph LR
    A[PRD v1.0 Approved] --> B[Merge PR to Main]
    B --> C[Engineering Breakdown]
    C --> D[Technical Design Doc]
    D --> E[Implementation Begins]
    E --> F[Reference PRD<br/>Throughout Build]

    style B fill:#e1ffe1
    style D fill:#d4edff

Why this handoff works:

Requirements are documented and version-controlled
All stakeholder input is captured in the PR history
Engineers can see the “why” behind decisions
If questions arise, the context is preserved

Pros, Cons, and Mitigations

Pros

1. Version control for requirements

See exactly what changed, when, and why
Roll back to previous versions if needed
Track decision evolution over time

2. Democratized collaboration

Non-technical team members can contribute via meetings
AI translates conversation into documentation
PR comments are accessible through web interface

3. Single source of truth

No more “which Google Doc is the latest?”
Requirements live next to code
Context is preserved forever

4. Async-first but meeting-aware

Capture meeting insights without forcing everyone to meetings
Distributed teams can participate in their timezone
Recording ensures nothing is lost

5. AI as the bridge

Transcription removes documentation burden
Knowledge extraction surfaces insights humans miss
Prototyping validates direction quickly

Cons and Mitigations

Con #1: Git learning curve for non-technical users

Mitigation:

Non-technical users don’t need to learn git commands
They contribute via meetings (recorded and transcribed)
PR reviews happen in GitHub web interface (point and click)
Export PRD to PDF for those who prefer familiar formats

Con #2: Meeting fatigue

Mitigation:

Limit to 1-2 focused meetings per initiative
Keep meetings to 60-90 minutes maximum
Use recordings so not everyone needs to attend live
Make meetings optional for those who prefer to review async

Con #3: AI transcription isn’t perfect

Mitigation:

Always have a human review AI output
Use high-quality audio recording
Consider hybrid: record + human note-taker
Treat AI as research assistant, not truth source

Con #4: PR review process can be slow

Mitigation:

Set clear review SLAs (e.g., 48-hour response time)
Use “required reviewers” for critical stakeholders
Escalate blockers in standup or Slack
Consider “implicit approval” after timeout

Con #5: Initial setup overhead

Mitigation:

Create templates for kickoff docs
Document the workflow once, reuse forever
Build AI prompts that can be copy-pasted
Front-load effort pays dividends over time

Why This Matters

Traditional product requirements live in documents that:

Get duplicated endlessly (“PRD v4 final FINAL v2.docx”)
Lose context when stakeholders leave
Become outdated the moment they’re written
Exist separately from the code they describe

This workflow treats requirements like code:

Version-controlled and auditable
Collaborative with clear ownership
Living documents that evolve with the product
Integrated into your existing development workflow

The key insight: AI doesn’t replace humans in this workflow—it amplifies collaboration by removing grunt work. Non-technical stakeholders contribute their expertise through conversation. AI handles transcription and knowledge extraction. Product owners curate and structure. Engineers reference requirements alongside code.

Everyone plays to their strengths.

Getting Started

To implement this workflow in your team:

Start small: Pick one small feature to experiment with
Create a template: Build a kickoff doc template with standard sections
Test AI tools: Try Whisper for transcription, Claude/GPT-4 for knowledge extraction
Document the process: Write your team’s version of this workflow
Iterate based on feedback: This isn’t prescriptive—adapt to your team’s needs

The goal isn’t perfection. It’s reducing friction and preserving context.

Conclusion

Product requirements don’t have to live in document chaos. By bringing requirements into git, leveraging AI to bridge the technical gap, and using PRs for collaboration, teams can build a workflow that’s:

Accessible: Non-technical contributors participate through meetings
Durable: Requirements are version-controlled and searchable
Collaborative: PRs enable line-by-line feedback and threaded discussion
AI-enhanced: Transcription and extraction remove documentation burden
Integrated: Requirements live next to the code they describe

The future of product collaboration isn’t everyone learning git commands. It’s using git’s powerful collaboration model while meeting team members where they are.

Your code is already in git. Maybe your requirements should be too.

Want to see this workflow in action? This blog post itself was created through a git-based workflow where I described the idea, Claude drafted the content, and we iterated through commits. Meta, but it works.

The Complete Workflow

Step 1: Prepare the Kickoff Document (PRD v0.1)

Step 2: Share with a Diverse Team Upfront

Step 3: Conduct and Record the Kickoff Meeting

Step 4: AI-Powered Transcription and Knowledge Extraction

Step 5: Create PRD v0.2

Step 6: Pull Request Reviews and Iteration

Step 7: AI Prototype Creation

Step 8: Iterate to Consensus

Step 9: Handoff to Engineering

Pros, Cons, and Mitigations

Pros

Cons and Mitigations

Why This Matters

Getting Started

Conclusion