All prompts in this library work across ChatGPT, Claude, and Microsoft Copilot. Here are the practical differences to know.
Quick Comparison
| |
ChatGPT (GPT-4o) |
Claude (Anthropic) |
Microsoft Copilot |
| Best for |
Long-form synthesis, structured tables |
Nuanced coaching language, nuanced analysis |
M365 integration, Teams/SharePoint |
| Context window |
Large |
Very large |
Varies by plan |
| Tone quality |
Strong |
Excellent for coaching/facilitation |
Good |
| Integration |
API, browser, mobile |
API, browser, mobile |
Embedded in M365 |
| Table formatting |
Excellent |
Excellent |
Good |
| Hallucination risk |
Low with good prompts |
Low with good prompts |
Low with good prompts |
ChatGPT (GPT-4o)
Best use cases in this library:
- Long retro synthesis with many inputs
- Multi-sprint pattern analysis
- Generating multiple versions of Sprint Goals or PI Objectives
- Structured tables (dependencies, ROAM risks)
Tips:
- Use the system prompt feature (in Custom Instructions) to pre-set your Scrum context once
- GPT-4o handles large pastes of retro sticky notes very well
- Use “Code Interpreter / Data Analysis” mode if you’re working with metrics
Watch out for:
- Overconfident output — always review PI Objectives for accuracy before sharing
- Verbose responses — add
"Be concise" or "Use bullet points only" if needed
Claude (Anthropic)
Best use cases in this library:
- Retrospective facilitation prompts (nuanced, empathetic tone)
- Coaching language for action items and improvement areas
- Stakeholder narratives and sprint review summaries
- Complex dependency analysis
Tips:
- Claude handles ambiguous team context well — it will ask clarifying questions if something is unclear
- Excellent at varying tone across audiences (team vs. leadership vs. Business Owners)
- Great for follow-up conversations: paste Claude’s output back and ask for refinements
Watch out for:
- Responses can be longer than needed — specify your length requirement in the prompt
- May add caveats you don’t need for internal documents — prompt with
"Write this as a direct summary, no caveats"
Microsoft Copilot (M365)
Best use cases in this library:
- Sprint review and retro summaries directly into Confluence/Word/SharePoint
- Teams post drafts for stakeholder updates
- Meeting summaries from Teams recordings (Copilot in Teams)
- PI Objective tables in Word or PowerPoint
Tips:
- Use Copilot in Teams to auto-summarise PI Planning or retro meetings — then use the prompts here to structure that summary
- Copilot in Word: paste the prompt + context directly into Word, select it, and use Copilot to rewrite/expand
- Copilot Pages: useful for drafting living team documents from prompt outputs
Watch out for:
- Quality varies by M365 plan (Business vs. Enterprise)
- Works best when you already have the context in your M365 ecosystem (notes, emails, calendar)
- Provide more context than you think you need — AI models perform much better with specific inputs
- Iterate, don’t restart — follow-up prompts within the same conversation preserve context
- Ask for alternatives —
"Give me 3 different versions of this Sprint Goal"
- Check accuracy — AI can confidently produce plausible-but-wrong output, especially for team-specific details
- Use AI for drafts — let AI do the first 80%, then apply your Scrum Master judgment for the last 20%