Page: 'Product Weekly — May 4, 2026'\n\nAttendees: Sara (PM), Marcus (eng lead), Priya (design), Tom (marketing)\n\nUpdates:\n- Sara: Onboarding redesign shipped Tuesday. Activation rate +18% on first cohort.\n- Marcus: API rate-limit bug from last week is fixed in main. Hotfix going out tonight.\n- Priya: Mobile nav prototype ready for review. 
  Need feedback by Friday so we can hand off to eng.\n- Tom: Q2 launch campaign needs hero copy. Stuck on positioning — should we lead with 'fast' or 'reliable'?\n\nDecisions:\n- Pricing experiment: A/B test the $19/$29/$49 ladder vs current $15/$25/$45 starting May 11. Sara to wire up GrowthBook flag.\n- Mobile rollout: gated behind feature flag, 5% rollout    
  next Monday, full rollout May 18 if metrics hold.\n\nAction items:\n- Sara: ship pricing flag by EOW.\n- Marcus: write postmortem for the rate-limit bug — due Wed May 7.\n- Priya: schedule mobile prototype review for Thursday.\n- Tom: draft 3 positioning options, share by Friday for team vote.\n\nOpen:\n- Do we hire a second backend engineer this quarter or  wait for Q3? CFO wants headcount frozen, but we're at 80% capacity. Tabled to next week.\n- Should the pricing experiment include an annual discount tier? Sara to ask David.

Summary  
This chapter covers using structured AI prompts to transform raw meeting notes into actionable outputs—specifically a TLDR, a list of action items with owners and deadlines, and open questions.  

General domain of usage  
Meeting notes summarization and action-item tracking.

Useful AI at work isn't about searching the internet – it's about working on **your stuff**. Your meeting notes, your specs, your brief. That's what a tool like `notion_page` unlocks.



## The Shift

A search tool fetches the world. A page-reader tool fetches **your context**:

| Tool | Question It Answers |
|---|---|
| `web_search` | What's true **out there**? |
| `notion_page` | What did **we** decide last Tuesday? |



## What This Lab Does

Claude reads a page of meeting notes and turns it into something usable: a **TLDR**, a list of **action items** with owners, and the **open questions** that still need a decision. That's the kind of post-meeting writeup a chief of staff would charge for – Claude produces it in seconds, but only if the system prompt tells it exactly what shape to deliver.



## Why "Give Me a Summary" Isn't Enough

Take a page of meeting notes and ask any AI for **"a summary."** You'll get a paragraph – maybe useful, maybe not. Now ask for **"TLDR in 3 bullets, then action items with owner and deadline, then open questions"** and you'll get something you can **act on**.

**When a tool feeds Claude raw content, the system prompt is what turns content into action.**



## Task
Send this prompt:

><b>Read my Product Weekly notes from May 4 and give me a TLDR, action items with owners and deadlines, and the open questions.

Then push it with follow-ups – the notes are already loaded, so Claude doesn't re-fetch:

><b>Just show me what Sara owns this week.

><b>What decisions are blocked on someone outside the team?

><b>Which action items have no deadline?



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