AI Prompt Library

Build me a daily briefing system. Every morning at 7am, I want a single consolidated
message that includes:

1. Today's calendar — not just "meeting with Greg at 2pm" but full context: who Greg is,
   what company he's with, what we discussed last time, and any relevant history. Pull
   attendee info from my email history and contacts.

2. Yesterday's key metrics — if I have content on YouTube, Instagram, or X/Twitter, show
   views, engagement, and any outliers worth noting.

3. Pending action items — what's overdue, what's due today, and what I'm still waiting on
   from other people. Cross-reference email threads related to today's meetings.

4. Optional background research on important meeting participants — if I have a big meeting,
   give me a quick brief on who I'm meeting with.

Deliver it as a single message. Keep urgent emails, CRM notifications, and follow-ups in
their own separate sections so nothing gets buried. The tone should be concise and
scannable — I want to read this in under 2 minutes.

Build an urgent email detection system that scans my inbox for important emails every
30 minutes during waking hours.

Use AI classification to determine urgency based on: sender importance, time-sensitivity
of the content, whether a response is expected, and whether money or deadlines are involved.

Include a feedback learning loop: when I tell you an email was or wasn't actually urgent,
adjust your classification over time. Learn my patterns.

Time-gate alerts so I only get notified during reasonable hours — weekdays 5-9pm, weekends
7am-9pm. No middle-of-the-night pings for non-emergencies.

Pre-filter known noise: marketing emails, newsletters, automated notifications, and
promotional senders should never even be classified.

For each urgent email, give me: who it's from, a one-line summary of what they need,
and why it's urgent. Deliver alerts to a dedicated channel (Telegram topic, Slack channel,
or text message — whatever I have set up).

You are a writing humanizer. Your job is to take AI-generated text and strip every
detectable AI pattern from it so it reads like a real human wrote it.

Specifically remove or rework:
- Stock phrases: "it's worth noting," "at the end of the day," "in today's landscape,"
  "dive into," "navigate," "leverage," "streamline," "holistic"
- Performed authenticity: "I'll be honest," "Let me be real," "Here's the thing"
- The Rule of Three: AI loves listing exactly three things. Vary it — sometimes two,
  sometimes four, sometimes one strong point
- Excessive em dashes — AI overuses them as a crutch for sentence variety
- Hedging stacks: "It's important to consider that perhaps one might want to..."
  Just say the thing
- Formulaic structure: [Hook] → [Context] → [Three points] → [Inspiring conclusion]
  is the AI writing skeleton. Break it
- Overly smooth transitions: "Moreover," "Furthermore," "Additionally" in sequence
- False balance: AI always presents "on the other hand" even when one side is clearly right

Preserve the original meaning, facts, and intent. The goal is not to dumb it down — it's
to make it sound like a specific human with opinions wrote it, not a language model trying
to sound helpful.

When I paste text, return the humanized version. No commentary unless I ask for it.

Build a food and symptom tracking journal. I want to log what I eat and how I feel,
then have you analyze patterns over time.

Four entry types:
- Food: what I ate, approximate time, and any notes (e.g., "large portion," "homemade")
- Drink: what I drank, including water, coffee, alcohol
- Symptom: what I'm feeling + severity on a 1-5 scale (1 = barely noticeable, 5 = severe).
  Examples: bloating, headache, fatigue, brain fog, joint pain, heartburn
- Note: anything else relevant — sleep quality, stress level, exercise, medication changes

Send me 3x daily reminders at 8am, 1pm, and 7pm to log meals and how I'm feeling.

Store everything organized by date. Once I have 2+ weeks of data, start running weekly
analysis:
- Correlate specific foods with symptoms (e.g., "dairy appears within 4 hours of your
  bloating episodes 70% of the time")
- Track symptom frequency and severity trends
- Flag any new patterns or notable changes
- Suggest potential trigger foods to test eliminating

Keep the logging friction as low as possible — I should be able to type "lunch: turkey
sandwich, apple, water" and have you parse it correctly without a rigid format.

Create a practical prompt engineering guide based on the latest model behaviors
(Claude 4.x / GPT-5.x / Gemini 3.x era). Focus on discoveries that contradict
older prompting advice. Specifically cover:

1. Why ALL-CAPS urgency markers (CRITICAL, MUST, NEVER, ALWAYS) now cause
   overtriggering in newer models. They were useful in GPT-3 days but modern
   models are too compliant — caps makes them overly rigid and paranoid.

2. Why explaining the REASON behind a rule works better than just stating the rule.
   "Don't include personal opinions because this is a factual report" beats
   "NEVER include personal opinions." The model generalizes from explanations.

3. Why you should only show examples of desired behavior, never anti-patterns.
   Models sometimes fixate on the anti-pattern and start reproducing it. Show
   what good looks like, not what bad looks like.

4. Why "if in doubt, use this tool" instructions cause tools to trigger on
   nearly every message. Be specific about WHEN to use tools, not permissive.

5. Why prompt formatting should match your desired output formatting. If you
   want prose, write your prompt in prose. If you want structured data, structure
   your prompt.

6. The difference between system prompts, user prompts, and few-shot examples —
   and when each is most effective.

Write this as a practical reference I can come back to, not an academic paper.
Include before/after examples for each principle.

Create a system that processes meeting transcripts and extracts actionable outcomes.

When I give you a meeting transcript:

1. Match attendees to known contacts (I'll provide context or you can reference
   my CRM if connected)

2. Extract every action item with:
   - What needs to be done (clear, specific description)
   - Who owns it (me vs. someone else)
   - Deadline if mentioned, or "no deadline stated"
   - Priority: high (explicitly committed to), medium (agreed but informal),
     low (suggested but not committed)

3. Separate items into:
   - MY action items (things I need to do)
   - THEIR action items (things I'm waiting on from others — but exclude
     internal team members, only track external contacts)
   - DECISIONS MADE (important things agreed on, even if no action needed)

4. Send me an approval queue — show each extracted item and let me approve,
   reject, or edit before it becomes a real task

5. Run a completion check 3x daily (8am, 12pm, 4pm) showing:
   - What's overdue
   - What's pending for today
   - What I'm waiting on from others

6. Auto-archive items older than 14 days that haven't been completed

Output format should be clean and scannable. No fluff.

You are a business advisory council made up of independent specialist perspectives.
When I describe my business situation or share data, analyze it from these 5 angles
IN PARALLEL — each perspective should reason independently without being influenced
by the others:

1. REVENUE GUARDIAN — Focuses purely on money. Where is revenue coming from? What's
   at risk? What's the fastest path to more revenue? Ruthlessly practical.

2. GROWTH STRATEGIST — Focuses on expansion opportunities. What's the next market,
   channel, or product? Where is momentum building that I could ride?

3. SKEPTICAL OPERATOR — The devil's advocate. What could go wrong? What am I
   ignoring? Where am I fooling myself? This voice should be constructively
   contrarian, not negative for its own sake.

4. CUSTOMER LENS — Focuses on the end user/customer experience. What do they
   actually want? Where is friction? What would make them tell a friend?

5. EFFICIENCY AUDITOR — Focuses on time and resource allocation. What should I
   stop doing? Where am I overcomplicating things? What's the 80/20?

After all 5 perspectives weigh in, provide a SYNTHESIS that:
- Eliminates duplicates across perspectives
- Ranks the top 3-5 recommendations by impact
- Numbers each recommendation so I can say "tell me more about #3"

When I give feedback (approve, reject, or modify recommendations), learn my
preferences over time so future analysis better matches my decision-making style.

My business context: [describe your business, current challenges, and what
data you have available]