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Course Launch Checklist

Complete guide to launching qwed-learning to the world.

✅ Pre-Launch (Before Announcement)

Repository Polish

  • All modules completed and tested
  • README.md has clear value prop
  • CONTRIBUTING.md guides community
  • LICENSE is correct (CC0-1.0)
  • All links work (test locally)
  • Code examples run without errors
  • Typography and formatting consistent

GitHub Settings

  • Enable GitHub Discussions
    • Go to Settings → Features → Discussions
    • Create categories: General, Module 1, Module 2, Module 3, Module 4, Show Your Projects
  • Add topics/tags: ai, llm, verification, course, neurosymbolic
  • Set description: "Free course on AI verification - Stop LLM hallucinations"
  • Add website: https://github.com/QWED-AI/qwed-learning

Content Final Check

  • Module 0 complete (for beginners)
  • Modules 1-4 complete
  • Examples work (healthcare, ecommerce, financial)
  • Notebooks open correctly
  • Capstone project structure ready
  • Positioning guides clear

🚀 Launch Day (Coordinated Announcement)

Morning (9-10 AM)

Twitter Thread:

  • Post main thread using template
  • Pin to profile
  • Tag relevant accounts (@OpenAI, @AnthropicAI if appropriate)

Afternoon (2-3 PM)

LinkedIn:

  • Post long-form announcement
  • Share in relevant groups (optional)

GitHub:

  • Star your own repo (to seed stars)
  • Post in GitHub Discussions Welcome thread

Evening (6-7 PM)

Reddit:

  • r/MachineLearning (check subreddit rules first)
  • r/learnmachinelearning
  • r/artificial (if allowed)

Hacker News:

  • Submit as "Show HN"
  • Keep title concise: "Show HN: Free course on AI verification"

Next Day

Dev.to:

  • Publish full article
  • Cross-post to Medium (optional)

📊 Post-Launch (First Week)

Community Engagement

  • Respond to ALL GitHub issues within 24h
  • Answer discussions promptly
  • Thank people for stars/contributions
  • Share student projects

Monitoring

  • Track GitHub stars daily
  • Monitor discussions for common questions
  • Check social media mentions
  • Respond to technical questions

Content Updates

  • Fix any bugs/typos reported
  • Add FAQ if questions repeat
  • Update README based on feedback

🎯 Growth Strategy (Ongoing)

Week 1-2

  • Daily engagement on GitHub Discussions
  • Share 1-2 tweets from course content
  • Respond to all mentions

Week 3-4

  • Feature student projects (if any)
  • Write follow-up blog post
  • Consider guest posts on popular blogs

Month 2+

  • Add community contributions
  • Create "Success Stories" section
  • Plan course improvements based on feedback

📈 Success Metrics

Track these weekly:

GitHub:

  • Stars: Goal 100 (week 1), 500 (month 1), 1000 (month 3)
  • Forks: ~10% of stars
  • Discussions: 5+ per week
  • Issues: Aim for <48h resolution

Social:

  • Twitter impressions
  • LinkedIn engagement rate
  • Reddit upvotes
  • Dev.to views

Course Completion:

  • Capstone projects submitted
  • Student feedback
  • Portfolio additions

🐛 Common Issues & Solutions

"Code doesn't run"

  • Check Python version requirements
  • Verify API keys are set
  • Test examples yourself before launch

"Too advanced for me"

  • Point to Module 0 (Prerequisites)
  • Suggest starting slower
  • Offer to help in discussions

"Need video tutorials"

  • Acknowledge request
  • Add to roadmap
  • Focus on written content quality first

"Certification?"

  • Explain it's self-paced
  • Portfolio project is the "certificate"
  • Consider quiz system later

🔄 Continuous Improvement

Monthly Review

  • Check analytics
  • Read all feedback
  • Plan next improvements
  • Update roadmap

Quarterly Goals

  • Add requested features
  • Improve weak modules
  • Expand examples
  • Consider translations

🤝 Community Building

GitHub Discussions Structure

Categories:

  1. 💬 General - Course feedback, general questions
  2. 📚 Module Discussions
    • Module 0: Prerequisites
    • Module 1: The Crisis
    • Module 2: Theory
    • Module 3: Hands-On
    • Module 4: Advanced
  3. 🏗️ Show Your Projects - Student implementations
  4. 🐛 Help Needed - Debugging assistance
  5. 💡 Ideas - Course improvement suggestions

Seeding Discussions

Post these to start conversations:

  1. "What brought you to this course?"
  2. "Share your first verification success!"
  3. "Which mental model resonates most? (Artist vs Accountant, etc.)"
  4. "Capstone project progress thread"

📧 Email Templates (If Building List)

Welcome Email

Subject: Welcome to AI Verification! 🎓

Thanks for your interest in the qwed-learning course!

Here's where to start:
→ Module 0 if you're new to LLMs
→ Module 1 if you know the basics

Join the community:
→ GitHub Discussions
→ Twitter: @rahuldass29

Questions? Just reply!

- Team QWED

Week 1 Follow-up

Subject: How's the course going?

Hey!

Have you started the AI Verification course?

Quick wins:
✅ Module 1: See the $12,889 bug
✅ Module 3: Build your first verifier
✅ Capstone: Portfolio project

Stuck? Ask in GitHub Discussions!

- Team QWED

🎉 Milestone Celebrations

100 Stars:

  • Thankyou tweet
  • Update README with badge

500 Stars:

  • Blog post: "What we learned from 500 students"
  • Feature top contributors

1000 Stars:

  • Major announcement
  • Plan course v2.0
  • Consider swag for top contributors

Final Go/No-Go Checklist

Before hitting "Publish":

  • All modules readable and error-free
  • Examples tested and working
  • README compelling and clear
  • No broken links
  • Social posts drafted
  • GitHub Discussions enabled
  • You're ready to engage with community
  • Week 1 time blocked for support

If all checked: LAUNCH! 🚀

Remember: Course quality > Launch hype. Better to delay and ship excellent than rush and ship mediocre.

You've got this! 💪