Hello everyone and happy Tuesday. I have been away from this community a few days catching up while working through everything we learned during the AI Advantage Summit, especially the insights from Sabrina and the other speakers. Today I had a truly transformative moment using ChatGPT, and I wanted to share it, because it’s probably going to save me at least 40 hours of work! I have a long standing personal interest in understanding how women around the world experience emerging technologies like AI, blockchain, quantum, and digital infrastructure. While sketching out some ideas for my own learning, I ran into a big problem. I needed to compare global religious and cultural calendars worldwide so I did not overlook important observances in different regions and countries. In the past this would have taken me at least a week of research by manually going through the different religious and cultural calendars. Instead I asked ChatGPT to scan major world religious calendars and cultural observances in every country around the world, to locate dates with the least overlap. Watching it process that global information in real time felt incredible. It just saved me DAYS of work. The summit encouraged all of us to experiment, think bigger, and try new tools, so I wanted to pass this moment along!! Did you have a similar moment since last weekend to discover a powerful or time saving use of AI? I hope you’re all doing well and especially for the people participating in the boot camp. I hope you’re learning lots of amazing things!

This season isn’t just about sales. it’s about data. What you do now tells you what will work next year. Which products convert, which creatives pull attention, what objections buyers have, and where people drop off. Brands that win long-term don’t disappear after peak season. They use this period to refine, document, and prepare. You don’t need to go all-in — but you shouldn’t go silent either. Finish the year strong, so next year starts with clarity instead of guesswork. Are you interested in getting things like this. You can drop a comment, let's discuss better.

Last posts I shared: - Guardrails 101 (copy/paste checklist), and - AI Safety for Non-Tech Builders (driver’s-ed framing) Those sparked good questions — “Okay, but how do I actually think about risk like this?” And in the comments, @Nicholas Vidal pushed the conversation into real, operational safety — ownership, kill-switch, reality checks — and @Kevin Farrugia added the “nightmare in one sentence” idea people really resonated with. So I turned that into something you can actually run: A 20-minute “nightmare scenario drill” for any AI feature — even if you’re not technical. Before you start: 4 Guardian Questions If you remember nothing else, remember these: 1. What’s the worst-case? 2. Who moves first? 3. How do they stop it fast? 4. How do we prevent the repeat? Everything below is just a structured way to answer those. ———————— Quick definitions (so non-tech people stay with us): - Threat model = simple version of → “What could go wrong, and who could get hurt?” - Kill switch = → “How do we pause/disable this fast if it misbehaves?” - Audit log = → “A record of what happened, so we can see when/where it went wrong.” ———————— You don’t need to be a security engineer to use these. You just need the right questions. Step 1 — One-sentence nightmare ✅ (Kevin’s point) Write this: “If this goes wrong, the worst thing that could happen is…” Examples: - “Our AI chatbot leaks customer data in a reply.” - “Our content tool generates harmful content with our brand on it.” - “Our automation sends 500 wrong emails before anyone notices.” If you can’t write this sentence, you’re not ready to ship. ———————— Step 2 — Owner + alert ✅ (Nick & Kevin) Now add: - Owner: “If this nightmare starts, who is responsible for acting?”(name + role, one person) - Alert: “How do they find out?”(email, Slack, SMS…) If everyone owns safety, no one owns safety.

(Updated) I thought this might be useful because a lot of people want to “build with AI” but don’t have a security background — and safety talk often turns into either fear… or vague theory. This is neither. This is a simple, repeatable checklist you can copy into your project and run every time (like a pre-flight check). If you can follow a recipe, you can follow this. When to run it Run this checklist: - Before you launch - After any new feature - After any security news/alert - Once per month as a quick maintenance habit 🔒 Guardrails 101 (Copy/Paste Template) Project name: Owner (who is accountable): Where it’s hosted (platform): Last checked (date): 1) What are we building? (1–2 lines) - AI feature(s): - What users can do with it: 2) Data & privacy (what touches what) - What data is used? (none / basic / personal / sensitive) - Where is it stored? - Who can access it? Rule: If personal data is involved → minimize it and document why it’s needed. 3) Secrets & access (high priority) - ✅ 2FA enabled on: email / GitHub / hosting / admin dashboards - ✅ API keys stored safely (not in chats, screenshots, or public repos) - ✅ Least access: only people who need it have it - ✅ “Rotate keys” plan exists (where/how) 4) Updates & patching (boring but essential) - Dependencies/framework updated: ✅ / ❌ (date) - Hosting/platform updates: ✅ / ❌ - If a critical alert happens: who patches within 24–48h? 5) Monitoring (can we see problems early?) - Logs enabled: ✅ / ❌ - Alerts enabled for suspicious activity / errors: ✅ / ❌ - Who receives alerts? 6) Abuse & misuse (what could go wrong?) Quick answers: - Most likely misuse case: - Nightmare scenario (1 sentence): “If this goes wrong, the worst thing is…” - How we reduce it (rate limits / permissions / filters): - What we will NOT allow the AI to do: 7) Kill-switch & rollback (must-have) - Can we disable the AI feature quickly? ✅ / ❌ - Where is the “off switch”? - How do we roll back changes?