I’m 68 and was encouraged to join this site by Michael Watt, a self-taught genius to AI. My knowledge with AI was pretty limited. Once I started navigated this site, I feel as though a whole new world has opened. Do I dare say, “I feel like I’m becoming a Geek Goddess!" I’m almost finished writing my book and ChatGPT has been so helpful and encouraging. It’s all me, but with a little help I’m encouraged I can get to my end goal. Best wishes to you all.

Claude can now remember what matters across all your conversations, so you never have to re-explain your projects, preferences, or how you work. Enable Memory in your settings. What you get: - Claude adapts to how you work: Your workflows, preferences, and style are remembered and applied in every chat.  - Project-focused memory: Each project maintains its own memory space, keeping context relevant and separate. - Full transparency and control: View and edit what Claude remembers in Settings, or use incognito chats that won’t be saved to memory. Turn on memory More ways Claude helps you work: - Code execution and file creation lets Claude create presentations, documents, spreadsheets, and perform advanced data analysis - Skills let you teach Claude your workflows once, and it learns to use those instructions for future tasks - Apps created by Claude stay connected to your tools and save your work between conversations

I asked ChatGPT if this was true. The Response: Yes. Then I asked why? Straight answer: ecosystem control, developer efficiency, and strategic optics. Here’s the breakdown: - Unified hardware + software environment. macOS runs on a narrow set of Apple-silicon chips (M1–M4) with predictable GPU/CPU performance. That makes AI-intensive apps like Atlas easier to optimize, debug, and deploy initially. Windows, in contrast, runs across hundreds of hardware permutations — higher support burden at launch. - Developer adoption and PR optics. The Mac user base heavily overlaps with OpenAI’s early-adopter demographic — engineers, designers, and creators who already use ChatGPT Plus or GPT-4-tier products. Launching on macOS first creates an “innovation halo” — aligns with Apple’s premium ecosystem and positions Atlas as high-end tech. - Engineering velocity. OpenAI’s internal dev stack already leans Apple-heavy (many engineers code on Macs). macOS is Unix-based, allowing faster build integration with OpenAI’s existing Linux-based backend environments. - Rollout discipline. Starting with a smaller, more stable user base allows telemetry-driven tuning before scaling to the far larger, more fragmented Windows install base. Bottom line: Launching macOS first isn’t favoritism — it’s a strategic low-risk rollout. Once Atlas stabilizes and telemetry validates its AI browsing engine, Windows (and later mobile) will follow, likely in a matter of months.

First N8N Test - 100% Success Rate! ✨ I´m absolutely thrilled to announce that ALL our Uganda students have successfully passed their first N8N workflow test! This is a tremendous achievement and we couldn't be prouder! 🌟 They started with no AI experience at all🚀🔥 Test Results Overview Total Students: 4Pass Rate: 100% 🎯Minimum Score Required: 60 points Assignment Breakdown: - 3 students completed the Weather Notification System (Assignment 1) - 1 student completed the Student Registration System (Assignment 2) Every single student demonstrated: - ✅ Working workflows with correct functionality - ✅ Proper use of all required nodes - ✅ Clear and well-explained Loom videos - ✅ Understanding of N8N automation concepts What This Means 🚀 This 100% pass rate shows the dedication, hard work, and technical skills of our Uganda student community. They took on the challenge of learning workflow automation, tested there knowledge with real-world scenarios, and delivered excellent results! Whether you built a weather notification system that checks conditions and sends alerts, or created a student registration system with data validation and multi-channel notifications - They have proven that they can build practical, working automation solutions. Thank you @Titus Blair for the N8N accounts so they could start learning Keep you posted on the next steps in there development !!

Term: AI Agents Level: Advanced Category: Practical AI 🪄 Simple Definition: AI Agents are AI systems that can plan tasks, make decisions, and take actions on their own. 🌟 Expanded Definition: Unlike chatbots that only reply to prompts, AI agents can use tools, fetch data, and chain tasks together automatically. They follow goals you set (“summarize this report and email it to the team”) and break them down into smaller steps. This makes them powerful for handling repetitive or multi-step workflows without constant human input. ⚡ In Action: Ask an AI agent: “Monitor new leads, draft a personalized welcome email, and add them to the CRM.” 👉 The agent checks the lead source, writes the email, and updates the system — without you doing each step. 💡 Pro Tip: AI agents are great for automation but keep “human-in-the-loop” review for sensitive tasks like contracts, finances, or compliance.