Something I've encountered pretty frequently is the question of how to use AI in an authentic manner. How do we use AI in a manner that preserves our critical thinking skills for future students, for the young ones growing up in this age? The biggest thing I've come across is using my voice. I'm using my voice right now with Wispr Flow to communicate this. Communicating and co-building with AI in a manner where we're both learning, and I'm using my voice, is the highest form of learning. Teaching is the highest form of learning. If you refer back to the learning pyramid, 5 to 10% of information from reading and listening gets retained, but when you discuss, apply, and teach topics, you retain 50 to 75% of the information. So having our students, people using AI, people we're training, companies we're training, use their voice to co-build with it so they don't lose their critical thinking is the most important thing. It's simple, but it's so effective. How are you using AI in a way that feels authentic to you?

I was setting up a website fully inside Cloudflare. Strict constraints. No third party tools. No external services. Clean stack. Minimal surface area. Reliability first. I had everything structured clearly. Skills defined. Phased build plan. Tight instructions. What I noticed was interesting. Even with explicit constraints, Claude kept suggesting external services as “easy” or “free” solutions. Things like adding a mail service or hooking in another tool to solve a small gap. Technically correct. But strategically wrong for this build. I had to shut it down multiple times and restate the boundary: We are not adding third party services. Everything stays inside Cloudflare. No new accounts. No new APIs. No new failure points. The drift wasn’t malicious. It was trying to be helpful. It saw a solution and offered it. But that solution multiplied complexity and risk. That reinforced something for me: AI will optimize for solving the problem. It will not automatically optimize for architectural restraint. If you are not explicit and persistent, the stack will sprawl. This is where human-in-the-loop really matters. Especially when you care about: • Risk mitigation • Maintenance overhead • Control of dependencies • Long term reliability The model can solve the issue. But it won’t necessarily solve it in the way you would architect it. So my takeaway: When building with strict constraints, watch for drift. Even with strong prompts and structured phases, it will try to “improve” the system unless you enforce the boundary. Progress overall is solid. Just an interesting observation about agentic behavior in real-world builds.

Hello everyone! I’m excited to join this business group and connect with like-minded entrepreneurs and professionals. Looking forward to learning, sharing ideas, and contributing value where I can. Wishing everyone growth, clarity, and big wins ahead 🚀

I recently pulled a quad muscle playing pickleball. Yeah, I know — everyone says it’s the sport most older folks get injured playing. Nonetheless, after pulling the muscle, I wanted to make sure I was doing everything I could to heal quickly and get back on the courts. So I used “Dr. Chat.” It did not disappoint. It told me what to do, how long to wait before getting back at it, and what to watch for once I was back out there — in case I needed to pull back. I certainly am not advocating against going to a doctor, but AI not only offers advice; as I’m learning, it also knows the pertinent questions to ask and can quickly come up with informed, practical guidance. I love it!

Anthropic just released Claude Opus 4.6 today, and I'm already running it. Here's what you need to know: What's New: 1M Token Context Window — First Opus model to handle this scale. That's 1,500 pages of text or 30,000 lines of code in a single session. A 5x jump from Opus 4.5. Agent Teams — Multiple AI agents now work in parallel on different parts of your task, coordinating together instead of working sequentially. Think of it as having a skilled team rather than a single assistant. Claude in PowerPoint — Direct integration (research preview). Create and edit slides without leaving the app. Cybersecurity Breakthrough — In testing, Opus 4.6 found 500+ zero-day vulnerabilities in open-source code using standard tools. No special instructions needed. Why This Matters for Business Anthropic's Scott White describes this as the shift to "vibe working" — where you describe what you want and the AI handles the execution end-to-end. For knowledge workers, analysts, and developers, this means: → Financial analyses that took days, done in minutes→ Agentic coding sessions that run 20-30 minutes autonomously→ Documents, spreadsheets, and presentations closer to production-ready on first attempt Rakuten already deployed it to autonomously manage tasks for a 50-person organization — closing 13 issues in a single day. The AI race continues. No single model dominates everything anymore — it's about choosing the right tool for the job. What's your first use case going to be?