One of the most practical AI systems I use every single day has nothing to do with coding, agents, or automation workflows. It’s my personal nutrition and activity tracker and daily dashboard. I log the food. I log the activity. ChatGPT does the rest. Every day: I log food, activity, bodyweight, and water as it is happening. ChatGPT estimates activity burn, subtracts it from my food intake, and then factors in my BMR to show whether the day is trending toward maintenance, fat loss, or an aggressive calorie deficit. Then, at the end of the day, it turns the raw inputs into a dashboard showing calories, macros, activity burn, net calories, net + BMR, protein density, protein per pound, fiber tier, fat-source patterns, etc. Because I follow a higher-protein diet, I also created a metric I call Protein Density: Protein grams ÷ total calories consumed (by snack, meal, day). The metric is useful because I can monitor food quality as I eat throughout the day, not just total calories. A good Protein Density score is: 0.10 or higher That generally means the day is optimized for muscle preservation and fat-loss efficiency. A lower score around: 0.05 That usually signals a less efficient nutrition day where calories are climbing faster than protein intake. For example: Chicken Breast (100g cooked, skinless): - ~165 calories - ~31g protein 31 ÷ 165 = 0.19 Protein Density Compare that to potato chips: Potato Chips (100g): - ~536 calories - ~7g protein 7 ÷ 536 = 0.01 Protein Density Both are food. But one is highly protein-efficient, while the other is primarily calorie-dense with minimal protein value. That simple ratio gives me immediate feedback on whether my meals are supporting my goals before the day is even over. The key for me is context. A 1,600-calorie day means one thing if I barely moved. It means something very different after 16,000 steps, hills, heat, and a high-output activity day. That is where AI becomes useful. Not just tracking data.

I had this discussion many times in my community: Claude, ChatGPT, and all the AIs are never able to properly determine days of the week and proper dates. I have the solution now, and it's the same one as for calculations. It needs to use code, so here goes the sentence to put in your global instruction for any AI that you're using or into your prompt if you need an AI to use a calendar or help you plan something. Here goes the sentence: "Always run code to compute or verify any date, day of the week, or time interval. Never answer date questions from memory." And the root cause is the same as for calculations. If the AI does not use code, it will just make a guess. That is why most of the time it gets it wrong.

Hello everyone — I wanted to share a quick video to walk through some recent changes we’ve made to the site. As the community has grown, it became clear that we needed a better way to organize content for members with different starting points. That’s where the four groups come in: - AI Curious - AI Enthusiast - Agency - Enterprise. In the video, I show how posts and classroom content are now organized by group so it’s easier to find what’s most relevant to you. That said, nothing here is meant to be restrictive. You’re encouraged to explore outside your group if you’re curious — sometimes that perspective is the most valuable part. This update is really about making the community easier to navigate as we approach 500 members, while keeping the spirit of open learning and shared experience intact. Thanks again for being here and for spending your time in this community. The questions, feedback, and quiet participation all matter more than you might realize. I genuinely appreciate every member of this community, and I’m glad we’re building this together. Respectfully. @Michael Wacht

Hey AI Bits & Pieces crew! I’m super excited to share a little milestone with you all. Recently, found out that I’m ranked in the top 5% of U.S. developers and top 10% of Global developers on Lovable.dev! Here’s what that looks like in numbers: - The sites I’ve developed there have pulled thousands of views. - Created over a dozen sites using a total of 426 prompts. - Altogether, the development work has generated over 199,000 lines of code. - This is the equivalent of 6,600 development hours if I did it the traditional way! I thought it’d be fun to share this with you all, not just to celebrate a milestone, but to show how these tools can really amplify what we do. Websites Developed: - Corporate Websites - Bakery Showcase - Custom Mustang Website - Anniversary Celebration - Opportunity Mapping Roadmap - Knowledge base connected to Pinecone and n8n - Document storage connected to Supabase - and more... Thanks for being part of the journey!