Built a simple skill that will use the brand guidelines I provide and suggest a daily post related to the topic of my choosing along with an image generated via kie.ai following the brand voice. Suggests 3 ways of writing, and after my preferential choice is made, runs it through the Humanizer skill.

Day 1 Build: From Zero Claude Code Experience to My First AI Newsletter Automation! 🚀 Well, I may have gotten a little carried away with this assignment! 😂 I started with VS Code, Claude Code, and the WAT framework. My goal was to build a newsletter automation similar to the demo. What I ended up building was a multi-brand newsletter system that researches topics, verifies claims, writes content, creates branded infographics, formats everything into HTML, and prepares newsletters for email delivery and archiving. I even tested it with two completely different brands, including my newly created Rainie Season Studios brand and its first newsletter, The Next Edit. 💡 What clicked for me: The difference between the agent, workflows, and tools. Once I understood how Claude could handle the reasoning while Python handled repeatable tasks, the whole WAT framework started making sense. I also learned something unexpected: not every graphic needs an AI image generator! Claude Code created two beautiful, editable infographics using code, with precise text and branding. No image-generation credits needed. 🔧 What I'd improve: I want to simplify the workflow so creating the next newsletter takes one instruction instead of a long conversation. I'd also like to turn the design into my first reusable Claude Code Skill, then eventually explore scheduled deployment. This was definitely more than I expected to tackle on Day 1 and it. bleed into a 2 day day endeavor, but seeing my own branded newsletter come together made it worth it. My biggest takeaway? You don't have to know how to code to start building useful automations. You do have to know what you want, ask good questions, test the results, and be willing to iterate. Sharing a screenshot of The Next Edit below! #ClaudeCode #AIAutomation #WATFramework #BuildInPublic

I created a generic newsletter because I don't have my actual business set up yet and I don't know what i would do a newsletter for. But here is a generic template I created -- I figure once I have the setup I can reuse over and over ....Right??

Hey builders, A lot of us build automations for clients who run WordPress/WooCommerce. Managing content, updating Elementor templates, or tweaking ACF fields across 10+ client sites has always been repetitive. To solve this, I spent the last few months developing a full WordPress MCP connector that links Claude Code, Cursor, and ChatGPT straight into WordPress via MCP (has around 145+ built-in actions). It’s completely free and open source (bilalnaseer/wsp-wordpress-mcp on GitHub). I want to put this in front of as many WordPress builders as possible, but open-source distribution is new to me. If your goal was strictly to get developer eyes, GitHub stars, and community feedback: - Where would you post/distribute this first? - What specific WordPress pain points (e.g. bulk WooCommerce edits, Elementor layout tweaks) should I highlight in short demo clips to get developers to star the repo? Appreciate any guidance from folks who have launched dev tools here!

🚨 ROBOTS ARE LEARNING ON THEIR OWN - AND YOU CAN TEST IT WITHOUT EVEN OWNING A ROBOT! Imagine taking a picture of your desk and having AI turn it into a 3D environment, place a robotic arm inside it, and let it practice movements until it learns how to complete a task. This is already happening! We created Real2Sim, an open project inspired by the robotics technology Google introduced with Gemini 4 Argon. The process is incredible: a photo becomes a physics simulation, the robot performs dozens of attempts, generates training data, and tests its movements before entering the real world. In our experiments, we achieved 50 successful movements in just 8.7 seconds, with a plan passing 19 out of 20 tests. We also compared four AI models. Gemini 4 Argon achieved 20 out of 20 successful attempts in one configuration, costing only $0.01 for that run. And here's the best part: You can experiment with all of this on your computer, using open tools, without buying a robot! This doesn't mean the physical robot has learned everything on its own yet. That's the next stage of the project. The real revolution is that we're beginning to replace hours of manual training with experiences generated and tested in simulation. 👉 Explore the project, see the results, and learn how to try it yourself: https://inematds.github.io/robotica-real2sim/guia/en/ The future of robotics doesn't begin when a robot moves. It begins when it learns before making its first move.