Welcome to the Out of The Box Series — where I test how far curiosity and AI can take you in 30, 60, or 90 minutes, using today's best no-code and low-code tools. No setup. No training. Just pure exploration — right out of the box. 🎬 This Episode: Default Image Creation — ChatGPT vs Gemini vs Claude 🕒 Time Limit: One prompt, default settings 📂 Category: AI Image Creation OpenAI just upgraded its image engine, and I wanted to see if it lives up to the buzz. So I ran a quick test: - Same prompt, three tools - Default settings No tweaks, no custom instructions — just hit go and see what comes back. A few surprises along the way: 🔹 ChatGPT: The image came back clean and easy to understand, with great use of whitespace. The upgrade was instantly noticeable. This is my new favorite image creation LLM. 🔹 Claude: Surprisingly, Claude still can't create images natively. But it offered to connect to Canva instead. I'm a Canva subscriber and a big fan, so that was an easy "hell yeah" from me. 🔹 Gemini: The one with the stellar reputation for image creation — is the one that missed. Notice the landscape image has two Claude panels. ✅ My verdict, two words each: 🔹 ChatGPT: Professional, Balanced 🔹 Gemini: Incorrect, Colorful 🔹 Claude (via Canva): Pedestrian, Underwhelming The results are below. 👀 You be the judge. What do you think? Prompt Used: Pasted content below into dialogue box, selected "Image Creation" mode, and hit enter. Content provided to each LLM: The chart breakdown ChatGPT — Best for: creative content, coding, everyday workflows Strengths: multimodal, custom GPTs, long-term context recall Pro tip: automate workflows, build custom GPTs for writing/planning/analysis Grok — Best for: real-time trends, pop culture, candid takes Strengths: connected to X/Twitter in real time, sharp/punchy tone Pro tip: use for viral posts and social commentary with personality Gemini — Best for: Google Workspace integration, real-time data Strengths: deep Docs/Sheets/Slides integration, real-time search

Join us on Zoom Saturday, July 11, 2026 12:30 ET - 13:30 ET we’re opening the AI for Life + AI Bits and Pieces session to everyone, including people outside the community. Join instructions https://us06web.zoom.us/meetings/81545596982/invitations?signature=NQBPitO7KYhO4f7NHMddMYVn476zmP8rjoEmkdhIvzY Meeting ID: 815 4559 6982 Passcode: 050131 Hosts: - 𝗠𝗶𝗰𝗵𝗮𝗲𝗹 𝗪𝗮𝗰𝗵𝘁 from 𝗔𝗜 𝗕𝗶𝘁𝘀 𝗮𝗻𝗱 𝗣𝗶𝗲𝗰𝗲𝘀 𝗰𝗼𝗺𝗺𝘂𝗻𝗶𝘁𝘆. - 𝗠𝗮𝘁𝘁𝗵𝗲𝘄 𝗦𝘂𝘁𝗵𝗲𝗿𝗹𝗮𝗻𝗱 from 𝗔𝗶 𝗳𝗼𝗿 𝗟𝗶𝗳𝗲 𝗰𝗼𝗺𝗺𝘂𝗻𝗶𝘁𝘆. This will be guided questions plus an open forum for practical discussion around what is happening in AI right now, including: - The explosion of AIOS aka Second Brain - AI hot topics and trends - Design and development - Workflows and automation - Process improvement - Tooling, use cases, and real-world implementation Join us for an open working conversation with people who have been building, testing, learning, and applying AI and automations in practical ways. 𝗦𝘂𝗯𝗺𝗶𝘁 𝗾𝘂𝗲𝘀𝘁𝗶𝗼𝗻𝘀 𝗽𝗿𝗶𝗼𝗿 𝘁𝗼 𝘁𝗵𝗲 𝗲𝘃𝗲𝗻𝘁 𝗳𝗼𝗿 𝗰𝗼𝗻𝘀𝗶𝗱𝗲𝗿𝗮𝘁𝗶𝗼𝗻. We’ll kick things off with pre-submitted questions. Simply submit your question(s) in the comments below, or direct message me in Skool. ✨ Claude will pick the question order. And of course bring questions, examples, workflows, problems, tools, or ideas you want to discuss during the open forum. Hope to see our friends there: @Ron Nedd @Frank Priboy @Gina Wang @Debbie Ai @Pedro Gomez @Usman Mohammed @Nick Mohler @Mike AI Consultant @Diane McCracken @R S @Collin Thomas @Jacob Brodsky @Bradley Kerman @Md. Abdullah Al Mafi @Michele Wacht @Mark Zayec @John Romano @Josh Frison

I'm building a lead system for a client or better i shall Input: keywords. Output: leads with company, email, phone, contact details and more ... My current idea: Apify pulling from Apollo, Google and other sources. But I'm sure someone here has already done this. Maybe some other ideas? Before I start from scratch: • Have you built something similar you'd share? • Know a solid GitHub repo for this? • What scraping tools actually work for you? • Or does anyone have a full system I could look at? Every pointer helps. Thanks

Most automation problems I see trace back to a fuzzy mental model of what an API actually is. So here's the frame I use with clients. An API is a remote control for software. Your app presses a button (sends a request). Another app does something and sends back a result (a response). You don't see how the other app works inside. You just follow the rules printed on the buttons (the docs). That's it. That's the whole concept. Two analogies that work in client calls: Restaurant menu. The menu lists what you can order and how to ask for it. Kitchen is hidden. Meal is the response. Light switch. Flip the switch (request). Wiring, grid, power plant are hidden. Light turns on (response). Same idea either way: clear inputs, clear outputs, hidden complexity. The actual call pattern: 1. Client asks (your app, browser, script) 2. Request goes out with a URL, a method (GET, POST, etc.), and any data the server needs 3. Server does the thing 4. Response comes back, usually JSON Break any of those rules and you get an error, not data. Why this matters for builders: - Reuse beats rebuild. Use Stripe's API instead of building payments from scratch. - Complexity stays hidden. You don't need to know how Twitter stores tweets to pull the last 20. - Access is controlled. APIs decide what's exposed, who can call it, and how often. Security still depends on the implementation, but the boundary exists by design. - Apps mix APIs like ingredients. Maps, payments, email, auth, all stitched together. When two pieces of software talk in a structured, agreed way, they're using an API. Every n8n node, every Claude Code tool call, every trigger. All APIs under the hood. What analogy do you use when a non-technical client asks what an API is? Curious what lands for other builders. Highly recommended related information: Check out @Michael Wacht's Daily Dose: https://www.skool.com/ai-automation-society-plus/ai-terms-daily-dose-api-use?p=5c08d0bf

We just crossed 600 members in AI Bits & Pieces. Consistent growth from day one, fueled by people trying to understand what AI actually means for their work and day-to-day life—and how it can help them stand out in the workforce, business environment, or executive ranks. That’s been the goal from the start. A place for: 🔵 AI Curious — figuring out what this all is 🟢 AI Enthusiasts — using it regularly 🟠 AI Practitioners — applying it to real work 🟣 Enterprise — thinking about scale across teams What’s been interesting isn’t just the number—it’s the mix of people and the conversations starting to take shape. Members are building small things. Members are asking in-depth questions. And members are starting to connect the dots between tools and outcomes. A special shoutout to each and every member, and the people who have supported me from the beginning: @Michele Wacht @Dena Dion @Debra Schmitt @Patti Hoekstra @Mark Zayec @Matthew Sutherland @Jason Hagen @Usman Mohammed @Nick Mohler @Eduard Friesen We have some exciting updates and new offerings for the community designed to help you win the AI game in life, at work, as a business owner, or as an agency. A heartfelt thank you. Michael