We’re planning upcoming live sessions and want to make sure it’s focused on what you want most. - What topic would you like us to cover? - Drop real use cases — we may build around them. 👉 We’ll run sessions on the top 2 choices first.

Welcome to the Out of the Box series — where I explore what can be built with no-code and low-code AI tools in 30 minutes or less. No manuals. No tutorials. Just curiosity and creation in motion. This time I revisited Sora 2 a few months later to see how the experience has evolved. App: Sora by OpenAI Time: Under 30 Minutes Category: AI Video Creation / Prompt-Directed Video Video Title: Move Over Rover, The Dog Days of Coding Are Over - Claude Code is The Cats Meow 🎥 What Is Sora? Sora is an AI video generation platform that transforms a simple text prompt into lifelike, cinematic scenes — complete with motion, lighting, and visual storytelling. Think of it as having a director, camera crew, and editor… all powered by a prompt. ⚙️ Experience 1 — The First Test A few months ago, I ran an Out of the Box experiment with Sora using a simple presenter-style scene. The results were impressive for early generative video, but the workflow still felt a bit like experimentation. The outputs were interesting, but not something that added much practical value beyond demonstrating what the technology could do. If you’re curious about that original test, you can see the full post here: 👉 https://www.skool.com/ai-bits-and-pieces/out-of-the-box-in-30-sora-2?p=e63f6633 That first experiment helped show what was possible, but the bigger question was how quickly the experience would evolve. ⚙️ Experience 2 — Revisiting It Today For the second experiment, I tried something completely different — a playful, high-motion scene designed to test character behavior and storytelling. Prompt theme: A cat driving a quad runner at high speed — Fast & Furious style — with a dog riding on the back howling and clearly terrified. The twist: - The cat is labeled “Claude Code.” - The dog is labeled “ChatGPT.” Experiment 2 Video: https://sora.chatgpt.com/p/s_69b4d4703dbc819180c914a61747c81f?psh=HXVzZXItQWI5dFRpa3JRS1RTSmhwbDY3VlFYaWxv.4nGp4ZY9Gsxo

Let me paint you a picture. 🎨 First, a little context about me. I am a low code/no code builder through and through. Lovable? That's my comfort zone. Claude Code? Open Claw? No, really — These terminal-based tools are about as far from my natural habitat as you can get. However. I've just finished binge-watching four Claude Code videos from Nate Herk in AIS+ and I am 🔥FIRED UP! These videos a great, and I am excited to get started. My interpretation of Claude Code is it's basically like having a senior developer living inside your terminal, building apps for you while you sip coffee. And the skills, the loops, all the good stuff I picked up from those videos — I am READY to put it all to work. I want that life. I deserve that life. So I go to install it. What I thought would happen: Type one command. Done. Sip coffee. What actually happened: A 2-hour odyssey involving Git Bash, hidden folders, PATH variables, and at least three existential crises. 🤷 😂 🛠️ The Setup: Windows Is Not macOS Here's the thing EVERYBODY tells you upfront — Claude Code loves Mac and Linux. Windows? Windows gets the "bless your heart" treatment. The official docs mention something called Git Bash, which is basically a way to trick Windows into pretending it's Linux. Fine. I install Git for Windows. Straightforward enough. Then I try to paste a command into Git Bash. Ctrl+V doesn't work. Right-click. Paste. Nothing. 🫠 Turns out you have to use Shift+Insert to paste in Git Bash. A fun little secret the universe decided not to tell me. The PATH Problem (A Love Story) After installing Claude Code, I type claude into Git Bash and get: bash: claude: command not found🤦 It installed. I can see the file sitting there on my computer. But my terminal doesn't know it exists. This is the computer equivalent of your friend standing right next to you while you call their name and they don't respond.

Part 2 — Where It Happens First The shift to machine-speed IT will not happen everywhere at once. It will begin where systems already interact heavily, data moves continuously, and decisions are repeatable. In most enterprises, five areas are positioned to change first. ⚡ Infrastructure Operations Infrastructure monitoring is already heavily automated. The next step is autonomous coordination between systems. AI agents will begin to: - Detect anomalies across networks, storage, and compute - Diagnose root causes across multiple systems - Trigger remediation without waiting for human review - Reallocate resources in real time Instead of dashboards alerting engineers, systems will increasingly resolve issues before humans are even notified. 🔐 Cybersecurity Security is already a machine-speed problem. Attack traffic, intrusion attempts, and vulnerability scanning occur far faster than humans can analyze. As a result, security systems are moving toward agent-driven response loops. AI systems will increasingly: - Identify abnormal behavior across environments - Correlate signals from multiple tools - Automatically isolate compromised systems - Adjust security posture in real time Security will become one of the first domains where machines defend against machines. 📊 Data Pipelines & Analytics Today, data flows through layers of processing before reaching dashboards designed for human interpretation. But machines don’t need dashboards. AI agents will increasingly: - Monitor live data streams - Detect meaningful changes - Trigger operational responses automatically - Coordinate actions across multiple systems The role of analytics will shift from informing people to triggering systems. 💼 Financial Operations Many financial processes follow structured rules: approvals, reconciliation, forecasting, and compliance checks. These processes are prime candidates for agent-assisted decision loops. AI systems will begin to: - Monitor financial signals continuously - Flag anomalies and compliance issues - Execute policy-approved transactions - Coordinate across billing, procurement, and forecasting systems

You don’t need to have the company name do all the work. That’s rarely necessary. In many cases, the name carries identity — and the tagline carries clarity. Together, they do far more than either one alone. Think of it this way. The name is the container. The tagline explains what’s inside. A strong tagline answers the question people almost always ask when they hear a company name: “What exactly do you do?” It clarifies your positioning. It reduces confusion. It strengthens your market signal. For example: AI & Data Strategies LLC Adopt AI with confidence. The name signals the lane. The tagline signals the outcome. Or take AI Bits & Pieces. The name carries story and identity. The tagline clarifies the tone and focus. AI Bits & Pieces Quick quips, quirks, and insights on people + AI Used together, they create signal. 🎯 What a Good Tagline Should Do A strong tagline usually clarifies at least one of three things: What you do Who you help What outcome you create For example: AI Education for Operators Agent Systems for Founders Adopt AI with confidence Short. Clear. Memorable. It shouldn’t feel like a paragraph. It should feel like positioning. 🎯 The Simple Test Look at your name and tagline together. If someone reads both and still asks, “So what exactly do you do?” It needs tightening. The goal isn’t cleverness. The goal is signal. 🎯 The Strategic Advantage A well-constructed name and tagline together give you: - Clarity - Story - Positioning - Flexibility - Longevity The name anchors identity. The tagline carries explanation. And explanation is where positioning lives. 🎯 Final Thought for the Series Naming isn’t about sounding innovative. It’s about signaling the kind of company you’re building. Some names carry story. Some names carry clarity. Some names optimize for search. Some names are built for longevity. The key is choosing intentionally. And then supporting that name with positioning that makes the signal clear. For example: