Let’s set expectations from day one. This community exists for one reason only: to help people actually use AI to build, automate, and scale real work, not just talk about it. Lateral Teams is not a “prompt collection”. It’s not another theory-heavy AI space. And it’s definitely not about chasing hype. We’re building an AI-powered system that helps teams and creators automate content creation and execution in a way that’s sustainable, repeatable, and human. The app is dropping very soon, and this community is part of that build. Here’s how this space works: This is a build-in-public community. You’ll see what we’re building, what’s working, what’s breaking, and why certain decisions are made. This is also a two-way space. Your feedback matters. Your questions matter. What you struggle with matters. The product will evolve based on real usage, not assumptions. Inside this community you’ll find: – early access to the app – practical frameworks and workflows – real examples from live use cases – and conversations around automation, systems, and execution If you’re here just to consume, that’s okay. If you’re here to build, test, and improve how you work with AI, you’re in the right place. Quick ask to get things moving 👇 What’s the one thing you’d most like to automate or simplify in your work right now? Let’s build this properly.

In our last post, we talked about how AI is a "data problem," not just a "prompt problem." But there’s a second hurdle that kills most AI implementations: Linear Thinking. Most teams try to use AI to do exactly what they were doing before, just slightly faster. - Old way: Write an email manually. - "New" linear way: Ask ChatGPT to write that same email. That’s not a system; that’s just a faster typewriter. Lateral Teams operate differently. We don't look for a better typewriter; we look at the entire communication architecture. In the Buss Down Chef case mentioned yesterday, the solution wasn't just "using an AI image generator." It was building a workflow where product data and brand identity were merged before the AI ever touched it. To build a truly "Lateral" workflow, you need to ask three questions: 1. The Input: Is the data I’m feeding the AI structured, or is it just noise? 2. The Logic: Am I asking AI to think or just to format? (Hint: It’s better at formatting structured thought). 3. The Feedback: How does the output get better tomorrow without me typing a longer prompt? The "Lateral" Challenge for today: Take one repetitive task your team does. Instead of asking "How can AI do this?", ask: "If I had 1,000 people doing this task for free tomorrow, how would I organize the data so they couldn't possibly mess it up?" That organization is your system. The AI is just the engine. What’s one process in your business that feels "stuck" in a linear workflow? Let’s brainstorm how to flip it laterally in the comments. 👇

When we started building Lateral Teams, we didn’t begin with features or hype. We began by solving real problems for real teams. Here are two early use cases that shaped everything we’re building. The first one comes from Buss Down Chef. https://www.skool.com/buss-down-chef-9497/about They had a strong product and an engaged community, but their content didn’t reflect the energy of their brand. No street vibe, no culture, just clean product photos. Weekly shoots were expensive and unsustainable. Using AI as a system (not as a toy), they turned simple product assets into cinematic, on-brand visuals. Same product. Completely different perception. Engagement went up because the content finally matched the identity. The second case comes from outbound and content workflows. Most people think personalization is a prompt problem. It isn’t. It’s a data problem. By structuring data first and then layering AI on top, we helped teams generate messages and content that actually sound researched, relevant and human. Less noise, more real conversations. Different scenarios. Same lesson: AI works when there’s a system behind it. This community exists to build that layer: systems, workflows and thinking that make AI useful in the real world. Curious to hear from you: What are you trying to build right now and where do you feel AI still “doesn’t quite work” for you? 👇