One challenge I've noticed with automation is that many workflows are fast—but not personal. Businesses often send the same message to every lead. The automation works... But the conversation doesn't feel human. So I built a workflow to change that. Here's how it works: 1️⃣ A webhook receives the request. 2️⃣ The workflow securely loads the required API credentials. 3️⃣ It retrieves the campaign details and messaging context. 4️⃣ An LLM generates a personalized message based on that context. 5️⃣ The output is structured and validated before it's used. 6️⃣ The final message is automatically sent to GoHighLevel for the next step in the workflow. The goal wasn't just to automate messaging. It was to make automated messages feel more relevant and consistent. One lesson I learned: Connecting the tools was actually the easy part. The real challenge was designing prompts and structured outputs that consistently produce useful messages. That's where most of the iteration happened. My takeaway: AI becomes much more valuable when it fits into a clear business process—not when it simply generates text. A good workflow combines: ✅ Business logic ✅ Reliable AI outputs ✅ Automation Together, they create a much better customer experience. 💬 Question for the Community If you were building an AI messaging workflow... Would you let AI write every message, or would you combine AI with predefined business rules? I'd love to hear how others are approaching this. 🚀 #AIAutomation #GoHighLevel #LLM #OpenRouter #WorkflowAutomation #AIAgents #BusinessAutomation

Hey everyone 👋 I want to make sure you’re truly using what’s inside the Classroom here on Skool — because it isn’t just theoretical content. It’s the proven starting point for building an AI service business in 2026, based on everything I've learned scaling my own 7-figure AI agency. When I first launched my business back in 2022, I was figuring things out in the dark — long days, trial and error, and a lot of mistakes before the real patterns finally emerged. Since then, I’ve worked with 7, 8, and 9-figure clients, helped thousands of people start AI agencies, and studied what separates the people who succeed from the ones who stall. And now the data is clear: There are TWO proven paths people are using to break into AI. All you have to do is choose the path that fits how you think and work. That’s why the very first thing you should do here is go to the Start Here module inside the Classroom. Inside it, you’ll find: - A clear breakdown of the two proven paths - Clarity on how to pick the one that fits you best - Then you'll find your playbook to land your first paid client fast Everything I wish I had when I started — the frameworks, playbooks, lessons, and action plans — is inside this Classroom. And I continue to update it based on what’s working right now. It’s all here for you, step by step. Don’t let this sit in your dashboard like another course. This is the stuff I lived to be where I am right now. If you aren't already, make sure you're following/subscribed to me for my latest content to help you on your journey: → Main Channel: https://www.youtube.com/@LiamOttley → VLOG Channel: https://www.youtube.com/@LiamOttleyVLOGs → Instagram: https://www.instagram.com/liamottley/ → X: https://twitter.com/liamottley_

The AI race is getting smarter. Your business should get pickier. 💰 AI company: "Our newest model is almost as powerful as our flagship, at a lower cost." Small business owner: "Now we're talking." 🤝 💡 Insight: Today's release of Claude Sonnet 5 highlights a shift in the AI market. Vendors are no longer competing only on capability, they're competing on value. Businesses buy outcomes, not benchmark scores. 📊 Business lesson: The question isn't, "What's the smartest model?" It's, "What's the cheapest model that consistently solves my problem?" 📈 Competitive advantage comes from cost per completed outcome, not model prestige. Source Anthropic. (2026, July 1). Introducing Claude Sonnet 5. https://www.anthropic.com/news/claude-sonnet-5

One thing I've been learning is that successful AI automation projects don't start with tools. They start with conversations. When I first began exploring AI automation, I was eager to think about: - Which LLM should I use? - Should I build it in n8n? - Would GoHighLevel be a better fit? - Which API is the fastest? - Now, I start somewhere completely different. I ask questions like: ✅ What repetitive task is taking up the most time? ✅ Where do mistakes happen most often? ✅ What process frustrates your team the most? ✅ If you could eliminate one manual task tomorrow, what would it be? The answers to these questions usually reveal the real opportunity. Not every business needs AI. Not every process should be automated. Sometimes the biggest value comes from solving one small problem exceptionally well. One lesson that's changed my approach: Don't start by designing the workflow. Start by understanding the workflow. The technology is important. But understanding the business comes first. That's what turns automation into a solution instead of just another technical project. Question for the Community 👇 What's the first question you ask before starting an AI automation project? I'd love to learn how others approach client discovery and solution design. 🚀 #AIAutomation #AIAgency #n8n #GoHighLevel #WorkflowAutomation #BusinessSystems #AIConsulting

The next wave of AI may not be massive cloud models. It could be micro AI: small, specialized models running locally on phones, laptops, and edge devices. They are faster, cheaper, more private, and often work without an internet connection. This creates a huge opportunity for micro SaaS. Simple AI-powered apps can solve one problem extremely well, using a local model most of the time and a larger cloud model only when needed. 💼 Business lesson: Don't chase the biggest AI. Build the smallest AI that solves a real customer problem. The next unicorn may not have the largest model. It may have the most useful one