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‼️ We’re Always Hiring — But Not Just Anyone.
If you’re in this community, you already know we don’t operate like a normal company. We move fast. We execute hard. We don’t just learn about AI — we build with it daily. If you’re looking for “slow, steady, and safe,” this isn’t for you. We’re building the future — and that takes a different kind of operator. We don’t care about degrees or titles. We care about execution, attitude, and how fast you can learn. More importantly, we’re looking for people who: - Don’t need constant hand-holding - Hate mediocrity - Actually want to make an impact So if you’re hungry, sharp, and ready to move — This is your shot. Check our open roles and apply here: Morningside: https://bit.ly/ms-skool AAA Accelerator: https://bit.ly/aaa-skool We’ll keep this post pinned — we’re always looking for A-players. Let’s see what you’ve got.
‼️ We’re Always Hiring — But Not Just Anyone.
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Must Read for Anyone Starting an AI Business
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_
Why do so many local/boutique brands still use clunky, slow websites instead of clean setups
was trying to buy some custom gear from a small brand recommended in a hobby group, and the site took 8 seconds to load. I gave up and closed the tab. In 2026, a slow website is literally throwing money away. As a customer, I value my time. Do you guys buy from slow sites, or do you bounce immediately?
Why do so many local/boutique brands still use clunky, slow websites instead of clean setups
I have a client that wants a sales follow up email i need help
So i have built it, and im wondering, should i build it for them in claude routines? sceduled task? on desktop app? on web? or should i set up VScode for them? should i just have the bot draft the emails first? do you guys have any recommendations when building a sales follow up email bot? how have you built yours?
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A lesson from building a job-costing automation: always pick a source of truth
Something I've learned building automations for small businesses: the biggest point of failure usually isn't the AI part, it's the handoff between tools. Example, a job-costing system I built recently pulled data from QuickBooks, a CRM, and payroll. The AI logic was the easy part. The real work was making sure data stayed in sync when someone updated a job in the CRM but not in QuickBooks, because that's exactly where automations quietly break and nobody notices until the numbers are wrong. My rule now: before automating a task, map out every place the same piece of data lives, and decide which one is the source of truth. Skipping that step is why so many automation projects look great in a demo and then fall apart within a week of real use. I do this kind of build work using Claude Code, mostly for real estate, recruitment, and service businesses. Not trying to sell anything here, just sharing what I've run into. Happy to talk shop if anyone's working on something similar.
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