looking for experienced with (GHL) and CloseBot to help us:✅ Build out database reactivation campaigns✅ Migrate our system to CloseBot V2✅ Assist with workflow setup and real-time campaign testing 💰 This is a paid role.If you’re skilled in automation, workflows, and integrations — we’d love to work with you!

(watch out for this) Just yesterday, I hopped on a call with an AI Founder who was obsessing over outreach to get more leads. But after checking out his funnel, I spotted the issue in 5 minutes. It wasn’t the outreach at the top of the funnel. He was bleeding leads in the middle of the funnel, without even knowing it. Let me explain… If your AI service comes with barriers like: • “You just need to install X first” • “We can only help if you already do Y” • “This only works if you're xyz” Each one of these scares away prospects. But not because they’re bad fits! You’re just adding friction that doesn’t need to be there. If you make it as easy as possible to start… It becomes harder to walk away. So make sure you eliminate all friction by offering a full done-for-you service. And watch your conversion rate skyrocket. For example, if you have an AI service for customer support ✖️ Don’t say: “just send us over your FAQ’s you’ve written.” ✓ Say: “our system will learn from your past support tickets and build your knowledge base for you before we begin automating.” Now you’ve also granted yourself a higher price tag too. If you want to improve your client acquisition as an AI Founder, just do this: 1. List all the requirements → what do you need from prospects before you can help? 2. Own the setup → offer to do ALL of it for them as part of your service. 3. Advertise this → make "done-for-you" your main selling point. Think of your offer like a bucket. It doesn’t matter how much traffic you pour in it if there are holes in the bottom. Every barrier, every “you need” is a hole. And you’re losing your best prospects before you even know they exist. Seal the holes, and the same visitors will turn into: → more leads, more bookings, more clients, and more revenue. Ease is the ultimate conversion lever. The path of least resistance is the path to most revenue. __ I help AI Founders market their services. Follow me on LinkedIn for more content like this.

Today I hit a wall — tired, unmotivated, and I had to take a nap. When I got back up, I confirmed another AI workshop and rescheduled a business conversation for today. The lesson: discipline isn’t about never falling down, it’s about always getting back up. Progress is built step by step, consistently.

Now AI can hold a natural conversation in multiple languages, switching seamlessly between English, Spanish, and more. It can answer questions, guide the customer, and even book an appointment in real time. I’ve attached a short demo below so you can see how it works. Do you think this kind of multilingual support could actually replace a receptionist, or is it still too early?

I’ve been watching the hype around reasoning-capable AI, and it all seemed so polished – intelligent, methodical, reasonable. We’re told these models can break down tough tasks into logical steps, produce a chain‑of‑thought and edge us closer to real “thinking.” But recent research throws a damp squib on that image. Apple’s "Illusion of Thinking" In June, Apple’s lab published “The Illusion of Thinking: Understanding the Strengths and Limitations of Reasoning Models via the Lens of Problem Complexity.” arxiv apple They pitted so‑called reasoning models (LRMs) against clean, logic puzzles – like Tower of Hanoi, River Crossing and Blocks World – with programmable complexity. Findings? These models perform well up to a point, but once complexity hits a threshold, their accuracy collapses to zero. They don’t ramp up; they give up. Some even stop using their token budget midway, essentially throwing in the towel. arize Journalists at The Verge reported the same: “LRMs face a complete accuracy collapse beyond certain complexities.” theverge Enterprise Echoes: Jagged Intelligence Over at Salesforce, researchers have coined the term jagged intelligence to describe this erratic behaviour. salesforce Yes, reasoning models can shine on medium‑difficulty tasks, but their performance is inconsistent, with sharp drops in capability exactly where reliability matters in real‑world settings. Enterprise General Intelligence remains aspirational. As Salesforce frames it, businesses need capability + consistency, not just impressive bursts of intelligence. itpro