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11h •
⚙️ AI Isn’t Magic, It’s Machines
AI feels invisible when it works well. We type a prompt, we get an answer, and it is easy to believe the system is limitless. But the teams who build sustainable advantages treat AI less like magic and more like machinery, powerful, useful, and governed by real constraints. ------------- Context: The Gap Between Expectations and Reality ------------- A lot of frustration with AI adoption comes from a simple mismatch. We expect the output to be instant, perfect, and cheap. We expect the tool to understand our business, our customers, and our context without being taught. We expect scale without tradeoffs. Those expectations are understandable because the interface is simple. It does not look like a factory. It looks like a chat box. But behind that interface are models that run on compute, require infrastructure, and produce outputs with variable reliability. When we ignore that physical and economic reality, we make decisions that seem logical but fail in practice. This is why some teams experience AI as transformative and others experience it as chaotic. The difference is not intelligence or ambition. It is operational thinking. Teams that treat AI as machines design workflows around cost, latency, failure modes, and monitoring. Teams that treat AI as magic keep being surprised. This post is about reclaiming realism, not dampening optimism. Realism is what turns AI from a novelty into a durable capability. ------------- Insight 1: Every AI Use Case Has a Cost Profile ------------- One of the most important shifts we can make is to stop thinking about AI outputs and start thinking about AI economics. Every call to an AI model has a cost. Sometimes the cost is financial. Sometimes it is latency. Sometimes it is complexity. Often it is all three. A low-stakes drafting workflow can tolerate slower responses and occasional errors because the output is reviewed. A real-time customer interaction cannot tolerate that. A workflow that runs thousands of times per day will expose cost and reliability issues that do not show up in a small pilot.
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1d •
Where are you using AI?
Where are you using AI, or learning AI to implement, right now? If it's somewhere else, let me know in the comments
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2d •
You know what’s crazy?
How many people think if they just don’t deal with something… it’ll magically work itself out. It never does. That conversation you’re avoiding? It doesn’t get easier next month. It gets heavier. Now there’s more emotion attached. More resentment. More fallout. That decision you’re putting off in your business? It doesn’t get cheaper. It gets more expensive. More money lost. More time wasted. More energy drained. Avoidance feels good for about five minutes. It gives you temporary relief. But you’re not eliminating the cost. You’re just adding interest. And here’s the part people don’t want to hear… Every time you avoid something, you train yourself to hesitate. Every time you face it, you train yourself to lead. The difference between people who win big and people who stay stuck isn’t intelligence. It’s not resources. It’s not even confidence. It’s speed of truth. Winners look at the ugly numbers. They have the uncomfortable conversation. They fire the wrong hire. They fix the broken system. They say what needs to be said. Not because it feels good. But because they know delay compounds pain. So if there’s something sitting in the back of your mind right now... that thing you keep saying “I’ll deal with it later”... that’s probably the thing you need to handle first. Discomfort now builds momentum. Avoidance builds debt. Your choice.
10h •
How I'm using AI to update my Linkedin Profile
Hi all, Wanted to share something I’ve been playing with in the hopes it can help you too. I originally shared a post about how the senior executives I work with are using AI to refine their LinkedIn profiles and attract their next role. (my specific niche) I’ve also shared this with my entrepreneur friends, and it works just as well for us as founders looking to sharpen our positioning. “The riches are in the niches,” everyone keeps telling us. And this is something I struggled with for a long time. Getting clear.Getting specific.Owning it. So here’s something you can experiment with. Take your current LinkedIn About section. Drop it into AI. Then try these prompts. 1️⃣Review what you know about me and ask me questions until you are 95% clear on who I serve and the outcomes I help them achieve. Then rewrite my LinkedIn About section in the style of a successful marketing copywriter you resonate with. (I chose Dan Kennedy) 2️⃣What would the top 1% of the clients I want to attract think when they land on my profile? 3️⃣What are the top 5 red flags potential clients might see when reviewing my profile or content? 4️⃣For each red flag identified, suggest specific changes to strengthen my positioning and reduce friction. 5️⃣Based on my profile and target audience, suggest stronger headline options that clearly communicate who I help and the transformation I deliver. And one more I’ve been testing: 6️⃣How can I refine my message so it feels distinct, memorable, unique and impossible to confuse with anyone else in my space? Don’t overthink it. Play with it. See what comes back. You don’t have to agree with everything it says. But sometimes it holds up a mirror you didn’t know you needed. Hope it helps. Happy experimenting. Would genuinely love to hear what shifts for you shout out and thank you to @Sabrina Ramonov from the AI advantage prompts for the initial inspiration and prompts that got me started down this rabbit hole.
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9h •
📰 AI News: ElevenLabs Adds “Expressive Mode” So Voice Agents Can Sound Human Under Pressure
📝 TL;DR ElevenLabs just launched Expressive Mode for ElevenAgents, making voice agents calmer, more empathetic, and better at handling tense customer calls. It is powered by a new conversational version of Eleven v3 plus smarter turn taking, so agents stop talking over people and start sounding genuinely helpful. 🧠 Overview Most voice agents fall apart in real life because they sound robotic or they interrupt at the worst moment. Expressive Mode is ElevenLabs’ push to fix both, emotional delivery plus better timing. The goal is not “fun voices,” it is production grade customer conversations where the agent can de escalate, reassure, and guide someone to a clear resolution. 📜 The Announcement ElevenLabs announced Expressive Mode for ElevenAgents, designed for real world customer support where frustration and urgency are normal. The upgrade bundles two major improvements, a more emotionally intelligent conversational TTS model and a new turn taking system that reduces interruptions. ElevenLabs also positions this as built for global operations, with emotional nuance scaling across 70 plus languages and improved delivery in languages and dialects where nuance has historically lagged. ⚙️ How It Works • Eleven v3 Conversational - A real time dialogue optimized TTS model that maintains conversational context across turns and reflects intent, emotion, and emphasis without sounding over acted. • Tone control on demand - Teams can steer delivery, calmer when a customer sounds worried, more direct when speed and clarity matter, while staying aligned with brand voice. • New turn taking system - Better timing so agents speak, pause, or wait more naturally, reducing the “AI keeps cutting me off” problem that kills trust. • Emotion signals from speech - The system uses real time transcription signals to infer emotion from how someone speaks, not just what they say, then adjusts when and how it responds. • Built for multilingual support - Expressive Mode is designed to carry emotional nuance across 70 plus languages, including stronger performance in languages like Hindi.
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