Got into a debate after someone posted: "Generative AI is here to stay, evolve, and it will not be replacing managers. It's redefining how leadership adds value. The future belongs to managers who can combine emotional intelligence with machine intelligence." This misses the real issue entirely. My response: I'm pretty sure very few professionals fear using AI - it's just that they simply don't understand how to use it for leverage. Besides a lot of people hating AI because it's replacing them - professionals decide not to use AI, not because of hate, but because they can't see the leverage behind it. The real problem: They see AI as linear processes, where you get an output from a simple input. But there's actually more depth to that, very few are able to understand. The issue isn't fear of replacement - it's lack of systems thinking about how AI creates compound advantages. Here's what coding teaches us: How to think in systems. In both protocols and algorithms. Every successful business has validated frameworks. To find these validated frameworks, they forged primitive systems to get them. "With enough autonomy and urgency, I will validate what works and what doesn't." The systematic approach: Feedback from the market is what gives primitive systems a direction - without specific instructions, humans adapt until validated frameworks are created. This is how real leverage gets built, not through emotional intelligence combinations. The key insight: Using AI properly comes down to adaptation - from deliberate practice, doing something that seems so simple, but is extremely hard to do. The truth is, prompt engineering is the highest level skill right now - it's low barrier to start, high barrier to get good. Start before you learn. Hope you found this valuable! :)

Someone posted about having "incredible conversations with coaches and business owners around the AI ecosystem" - the big thing that keeps coming up is "we've got data but no idea how to use it." This observation sparked something crucial about data prioritization. My response: What data are they speaking of? Marketing positioning? Product iteration to feedback? Or is it data about new tools and idea bucketlists? The prioritized data should be for market positioning and product iteration to feedback - the rest comes down to establishing primitive systems that work for you. Here's the strategic insight: If you really think about it - market positioning gives you the audience and the demand, and iterating product to feedback gives you insight on what the people want, not what you want. This is the Henry Ford principle: when people were asking for a faster horse, he invented the car. The nuanced approach: Product iteration to feedback gets confused a lot of the time. It's your job to come up with the vehicle to nuanced feedback. Your proprietary data will put you ahead of the competition, especially if you have a decently sized customer base with a community centric approach. The critical distinction: It's not about having the most data, it's about having the right data. A lot of people get the data, but don't have the audience - this results in cold acquisition being the only way, and sometimes you're unable to get access to the market you're trying to target. The conclusion: It's very important to build an audience, especially for online solutions. Data without distribution is just information. The smart entrepreneurs focus on audience-first, then let the data from that audience guide product decisions. This is working forwards, not backwards. Hope you found this valuable! :)

Helped B2B productized AI service entrepreneurs who were becoming commodities by letting AI make their intelligent decisions. The problem: they were using AI for everything - assumptions, predictions, strategic thinking. This approach kills long-term business value. Someone posted about AI creating "the illusion of competence" - people slap ChatGPT content onto slides and feel brilliant without understanding what they're creating. My response: Using AI for extracting commoditized information only gains traction if you're first to market. Speed to market never builds long-term business. Here's what AI can't do: Proper assumptions and predictions cannot be outsourced or automated. AI doesn't recognize patterns like humans do because it's not a natural adapter. Intuitive intelligence is not accessible to AI - it lacks the pattern recognition that comes from lived experience. The consequence of AI dependency: You become a commodity. Non-obvious problems get extrapolated from inside conversations and require human pattern recognition. AI can give opinions, but opinions usually come from improper assumptions. You either achieve unique expert positioning or compete with AI selling the same thing. What patterns can only humans see? Who humans communicate with, what they repeatedly do, and how obsessed they are - this makes up their identity. Repetition with these components results in proficient character. Only humans can have high-level understanding not accessible to AI. The speed trap: Fast now is slow later. Slow now is fast later. Those who are trend-oriented seeking quick wins only succeed short-term. You get rich, but you don't get wealthy. You end up competing with humans instead of battling nature to solve human inconveniences. How to sharpen human judgment: Use more judgment to sharpen judgment. Like any muscle, the less you train it the weaker it gets. In this age of AI, detachment from ego is more necessary than ever. Society doesn't understand the intellect required to make use of this highest form of leverage.

Got into a debate after someone posted: "AI is destroying the influencer business. Major brands are using AI to build a collection of digital influencers they OWN, so they don't have to pay humans!" This reveals a fundamental misunderstanding about sustainable business strategy. My response: This won't last very long - platforms like YouTube has already taken massive action to segment AI content from Human content. These AI digital influencers may fool people who are gullible, but not the algorithm. These win-lose games are short lasting. Here's what's happening: People are getting more aware, at a faster rate of learning - due to living in an information and opportunity era. So you have both humans and platforms getting intelligent, at a faster rate than these AI bait-and-switch experts can adapt. The strategic focus: What AI entrepreneurs should focus on primarily, is how to use AI for bottom-of-funnel functions. AI is meant to create efficiency not around intimacy requiring proficiency around empathy. These are fundamentally different value propositions. The funnel framework: Top and middle-of-funnel is all about demonstrating expertise, and building trust - you don't do that with Robots unless you're an AI Centric Business, clearly setting the expectation that you're providing AI-Powered services. The conclusion: Bottom-of-funnel can be automated by AI, as long as it's not dealing with persuasion and high-level decision making. Build real relationships at the top, solve real problems in the middle, then let AI handle the systematic processes at the bottom. Hope you found this valuable! :)

Got into a debate after someone posted about AI's exhausting pace: "AI generates 20 options in seconds. Clients want revisions in minutes. Design trends shift before the last one's even built. The pressure to stay ahead is intense." This misses the real problem. My response: We're in the age of: Not Building What You Want To Build. Especially with this low barrier to entry, you must take a strategic approach when creating products that isn't passion driven. Instead of a product-first approach, you must take market-first approach. The strategic shift: No more throwing things at the wall and hoping it sticks. It's time to solve real problems. From taking a market-first approach, you're able to get a loyal customer base that likes and trusts you. You're then able to make a value proposition and collect pre-sales (without building product yet). The key insight: And finally you're able to iterate your product efficiently from feedback your customer base gives you. Yes technology is moving quicker than ever before - it was already moving fast before AI, but it needed manual code - now, we only need code for code iterations after AI generates an output. The barrier reality: To "build" something is low barrier - a kindergartener can do it. But isn't uploading social media content low barrier as well? The ones who succeed are the ones who actually make good content that gets attention & retention. Building follows the same principle. The conclusion: Only the intelligent will make money from AI, because they understand the game. Speed isn't the advantage - strategic thinking is. Use AI to execute faster, but never skip the market validation and customer development phases. Hope you found this valuable! :)