MIKE UNHINGED 4
8 Skills Required for AI Futures?
AND WHY IT WONT WORK!
Based on the video, here are the 8 AI skills that will separate winners from losers in 2026, along with a short summary for each:
1. Skepticism [01:33]
Develop a strong filter against “get rich quick” claims and clickbait titles. Do not instantly believe every income claim or new tool hype you see on social media. Instead, cross-reference information and verify claims before diving into every new “shiny object.”
2. Learn How to Love Learning [05:07]
Shift your mindset from frantically chasing money to genuinely enjoying the process of discovery. Instead of stressing about being “behind,” set aside time to playfully explore AI tools without immediate pressure to produce results, which helps you adapt to the rapid pace of change.
3. Learn in Public [09:12]
You don’t need to be an expert to build a personal brand. Share what you are learning as you learn it. If you discover a cool prompt or workflow, share it on social media immediately rather than waiting until you have “built” something massive.
4. Context Engineering [13:09]
Move beyond basic “prompt engineering” by providing AI with deep background information. Use a structure that defines the AI’s role (e.g., “You are a 1% expert”), gives detailed context about your specific situation and constraints, and asks the AI to ask you clarifying questions before generating a solution.
5. Using AI as Your Sparring Partner [17:41]
Don’t just use AI to get answers; use it to improve your questions. Ask AI to act as a critic, a coach, or a skeptical investor to rip apart your ideas, identify blind spots, and challenge your assumptions rather than just validating them.
6. Vibe Coding [19:35]
Use plain English to “code” software. New tools allow you to describe a website or app in natural language, and the AI generates the code for you. This allows non-technical people to build simple web apps and prototypes quickly and cheaply.
7. Building AI Systems [24:26]
Move from manually using AI for one-off tasks (like drafting a single email) to building automated systems that work 24/7. An example is an AI customer support agent that can read tickets, access your company’s knowledge base, and resolve issues or process refunds autonomously.
8. Documentation [29:16]
Create high-quality documentation, which acts as the “brain” for your AI systems. For an AI to function reliably and scale without constant errors, it needs clear, written instructions and context on how to handle specific tasks and troubleshoot issues.
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Mike R. Jay is a developmentalist utilizing consulting, coaching, advising and helping… emergent from dynamic inquiry as a means to cue, scaffold, support, lift, and protect; offering inspiration to aspiring leaders who are interested in humaning where being, doing, having, becoming, contributing, relating, guiding to produce resilience and wellth help people lead generative lives.
