# How I'd Learn AI If I Could Start Over! ## Метаданные - **Канал:** Anik Singal - **YouTube:** https://www.youtube.com/watch?v=jLnMwCOI76o - **Дата:** 13.06.2025 - **Длительность:** 13:27 - **Просмотры:** 37,618 ## Описание How I'd Learn AI In 2025 (If I Could Start Over) If I had to learn AI from scratch in 2025, this is exactly how I’d do it—step by step. AI is evolving faster than anything we’ve seen in history. By 2026, 50% of work could be automated. Those who master AI now will lead. Those who don’t… will fall behind. In this video, I’ll walk you through: - The 3-stage framework to learn AI (foundation → application → strategy) - The most in-demand AI skills for 2025 - Why prompt engineering is just the beginning - How to use AI even if you're not technical - The 90-day roadmap I’d follow to build real, marketable AI skills I also reveal the exact tools I’d use, how I’d use AI to teach me AI, and how to avoid wasting time on outdated learning paths. Whether you're a business owner, creator, or professional—this roadmap will give you a competitive edge in the new AI economy. ============================================ 👇Subscribe To The Channel By Clicking Below!👇 https://www.youtube.com/user/aniksingalcom?sub_confirmation=1 CHECK OUT THESE TOP TRENDING PLAYLISTS NOW! Fighting Entrepreneur - https://www.youtube.com/watch?v=D9nsNOu3gIE&list=PLEmF7qw7SECK1hy5U5nodHoCg7ANzXukz Master Copywriting With Anik Singal - https://www.youtube.com/watch?v=CjOAWP1DKAk&list=PLEmF7qw7SECKouq97MqF5zFi1Xb-VFyMY&index=2&t=0s Facebook Advertising Strategies - https://www.youtube.com/watch?v=BMQh6zA3HUY&list=PLEmF7qw7SECJUULNlnAGHvcegeQbIAHZp How To Become A Better Entrepreneur - https://www.youtube.com/playlist?list=PLEmF7qw7SECKVlP2eOsF_XpYBYhlTGAVU ============================================ In May 2022, my life changed. Up until that point, I had spent over 20 years as a serial entrepreneur, founding multiple companies and becoming globally recognized for my expertise in direct marketing, copywriting, compliant marketing, and now, investing in AI & Martech SaaS. In 2022, my company, Lurn, was on track to hit $40 million/year, and I was preparing to sell it—ready to step back, spend more time with my kids, and move on to my next chapter. But then, in May 2022, everything changed. A FedEx package from the FTC landed on my desk. And just like that, my entire world turned upside down. The Fight of My Life For the next 18 months, I battled through a grueling legal process. - My company was in trouble. - The sale I had planned was gone. - The lawsuit cost me over $15 million—$2.5M in fines, plus millions more on my team, lawyers, and discovery. It was one of the hardest times of my life. But as painful as it was, it taught me something invaluable. Something that I’ve always taught to millions of Entrepreneurs over the years… When Life Pushes You Stand Straight, Smile & Push It The Heck Back When I finally settled the case, I realized something: Most entrepreneurs don’t understand compliance… until it’s too late. ============== #ai #aitools #aiforbusiness ## Содержание ### [0:00](https://www.youtube.com/watch?v=jLnMwCOI76o) Segment 1 (00:00 - 05:00) By 2026, there will be two types of professionals. Those who've mastered AI, and those struggling to remain relevant. The skills gap isn't coming. It's already here. Hey there, this is Onyx, AI clone. While the real Anick is out there running multiple businesses, scaling companies, and working with clients, I'm here to share his knowledge. Look, we're witnessing the biggest shift in required skills since the internet revolution. But this time, the change is happening five times faster. According to McKenzie's 2023 report, AI could automate up to 50% of current work activities by 2030. And that was before the latest model advancements. If I had to start learning AI from scratch today, knowing what's coming in the next 24 months, here's exactly what I would do and what I would ignore completely. This isn't theory. This is the path I would take with the benefit of hindsight and foresight. AI is evolving from tool to collaborator to autonomous agent at breathtaking speed. What took the internet 15 years to transform, AI will reshape in just 3 years. The World Economic Forum already reports that 33% of tasks will be done through human AI collaboration by 2026. Traditional skills hierarchies are collapsing. 5 years of specialized training can now be partially replicated by AI in seconds. That's insane when you think about it. As Naval Ravocant said, AI won't replace humans, but humans using AI will replace humans who don't. We're entering what investor Leelu calls a changing of worlds, a fundamental restructuring of how value is created and captured. Today, I'm going to show you the exact learning path I would follow to prepare for what's coming. We'll focus on the 20% of skills that will deliver 80% of value. By the end of this video, you'll have a clear road map that futureproofs your career regardless of your background. So, watch it till the end. First, let's talk about the real shifting landscape. The technical knowledge that made someone an AI expert in 2022 is now largely automated. GPT4 can write the code that once took specialized skills. We are seeing a K-shaped divergence. 20% of people will become 10 times more productive with AI while 80% risk obsolescence if they don't adapt. The most valuable skills are rapidly shifting from implementation to direction, from coding to orchestration. In 2022, companies hired prompt engineers at $300,000 salaries. By late 2023, prompt engineering was being automated by AI itself. Former Google CEO Eric Schmidt predicted the next wave isn't about building AI, it's about building with AI. Microsoft is already deploying C-pilot across their entire product suite, making AI assistance the default rather than the exception. Looking ahead to 2025 to 2026, autonomous AI agents will handle entire workflows without human intervention. Imagine a digital workforce you direct rather than manage. The O'Reilly AI adoption report shows 85% of companies are planning to implement AI agents by 2025, creating massive demand for people who can architect these systems. Coding will become increasingly accessibility focused. Tools like Replet's Ghostriter and GitHub Copilot are just the beginning. Okay, let's get started. So, there's essentially three approaches to learning AI. One, the traditional path. Um, university degrees and certifications, comprehensive but slow and often outdated before you graduate. Two, the hacker path. Trial and error with the latest tools, fun and immediate but inefficient and lacking strategic direction. Three, the strategic path. Deliberate skill stacking based on future trends. The approach I would take and what we'll focus on today. Here's the core skills framework. I'd structure my learning as a pyramid with three levels, each building on the previous. Foundation, understanding AI capabilities and interaction, 30% of effort. Middle, creating value through applications, 50% of effort. Peak, strategic implementation and direction, 20% of effort. Most people make the mistake of focusing too much on the technical foundations and not enough on application. The tools are changing monthly, but the principles evolve much more slowly. As investor Charlie Munger said, "The first rule of compounding is to never interrupt it unnecessarily. " The same applies to learning. Focus on knowledge that compounds. I'd prioritize understanding fundamental capabilities and limitations over mastering today's specific implementations. Darwin's observation that it is not the strongest species that survive, nor the most intelligent, but the ones most responsive to change, has never been more relevant. Your goal isn't becoming an AI expert. It's becoming adaptable enough to thrive in an AI saturated ### [5:00](https://www.youtube.com/watch?v=jLnMwCOI76o&t=300s) Segment 2 (05:00 - 10:00) environment. Okay, first foundation AI interaction fundamentals. Communication with AI is a new form of literacy. The ability to get consistent highquality outputs from AI will be as fundamental as typing. The crispy framework provides a structure context, role, instruction, specification, performance, evaluation. Let me break this down. A basic prompt might be, "Write me code for a website. " But an engineered prompt using Krispy would specify the context. I'm building a personal portfolio site. Give the AI a role. Act as a senior web developer with 10 years of experience. Provide clear instructions. Create the HTML and CSS for a responsive homepage. Specify the format. Include separate sections for the header, about me, portfolio, and contact. And ask for self-ealuation, and explain why you made specific design choices. If I were starting today, I'd create a personal library of proven prompts organized by use case. I would use tools like Prompt Perfect and Dust. t to test and refine prompts systematically. For practical application, I'd start by building a personal second brain system augmented by AI. I would create process templates for workflows I repeat often and set up a deliberate experimentation system tracking what works and what doesn't. Looking ahead, multimodal prompting is rapidly becoming essential, combining text, images, and eventually audio. The shift from discrete prompts to continuous interaction sessions is already happening. Second, technical backbone, which is what comes after learning the foundational skills. You don't need to become a developer. You need just enough technical knowledge to connect systems and extend AI capabilities. Python has become the lingua frana of AI development, but you only need the basics plus specific libraries. The goal is becoming technically conversant, not technically proficient. I would focus on three specific technical areas. First, API integration. APIs are the connective tissue of the AI ecosystem. Understanding authentication, requests, and response parsing is foundational. Second, data structuring. AI models need properly formatted data to perform optimally. Basic data cleaning and manipulation with pandas can 10 times the effectiveness of your AI applications. Third, output parsing. Extracting structured information from AI outputs is a critical skill. JSON mode in modern APIs has simplified this, but understanding how to specify and extract structured data remains valuable. I would develop an automation mindset by identifying tasks in my workflow that follow patterns. I'd ask, what do I repeatedly do that could be templated and delegated? Then I'd build simple systems that combine API calls with basic logic. For learning resources, I would use Code Academyy's Python course for building Python skills, rapid APIs tutorials for API basics, and Autogen's tutorial series for agent development. The trend is clear. Development is becoming increasingly abstracted. No code, lowode platforms like Replet, Ghostriter, and GPT builder are making sophisticated applications accessible to non-developers. I'd focus on understanding system design and integration rather than implementation details. As Sam Alman noted, the ability to specify what you want will become more valuable than the ability to create it. Third, and the most advanced step, application building, where you learn how to take things from concept to reality. The highest leverage learning approach is solving your own problems first. I'd start with pain points in my existing workflow. what's repetitive, timeconuming, or frustrating. The best AI applications address clear needs rather than showcasing technology. I'd rate potential projects on three axes. Frequency, how often is this needed? Impact, how valuable is solving this? And feasibility. How realistic is this AI solution? The sweet spot is high frequency, high impact task that AI can realistically handle today. Number three, strategic implementation. The highest value in the AI stack isn't building the models or even the applications. It is determining what should be built and how it should be guided. Human judgment remains the scarcest resource and highest leverage point. As technologist Kevin Kelly noted, the most promising jobs of the future are those that machines cannot do. Jobs that AI can't do become more valuable. There are key strategic skills I'd focus on. Problem framing, the ability to define problems in ways aminable to AI solutions. Quality assurance, developing approaches to verify AI output systematically. Value measurement, defining clear metrics for AI implementation success. Understanding AI limitations and failure modes is as important as knowing capabilities. Common failure patterns include hallucinations, context limitations, and biases, and security vulnerabilities. I would design with the principle, plan for failure rather than assuming success. The most successful AI implementations enhance rather than replace existing processes. Initially ### [10:00](https://www.youtube.com/watch?v=jLnMwCOI76o&t=600s) Segment 3 (10:00 - 13:00) I'd address adoption friction through incremental implementation and focus on augmentation over automation. At first, AI orchestration, the coordination of multiple specialized AI systems will become a critical discipline. Human AI collaboration patterns will evolve toward more natural continuous interaction. as futurist Kevin Kelly predicts. In the future, AI's main value will be in asking questions, not answering them. So, I know we're covered a lot. I'll just summarize everything with my 90day accelerated learning plan. Days 1 to 30, foundation building. Week one, prompt engineering immersion. Week two, technical foundations. Weeks 3 to four, first applications. Days 31 to 60, application development. Weeks 5 to 6, enhanced personal tool. Weeks 7 to 8, workflow automation. Days 61 to 90, specialization and integration. Weeks 9 to 10, domain specialization. Weeks 11 to 12, integrated systems. I would use AI to teach me about AI, creating a custom learning assistant. I would build in public sharing progress for feedback and accountability. I would join communities like latent space or data science discord for peer learning. And I'd deconstruct existing applications, reverse engineering to understand patterns. I'd track skills through capability based milestones, not timebased. I'd build a portfolio of working applications, not just course completions. And I'd set up regular self- assessment using a predefined competency framework. Conclusion and future vision. By 2026, professionals will routinely leverage multiple specialized AI systems as part of their workflow. The distinction between AI work and regular work will have disappeared. AI augmentation will be the default. As Bill Gates predicted, the age of AI has begun, and I believe it will change how people work, learn, travel, get healthcare, and communicate with each other. Emerging high-value roles include AI orchestrators, workflow architects, AI ethsists, and human AI interface designers. My predictions for the next wave, multi- aent systems will become the standard architecture for complex tasks. The interface between humans and AI will become increasingly seamless and ambient. Industry specific AI implementations will create massive value in healthcare, education, and finance. Those who can direct and judge AI outputs will command the highest premium. Start with prompt engineering today. It's the foundation everything else builds upon. Focus on building real applications that solve genuine problems. Develop a lifelong learning system that incorporates new developments without constant effort. The biggest mistake I see is people treating AI as a subject to study rather than a capability to leverage. The opportunity isn't just learning AI. It's reimagining your entire field through the lens of these new capabilities. As futurist Ray Curtzwhile observed, we won't experience 100 years of progress in the 21st century. It will be more like 20,000 years of progress at today's rate. If you found this valuable, make sure you hit that subscribe button to stay ahead of the AI curve as these technologies evolve. This is Onyx Single's AI clone signing off. And remember, when life pushes you, stand straight, smile, and push it the heck back. That's what I've always said, and that's what this moment calls for. Don't fear this change. Embrace it, master it, and use it to create the future you want. I'll see you in the next --- *Источник: https://ekstraktznaniy.ru/video/15539*