How to Build and Maintain AI Expertise

Want to become a Generative AI Architect? Start small and build step by step. 𝟭. 𝗟𝗲𝗮𝗿𝗻 𝘁𝗵𝗲 𝗕𝗮𝘀𝗶𝗰𝘀:   - 𝗣𝗿𝗼𝗴𝗿𝗮𝗺𝗺𝗶𝗻𝗴: Get comfortable with Python. Learn its syntax, libraries (like NumPy, Pandas), and basic coding practices.   - 𝗠𝗮𝘁𝗵 𝗘𝘀𝘀𝗲𝗻𝘁𝗶𝗮𝗹𝘀: Brush up on linear algebra, calculus, and basic probability. These form the backbone of AI. 𝟮. 𝗚𝗲𝘁 𝗜𝗻𝘁𝗼 𝗠𝗮𝗰𝗵𝗶𝗻𝗲 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴:   - Understand key ML concepts (supervised vs. unsupervised learning, evaluation metrics).   - Try out simple projects with scikit-learn to see these ideas in action. 𝟯. 𝗗𝗶𝘃𝗲 𝗗𝗲𝗲𝗽𝗲𝗿 𝘄𝗶𝘁𝗵 𝗗𝗲𝗲𝗽 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴:   - 𝗡𝗲𝘂𝗿𝗮𝗹 𝗡𝗲𝘁𝘄𝗼𝗿𝗸𝘀: Learn how they work (from neurons to backpropagation).   - 𝗙𝗿𝗮𝗺𝗲𝘄𝗼𝗿𝗸𝘀: Experiment with TensorFlow or PyTorch by building a few small projects (think image classifiers or basic NLP tasks). 𝟰. 𝗘𝘅𝗽𝗹𝗼𝗿𝗲 𝗚𝗲𝗻𝗲𝗿𝗮𝘁𝗶𝘃𝗲 𝗠𝗼𝗱𝗲𝗹𝘀:   - 𝗦𝘁𝗮𝗿𝘁 𝗦𝗶𝗺𝗽𝗹𝗲: Tinker with autoencoders and variational autoencoders (VAEs).   - 𝗦𝘁𝗲𝗽 𝗨𝗽: Once you’re comfortable, build a simple GAN to generate images.   - 𝗞𝗲𝗲𝗽 𝗨𝗽: Follow emerging techniques like diffusion models and transformers—these are pushing the field forward. 𝟱. 𝗕𝘂𝗶𝗹𝗱 𝗬𝗼𝘂𝗿 𝗣𝗼𝗿𝘁𝗳𝗼𝗹𝗶𝗼:   - Work on personal projects—even small experiments count.   - Share your work on GitHub or your blog. Real-world examples speak volumes. 𝟲. 𝗖𝗼𝗻𝗻𝗲𝗰𝘁 𝗮𝗻𝗱 𝗚𝗿𝗼𝘄:   - Join online communities, attend meetups, or webinars.   - Networking isn’t just for job hunting—it’s a great way to learn and stay motivated. 𝟳. 𝗞𝗲𝗲𝗽 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴:   - The field is evolving fast. Follow thought leaders, read research papers, and always be curious. 𝗕𝗼𝘁𝘁𝗼𝗺 𝗹𝗶𝗻𝗲: Start with one small project, build your skills gradually, and don’t be afraid to share your journey. Every expert began somewhere. Happy coding!

Learning to build with AI—not just chat with it—is everyone’s most important career opportunity right now. I’ve developed a four-step framework to go from casual user to builder: Phase 1: Think like a builder - Embrace the builder attitude - when an app doesn't meet your needs, improve it or build one with AI assistance - Adopt an "automation" mindset - delegating work to computers makes your output more trustworthy and reliable - Stay flexible and dynamic - the GenAI landscape evolves rapidly, so avoid rigid thinking Phase 2: Master GenAI’s inner workings - Understand how LLMs actually work - including the illusion of "memory" and the critical concept of context windows - Master proactive context window management (this is arguably the most important skill) - Switch from scattered back-and-forth conversations to consolidated, complete requests that include all requirements upfront (tip: build reusable prompt templates that embed fixes for common AI behaviors) In our class, we highly recommend a way of building -- document driven approach. It's much easier to improve documentation than improving code directly, and the result is an artifect that you can take to different tools to get the best result. Phase 3: Strategic delegation and implementation - Identify your core competencies vs. limiting factors, then strategically delegate to AI - Delegate consensus-based and transformation tasks (summarizing, code generation, format conversions) - NEVER delegate critical thinking, original insights, or emotional impact - these are your unique strengths Phase 4: Continuous learning and development - Learn by building and experimenting - GenAI is hands-on - Use top-down learning: ask GenAI direct questions, then explore deeper - Develop management skills for AI - treat it like managing a team member Want to dive deeper? I teach a course with Yan Wang where you’ll learn how to: - Move from prompts to building real prototypes. - Manage AI’s limits (laziness, forgetfulness, hallucinations) - Delegate effectively with clear criteria and safeguards. - Integrate AI into real workflows to compound productivity. Our next cohort kicks off this November: https://bit.ly/4p38xC5

𝟵𝟳 𝗠𝗶𝗹𝗹𝗶𝗼𝗻 𝗔𝗜 𝗝𝗼𝗯𝘀 𝗔𝗿𝗲 𝗖𝗼𝗺𝗶𝗻𝗴—𝗛𝗲𝗿𝗲 𝗔𝗿𝗲 𝟲 𝗦𝘁𝗲𝗽𝘀 𝘁𝗼 𝗣𝗶𝘃𝗼𝘁 𝗬𝗼𝘂𝗿 𝗖𝗮𝗿𝗲𝗲𝗿 𝗦𝘂𝗰𝗰𝗲𝘀𝘀𝗳𝘂𝗹𝗹𝘆 AI is transforming industries faster than we imagined. According to the World Economic Forum, by 2025, 85 million jobs will be displaced, but 97 million new ones will be created. The real question is: Will your career adapt to this shift, or risk being left behind? Back in 2018, I decided to pivot into AI. Here’s exactly what I did to make the shift, and how you can do it too: 1 - Learn the Fundamentals: Don’t wait for your company to train you. Back then, I joined one of the first executive AI courses at Stanford University. ↳Today, platforms like LinkedIn Learning ( 1 click away ) and Coursera make it easier than ever to start. ↳Own your learning—curiosity is your greatest advantage. Follow people like Andrew Ng who is always sharing great content and free here. 2. Integrate AI Into Your Current Role: I started small by incorporating AI into strategy discussions, product improvements, and productivity initiatives. ↳Whether it’s better forecasting, writing, smarter customer engagement, or automating workflows, go find a way for AI to add value in your role right now. 3. Play to Your Strengths: Pivoting doesn’t mean starting from scratch. ↳I didn’t try to become a data scientist—I focused on using AI to innovate and reinvent businesses, which was my core strength. Find a niche within AI that fits your expertise, and build from there. 4. Rebrand Yourself: Update your job title to reflect your focus on AI. ↳Add “+ AI” and show your commitment by writing, speaking, or even teaching about how AI impacts your field. ↳Thought leadership is built by taking action, not waiting for permission. 5. Be Relentless About ROI: AI is powerful, but it’s not cheap. ↳Avoid the hype by always tying AI initiatives to measurable outcomes. ↳Knowing exactly how AI creates value will set you apart as a strategic thinker. 6. Build Your Career Path Around AI: Once I integrated AI into my work, I expanded further—joining AI companies, advising startups, and eventually writing a book (coming soon) about the field. ↳These moves weren’t without risk, but they aligned with my vision for the future. AI has become central to everything I do, and it’s been worth every step. For additional inspiration, follow Allie K. Miller—a top AI influencer whose career pivot from an employee in AI to an entrepreneur and evangelist in the field has inspired many people, including myself. Let me know the steps you are taking to make AI part of your career. If you like this post share it to network ♻ #AI #JobsOnTheRise #GetHired2025 #career