AI Learning Roadmap 2026
Clarity Over Chaos.

The AI field has shifted dramatically. In 2024, the focus was on understanding transformers and fine-tuning models. In 2026, the priority is building with LLMs: agent frameworks, production RAG systems, prompt engineering, and AI-native application architecture. Most older roadmaps spend weeks on concepts that are now commoditized by APIs. A 2026 roadmap prioritizes what actually gets you hired today.

Priority order for 2026: 1) Solid Python and API skills as your foundation, 2) Deep understanding of LLM capabilities and limitations, 3) Building agents and multi-step AI workflows, 4) RAG and vector database implementations, 5) Production deployment and evaluation. Skip the deep learning theory unless you're targeting research roles. Focus on building real applications that solve problems.

Self-study works if you have strong self-discipline and can figure out what to prioritize. The challenge is that the field moves fast and generic courses can't tell you which skills match YOUR background and goals. Personalized coaching accelerates your path by 3-6 months because you get guidance tailored to your situation, not a one-size-fits-all curriculum. Most people benefit from at least some structured guidance.

Most clients invest 10-15 hours per week, but this can be flexible based on your schedule. We'll have weekly 1:1 calls plus time for you to work on projects and learning. The key is consistency. Regular, focused effort beats occasional marathons.

Not necessarily. While some programming experience is helpful, many of my clients have successfully transitioned from web development, data science, or other technical backgrounds. We'll assess your current skills during our strategy call and create a personalized plan that meets you where you are.

Focus on fundamentals that transfer (programming, system design, understanding LLM patterns) rather than chasing every new tool. Follow a few high-signal sources rather than consuming everything. Build projects with current tools so you develop intuition for what matters. A good coach helps you filter signal from noise and focus on skills with lasting value.

You become a member of the AI Native Engineer community, and you stay and keep going. Career transitions take different amounts of time for everyone, and I'm not going to abandon you if things take longer. You get ongoing support through good times and bad.

Online courses give you content. 1:1 coaching gives you a personalized roadmap, direct feedback on your work, career strategy, interview prep, and accountability. You get answers to your specific questions and guidance tailored to your unique situation instead of generic advice meant for everyone.

Investment details are discussed during the 30-minute strategy call, where we'll assess your goals and create a custom plan. The program is designed to pay for itself quickly through your increased salary. Most AI engineers see a 20-50% pay increase.

Absolutely. Most of my clients work full-time and make steady progress. We'll schedule calls at times that work for you and create a realistic plan that fits your schedule. Consistency matters more than intensity.