Why This Exists
Let's be honest: the world of AI can feel overwhelming.
Agents. RAG. Embeddings. Vector databases. Guardrails. Function calling. Multi-modal models. Thinking models. Fine-tuning.
The terminology flies around in every tech article, every client conversation, every conference talk. You're expected to not only understand these concepts, but to know how they fit together and when to apply them.
That's exactly why this guide exists. We've collected industry leading resources and organized them into your personal roadmap through the AI landscape, making it easier to digest and follow.
What You'll Gain
A Structured Mental Model
The AI Periodic Table presented by Martin Keen from IBM Technologies gives you a framework to organize every AI concept you encounter. Instead of drowning in terminology, you'll see how pieces connect. When someone mentions "RAG," you'll immediately understand it sits in the Orchestration family, builds on embeddings and vector databases, and serves a different purpose than fine-tuning.
Revealed Unknown Unknowns
You don't know what you don't know. That's not a criticism—it's human nature. This framework systematically exposes the gaps in your knowledge so you can fill them intentionally rather than discovering them in front of a client or during a critical project.
Clear Growth Path
No more wondering "what should I learn next?" The learning tiers build naturally from foundational concepts to advanced techniques. Each tier represents a deeper understanding, not a finish line. You're always growing, always adding to your capabilities.
Credibility in Conversations
When a client asks about AI capabilities, you'll speak from genuine understanding—not memorized buzzwords. You'll know when to recommend RAG versus fine-tuning, when agents make sense versus simple prompting, and why guardrails matter in production.
Career Differentiation
AI proficiency is becoming table stakes in our industry. This framework helps you document your growing capabilities in a way that matters for your professional development. The portfolio you build becomes proof of real skill.
Practical Application
Every element connects to real work. You'll build things, not just study theory. The best way to understand a concept is to use it, and this is designed around that principle.
Why This Matters to Jahnel Group
Our clients are asking for AI capabilities, and we need to deliver with confidence.
What We're Building Toward
Genuine Understanding - When we say we can deliver AI solutions, we back that up with demonstrated knowledge. Not certificates on a wall, but genuine capability across our team.
Client Confidence - Enterprise clients need to trust that we understand what we're building. When our team members can articulate AI concepts clearly and make informed architecture decisions, that confidence is earned naturally.
Shared Vocabulary - We need to know who can work on AI projects and at what level. The learning tiers give us a common language—when someone says they're comfortable at Practitioner level, everyone understands what that means.
Collective Learning - As you progress, you'll contribute to our collective knowledge. Write-ups, demos, lessons learned—these become resources for everyone who follows.
This Is a Journey, Not a Destination
We want to be clear about something: reaching a tier doesn't mean you're "done."
The AI landscape evolves constantly. New models, new techniques, new best practices emerge regularly. The tiers exist to give us a common language for where we are in our understanding, not to create a finish line.
Think of it like fitness. You don't "complete" being healthy—you maintain it, build on it, adapt as you learn more. The same applies here. Foundation tier doesn't mean you stop learning foundational concepts. Practitioner doesn't mean you've mastered everything in that tier forever.
The portfolio work exists because building things is how you truly learn. The assessments exist to help identify gaps and confirm understanding. But the real value is in the journey itself—in the conversations you'll have, the projects you'll build, and the confidence you'll develop.
Ready to start? Head to the Getting Started guide, or explore the AI Periodic Table to see the full landscape.