# Starting My AI Journey: Claude 101 and AI Fluency (Framework and Foundations)

> Source: <https://dev.to/shreya_jayanna_0408/starting-my-ai-journey-claude-101-and-ai-fluency-framework-and-foundations-1hll>
> Published: 2026-07-12 22:39:57+00:00

Welcome! I'm Shreya, a data professional, and I started this blog to document my journey into AI and share every lesson, failure, and breakthrough I encounter along the way.

For my first post, I want to start where I actually started — with two courses that gave me a solid foundation: **Claude 101** and **AI Fluency: Framework and Foundations**. Here's what I learned from each.

This course was all about building a working relationship with Claude — from the basics to real, practical use.

**Meet Claude**

I started with the fundamentals: what Claude actually is, having my first real conversation with it, and learning how to get better result. I also got a walkthrough of the Claude desktop app — Chat, Cowork, and Code — and how each one fits a different kind of work.

**Organizing your work and knowledge**

This section shifted from "chatting" to actually *working* with Claude. I learned about Projects for organizing ongoing work, Artifacts for creating documents and content I could iterate on, and Skills for handling more specialized, repeatable tasks.

**Expanding Claude's reach**

Here's where things got interesting — connecting Claude to my own tools, using enterprise search to pull in relevant context, and using Research mode for deeper, multi-step investigations instead of one-off questions.

If Claude 101 was about the *how*, this course was about the *why* and *when*. It introduced a framework for thinking clearly about working with AI, rather than just using it reactively.

**The AI Fluency Framework**

The course opened with a simple but important question: why do we even need "AI fluency" as a skill? Then it introduced the **4D Framework**, which became the backbone of everything that followed.

**Deep Dive: What is Generative AI?**

Before jumping into technique, the course grounded me in the fundamentals of generative AI — how it works, and just as importantly, its capabilities *and* limitations. Knowing what AI is bad at turned out to be as useful as knowing what it's good at.

**The 4Ds, one at a time:**

**Deep Dive: Effective prompting techniques**

This tied Description and Discernment together with concrete techniques for getting more reliable, higher-quality outputs.

**The Description-Discernment loop**

Probably my favorite concept from the whole course — treating AI collaboration as an iterative loop rather than a one-shot request. Describe, evaluate, refine, repeat.

This is just the first entry. Next up, I want to start applying these concepts to real projects — combining my data background with what I'm learning about AI collaboration.

If you're on a similar path, let's connect — I'd love to learn alongside you! Find me on [LinkedIn](https://www.linkedin.com/in/shreya-p-j/).