Learning in the Age of AI - The Challenges

Why Learning Feels Harder Than Ever — And What We’re Getting Wrong

If you've ever set out to learn something new — SQL, statistics, AI, or even just a new way of thinking — and found yourself stuck, you're not alone.

What seems like a straightforward topic often turns into a maze. Tutorials feel too fast. Terms feel unfamiliar. Progress feels fake.

This article is a reflection on why learning feels so hard — especially for self-learners, busy professionals, or anyone jumping into a new domain — and what we can do about it.

More than anything, this is an acknowledgment piece — a way to name the frictions many learners feel but rarely talk about.

Challenges in Learning a New Topic

1. Prerequisite Gaps

• Topic assumes concepts we haven’t learned yet

• Hidden dependencies only surface when we're stuck

• Hard to know what's missing until it's a problem

🔹 2. Terminology Overload

• Jargon is vague, overloaded, or inconsistently used

• Familiar words mean something new (“loadings,” “identification”)

• Poor scaffolding makes concepts feel alien

🔹 3. Skill Mismatch

• Needs unfamiliar skills (e.g., coding, syntax, logic)

• Understanding ≠ fluency — we can't execute the idea

• Multimodal demand: switching between code, math, diagrams

🔹 4. Cognitive Load

• Too many concepts or steps at once

• Unclear what’s core vs detail

• No visible input → transformation → output structure

🔹 5. No Anchor Points

• Concepts feel detached from anything we know

• Toy examples don’t connect to real-world relevance

• Learning feels like memorizing, not internalizing

🔹 6. Setup & Tooling Barriers

• Complex installation, environments, version issues

• Tooling distracts from concept learning

• Setup time outweighs insight gained

🔹 7. Time Constraints & Context Switching

• Learning happens in short, fragmented sessions

• Constant re-orientation breaks flow

• Competing priorities make deep work rare

🔹 8. No Clear Path or Sequence

• Many possible starting points — none feel right

• Uncertainty about what’s foundational vs advanced

• Fear of skipping something essential

🔹 9. How Deep Should I Go?

• Guilt about staying shallow

• Anxiety about going too deep too soon

• No definition of “good enough to move on”

🔹 10. Tutorials Don’t Build Confidence

• We can follow along, but not adapt

• Steps are shown, but logic isn’t

• We freeze when asked to apply or modify

🔹 11. Emotional Friction & Imposter Syndrome

• Past failures amplify fear

• We compare our behind-the-scenes to others' highlights

• Learning feels like proof of weakness, not growth

🔹 12. Missing Feedback Loop

• No clarity on whether we're right or wrong

• GPTs or guides may sound right even when they’re not

• No checkpoints to test understanding

🔹 13. Misaligned Resources

• Content doesn’t match our goals (business vs academic)

• Too advanced, too basic, or wrong sequence

• Doesn't fit how we learn (e.g., too text-heavy, not visual)

So What Can We Do?

We’re being asked to learn more — and do it faster — than ever before. But most of us are still using methods built for a slower, more predictable world.

What if today’s tools — especially AI — could help us learn not just faster, but smarter?

Sure, joining a course or learning community can help. But for me, something else clicked: ChatGPT.

➡️ In Part 2: Hacking Your Learning Process with ChatGPT, I’ll share how I started using GPT as a kind of learning preprocessor — helping me shape confusing topics around how I think, before I even sit down to study them.