I’m in a Whatsapp group with a number of successful UK-based entrepreneurs.

The common questions for the past 6 months have all been AI related.

How do I use AI? How can I learn about this stuff? How can I keep up?

I was chatting to one entrepreneur last week and he was telling me: "I've got 15 newsletters in my inbox, a Slack channel full of updates, and my LinkedIn feed is nothing but AI announcements. I'm drowning in information but I don't feel like I'm actually learning anything useful."

This captures perfectly the bizarre paradox we're all living through: we have more access to information than any humans in history, yet genuine learning often feels harder than ever.

But here's where it gets interesting. While helping him set up a systematic approach to learning with AI, I realised something profound had changed - not just in how much information is available, but in our entire relationship with knowledge itself.

This week we’re covering this new paradigm and learning how to learn.

Let's get started

From Scarcity to Overload to Synthesis

For most of human history, information was scarce and precious. Books were rare, education was limited, and expertise was locked behind years of dedicated study. The industrial age began to change this with mass printing and public education, but the internet truly shattered the scarcity model.

I was extremely fortunate to be able to study my degree from this (rather lovely) room

But even then this model of memorising and consuming information seemed sort of…weird. Why did we need a special fancy building for this knowledge? Why was access restricted? Why was information not free?

The internet has changed this over the last couple of decades. It’s hard to overestimate its impact.

What followed was the era of information overload - where Google became our external brain. Need to know something? Just search for it! The problem shifted from "How do I find information?" to "How do I filter through all this noise?"

Increasingly the only reason to retain minutiae is for pub quizzes… there’s very little other reason to know all the FA Cup Winners of the past 50 years.

But now, we're entering a third era - the age of AI. The challenge isn't just finding or filtering information anymore. It's having machines that can analyse, combine, and transform raw information into personalised knowledge.

We have access to another brain. One that is (arguably) superior to our own.

This is fundamentally different from what came before

• In the scarcity era, we memorised because information access was limited

• In the overload era, we focused on search skills and critical evaluation

• In the AI era, we need to master the art of collaboration with AI systems that can process and connect information in ways we simply cannot

The Death of Memorisation and Search

This evolution has rendered many traditional learning approaches obsolete. Consider

• Rote memorisation of facts is increasingly pointless when AI can instantly recall any fact. This was possible with Google Search but even that pales.

• Simply collecting and cataloguing information (like saving articles to read later) adds little value when AI can summarise and synthesise on demand

• Even "knowing where to look" has less value when AI can search, filter, and organise information automatically

But if these traditional approaches to learning are dying, what replaces them?

The answer is learning how to direct the synthesis process, ask the right questions, and apply the resulting knowledge to real-world situations. In other words, we're moving from being knowledge collectors to knowledge conductors.

HOW to work alongside AI is the skill moving forward.

This shift means that your relationship with learning is fundamentally changing. Here's what the new paradigm looks like:

1. From passive consumption to active direction: Instead of just absorbing information, you need to actively direct the AI synthesis process.

2. From memory to connectivity: The valuable skill isn't memorising isolated facts but understanding how concepts connect across domains.

3. From solo learning to collaborative learning: You and AI form a learning partnership, each with different strengths.

4. From "just in case" to "just in time": The focus shifts from accumulating knowledge that might be useful someday to acquiring specific knowledge when you need it.

5. From information hoarding to action orientation: Knowledge becomes valuable primarily as fuel for action, not as something to possess.

This stuff is exciting. And scary. It’s one hell of a shift!

Learning Accelerated: The AI Advantage

The exciting part of this new paradigm is that it can dramatically accelerate the learning process. When used effectively, AI can help you:

• Identify the most relevant information in any domain

• Customise explanations to your specific background and learning style

• Make connections between concepts that might otherwise remain hidden

• Test your understanding through dynamic questioning

• Adapt to your pace and fill gaps in your knowledge as they appear

This isn't just marginally faster learning - it's the possibility of an order of magnitude improvement in how quickly you can gain useful knowledge in any domain.

This will be the plan in this Playbook - building our a personalised AI tutor for you to learn any subject. A tutor that understands where you are, what you want to learn and how to get you there.

What's Next?

This shift in how we relate to knowledge requires a new systematic approach to learning - one that leverages AI as a partner rather than just a tool. Over this week, we'll build a complete methodology for AI-assisted learning:

Part 1: The New Learning Paradigm - Today we've explored how AI fundamentally changes our relationship with knowledge acquisition and why we need new approaches to learning.

Part 2: Setting Up Your Personal AI Tutor - Tomorrow we'll create a specific prompt template for configuring an AI to serve as your personal tutor, customised to your learning style and goals.

Part 3: Structured Learning Sessions - We'll dive into the optimal structure for learning sessions, including active engagement strategies to maximise retention.

Part 4: Active Recall & Reinforcement - You'll learn strategies for ensuring knowledge sticks, including spaced repetition and project-based knowledge management.

Part 5: Cement Learning Through Teaching & Application - Finally, we'll explore how teaching concepts back (including on camera, you know me!) and applying knowledge through time-boxed projects solidifies learning.

By the end of this series, you'll have a complete system for using AI to learn any subject more effectively than traditional methods could ever achieve.

Keep Prompting,

Kyle