🔶 Intermediate Level 3
🔶 INTERMEDIATE · LEVEL 3

Thinking Like a Strategist

Practical application of the 3 survival types, distinguishing dangerous vs. successful strategies, and mastering strategic thinking through case analysis.

📚
Lecture Slides
10
🕵️
Case Studies
5
📝
Test Questions
20
🎯
Passing Score
75+ pts

📋 What You Will Learn in This Level

1What is strategic thinking — Why is it important
2In-depth analysis of 3 survival types (AI User, Connector, Supervisor)
3Practical skills, tools, and career paths for each type
45 Dangerous strategies vs. 5 Successful strategies
55 Principles of strategic thinking — The strategist's mindset
6🕵️ Case Analysis — Choosing the best strategy in real situations
7My own AI strategy design framework
🔶 Intermediate Level 3
Slide 1 / 10
📖 Intro

Thinking Like a Strategist

Information overflows in the AI era. The problem isn't a lack of information, but missing opportunities due to an inability to make proper judgments and set priorities.

🧩 Strategist vs. Average Person
Average Person: "I feel like I should do something, but I don't know what" → Anxious but takes no action.

Strategist: "Analyze the current situation → Choose the best option → Execute immediately."
✅ 3 Core Elements of Strategic Thinking
① Reality Check — Accurately assess your current position (avoid both extreme optimism and extreme fear).
② Selection & Focus — You can't do everything. Do what's most important first.
③ Execution First — Fast execution + rapid correction is much more powerful than a perfect plan.
🎯 Goal of This Level

Develop the ability to choose the best strategy by applying the knowledge learned in Intermediate Levels 1 and 2 to real situations. This is the completion of the Intermediate stage and the gateway to Advanced.

👤 3 Survival Types

The 3 Survival Types — Overview

People who survive in the AI era fall broadly into 3 types. You can start as any type right now.

TypeCore RoleStrengthsTypical Revenue
① AI User Maximize productivity with AI Speed, efficiency, output Mass production of content/apps/services
② AI Connector Design AI + service automation System building, automation Automation solutions, SaaS, API
③ AI Supervisor Control AI design, ethics, & ops Trust, safety, providing direction Consulting, oversight roles, professional services
💡 Key Point

These three types are not mutually exclusive. The most realistic path is to start as an AI User and gradually expand your capabilities into a Connector and Supervisor.

👤 Type ①

AI User — "Make AI do the work"

⚡
TYPE 1 · AI USER
Someone who increases productivity 10-100x using AI
They don't just use AI as a simple tool, but utilize it like "100 employees." They single-handedly produce the output of an entire team. This type has the lowest barrier to entry and can be started right now.
AI Prompt Engineering Content Automation AI Code Generation Multimodal AI Usage
📌 Real-life Example:
Charlie (Neuroscientist) creates over 100 web apps by himself using ChatGPT. Achieving this level of output alone without a dev team is a classic AI User success model.

📌 Core Mindset: "I don't do it myself. AI creates the draft, and I set the direction."
👤 Type ②

AI Connector — "Combine AI to build automation"

🔗
TYPE 2 · AI CONNECTOR
Someone who links various AI, APIs, and services to build automation structures
Going beyond simply using AI, they connect multiple AI tools and services into a pipeline to build a system that runs automatically. This is a level higher than the AI User.
API Integration Workflow Automation No-code/Low-code Data Pipelines
📌 Real-life Example:
"Customer submits a form → AI auto-generates a custom reply → Auto-sends email → Auto-logs into CRM." Building such an automated pipeline is the job of an AI Connector.

📌 Core Mindset: "Everything I repeat can be automated. Build it once, and it runs continuously."
👤 Type ③

AI Supervisor — "Designs and takes responsibility for AI systems"

🛡️
TYPE 3 · AI SUPERVISOR
Someone who supervises the design, ethics, and operation of AI, bearing final responsibility
As AI systems spread, roles dedicated to supervising and taking responsibility for malfunctions, bias, and ethical issues become absolutely necessary. This requires the highest level of expertise but is the most stable and influential role.
AI Ethics & Policy Risk Management AI System Design Organizational AI Strategy
📌 Real-life Example:
Similar to when Amazon scrapped its AI hiring system after discovering gender bias, this role continuously inspects organizational AI systems to detect and correct bias, errors, and ethical issues.

📌 Core Mindset: "AI should never be left alone. There must be a human taking responsibility for all outcomes."
⚖️ Strategy Comparison

Dangerous vs. Successful Strategies — 5 Comparisons

Even with the same goal, the strategy you choose completely changes the outcome.

❌ Dangerous Strategies
  • Delaying start until it's perfect
  • Going all-in on one revenue channel
  • Viewing AI as a competitor or threat
  • Only continuing to build simple labor skills
  • Constantly changing direction to chase trends
  • Trying to do everything alone
  • Focusing only on short-term profits
✅ Successful Strategies
  • Starting fast even if only 70% ready
  • Diversifying revenue channels
  • Actively using AI as an employee/tool
  • Focusing on skills AI cannot replicate
  • Maintaining your own core direction
  • Delegating to AI to focus on strategy
  • Designing long-term revenue through systems
🔑 Core Strategy Principle

In the AI era, a fast cycle of "Execute → Feedback → Improve" is far more powerful than a "perfect plan." Those who start first get the data, and whoever has the data wins.

🧭 Strategy Principles

The Strategist's Mindset — 5 Principles

These are the core thought patterns shared by people who think strategically.

1
🎯 Clear Goal — "What is this strategy for?"
Strategy cannot exist without a goal. "I want to survive in the AI era" is too abstract. Set a specific goal first, like "Achieve $1,000/month in system revenue within 2 years."
2
🔍 Reality Check — "Where am I right now?"
Honestly evaluate your current skills, resources, and time. No exaggerating and no underestimating. You need a realistic starting point to create a realistic path.
3
⚡ Leverage — "What produces the biggest effect?"
Rather than doing 100 things a little bit, focus intensely on the 1 thing that yields a 10x effect. Choose the AI tool that provides the greatest leverage toward your goal.
4
🔄 Iterative Improvement — "Execute and look at the data"
A perfect plan doesn't exist. Run a cycle of fast execution, viewing real results (data), and making improvements. 10 fast iterations > 1 perfect attempt.
5
🛡️ Risk Management — "Prepare for the worst-case scenario"
Hope for success, but prepare for failure. Do not go all-in on one revenue channel; diversify. Maintain a structure you can recover from even if you fail.
🕵️ Case Studies

Real-life Situations, What is the best strategy?

Read each situation and choose the best strategy. After selecting, check the feedback to see why it's the best option!

🗺️ Strategy Design Framework

Designing My Own AI Strategy — 6-Step Framework

This is a step-by-step framework to design your own AI era survival strategy by integrating everything you've learned.

🔍
STEP 1
Diagnose Current Position
Honestly evaluate your job, skills, and income structure. "Am I currently a laborer or a system owner?" Determine if you are in a risk group or a safe group.
🎯
STEP 2
Select Target Type
Choose the most realistic type for you right now among AI User, Connector, and Supervisor. Starting as an AI User is usually the easiest.
⚡
STEP 3
Find Leverage Points
Find the 1 point where combining your existing skills + AI produces the biggest effect. Ex: Neuroscience knowledge + AI coding = Brain health app portfolio.
🚀
STEP 4
Define Minimum Execution Unit
Define the smallest execution you can do right now, not a "perfect start." Ex: Build 1 web app this week → Deploy → Get feedback.
📊
STEP 5
Set Revenue Structure Stages
Set a realistic timeline for Step 1 (Traffic/Ads) → Step 2 (Premium) → Step 3 (AI Features). Clarify which stage you are in right now.
🔄
STEP 6
Iterative Improvement Cycle
Execute → Check data → Improve → Re-execute. Measure results weekly and fine-tune your direction. In one year, you will be at a completely different level.
🏁 Intermediate Completion Message

Anyone who actually applies this framework is already an AI era strategist. The difference between knowing and doing is the difference in your outcome.

🔑 Core Keywords

Intermediate Level 3 Core Keywords

AI User
Increases productivity 10-100x with AI. Survival type ① with the lowest entry barrier.
AI Connector
Builds automated structures by combining AI, services, and APIs. Survival type ②.
AI Supervisor
Controls AI system design, ethics, & operations. The responsible entity. Survival type ③.
Leverage Point
The core point that produces the biggest effect compared to the investment. Standard for strategic focus.
Iterative Improvement Cycle
Execute → Feedback → Improve → Re-execute. A strategy more powerful than perfect planning.
Risk Diversification
Diversifying revenue channels to maintain a recoverable structure even if one fails.
✏️ Mini Quiz
Q1. Among the three survival types, which one has the "lowest entry barrier and can be started right now"?
Q2. What does the principle "Fast execution + feedback is more powerful than a perfect plan" emphasize?
✅ Test Readiness Checklist

Click to check the items once you understand them.

🔶 Intermediate Level 3
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