Strategy - Julien cole

 Good strategy is NOT about what people want.

Here’s what you’re missing;
Want ≠ Insight.
Most strategists stop way too early.

They uncover the want and think that’s the strategy.

Example for Burger King;
⭕ Want: They want quick, delicious flame-grilled burgers.

BUT that’s not the hard part.

Finding the consumer problem is the real work.

It’s that consumers see fast food as fake food.

With the insight that more Burger King restaurants have burned down than any other chain in the last 50 years,

Is proof that they use actual flames when cooking their burgers.

So people can associate Burger King with real cooking.

👉I’ll show you how to write a strategy on a page with more examples at a free workshop.

It’ll be recorded if you can’t make it live.

Seats are limited! Sign Up Here: https://lnkd.in/g58FYFSn

Acourses for Claude

 🚨 IN 2026, AI COURSES AREN’T THE ADVANTAGE.

Execution is.
Most people are “learning AI.”
Very few are redesigning how work gets done with it.

That’s the real gap.

And it’s why most AI learners stay exactly where they started.

🎯 This is the hidden failure point:

Not access.
Not intelligence.
Passive consumption.

Here’s the AI learning stack that actually builds leverage 👇

🧠 1. Foundations & Fluency → Understanding systems

Courses:
• Claude 101
https://lnkd.in/gCPUQsRg

• AI Fluency: Frameworks & Foundations
https://lnkd.in/gS6ceZ_M

Signal:
You want to understand how AI actually works, not just prompt it.

Use for:
• AI fundamentals
• Context engineering
• Workflow thinking

🤖 2. Agents & MCP → Workflow orchestration

Courses:
• Introduction to Agent Skills
https://lnkd.in/g_wWNiEb

• Introduction to Model Context Protocol
https://lnkd.in/gAj5HqMY

• MCP: Advanced Topics
https://lnkd.in/g3eDwBFY

Signal:
You want AI to execute workflows, not just answer questions.

Use for:
• Agent systems
• Multi-step automation
• AI orchestration

💻 3. Building & APIs → Turning ideas into systems

Courses:
• Building with the Claude API
https://lnkd.in/gDr5K_B4

• Claude Code in Action
https://lnkd.in/g9wWZbK9

Signal:
You want reusable systems, not one-time outputs.

Use for:
• Internal tools
• AI products
• Automation layers

🏢 4. Enterprise AI → Scaling safely

Courses:
• Claude with Amazon Bedrock
https://lnkd.in/gbfPjSFt

• Claude with Google Vertex AI
https://lnkd.in/gvVgB4Ub

Signal:
AI needs governance, deployment, and control.

Use for:
• Enterprise AI rollout
• Infrastructure decisions
• Production environments

🎓 5. AI Across Industries → Adapting context

Courses:
• AI Fluency for Students
https://lnkd.in/gKKujHGG

• AI Fluency for Educators
https://lnkd.in/gVcKnuhA

• Teaching AI Fluency
https://lnkd.in/g9P4gJFM

• AI Fluency for Nonprofits
https://lnkd.in/gpsm_BVf

Signal:
You want to understand how AI changes different environments.

Use for:
• Education
• Nonprofits
• Industry-specific workflows

💡 Before starting any AI course, ask this:

1️⃣ Will this change how I work tomorrow?
2️⃣ Am I building while learning?
3️⃣ Does this improve a workflow or just increase knowledge?
4️⃣ Can I apply this inside a real system?

Most people skip #2.

They consume information
Then never operationalize it.

⚙️ The real issue

This is the Execution Gap in AI learning.

The distance between:
• Watching AI content
and
• Building AI capability

And it’s where most people quietly stall.

Not because they lack intelligence.

Because they never apply enough to compound.

📈 The people accelerating fastest with AI aren’t learning more.

They’re applying faster.

Anything else is just digital note-taking.

💾 Save this as your AI execution roadmap

♻️ Repost to help someone stop consuming and start building
➕ Follow Sandeep Gulati🎯 for AI × Markeing × execution frameworks

👉 Join Proptifi.com for AI-powered home design ideas.

IC: Hruthik Varma.