Day 10: Learn SWE fundamentals for AI

Day 10: SWE fundamentals 101

👋 Welcome to Lesson 10 of the 14-Day Course. So far, you’ve explored how to build agents in notebooks. But to ship real apps? You need to think beyond the demos and start learning about SWE fundamentals.

What we will cover today:

• Stop using Jupyter Notebooks

• Moving away from ML to SWE in 2025

• How to unlock new roles in AI?

• What does “full-stack” actually mean?

• Main Components of AI Applications

📌 Missed a lesson? Catch up here:

 👉 Day 1: Intro to Agents 
👉 Day 2: Agents vs Workflows 
👉 Day 3: RAG and Tool Use 
👉 Day 4: Memory 
👉 Day 5: Evals for Agents 
👉 Day 6: Context for Agents 
👉 Day 7: Multi-Agents (MAS) 
👉 Day 8: Setup Git and Github 
👉 Day 9: AI assisted coding 
 

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Our next AI Engineering Bootcamp starts on June 12th! Limited spots available. Reserve now!

1. Stop using Jupyter Notebooks

Let’s be honest, most AI tutorials you see on Linkedin, Youtube or Twitter will only teach you how to:

• run demo code locally in a Colab notebook

• make a single API call to OpenAI

• and print the output

🫠 That’s not how production apps are built.

If you want to break into AI engineering, you need to understand how to wrap a complex backend logic, connect it to a frontend, and let real users interact with it, which is an entirely different philosophy altogether.

2. What does the industry want now?

There’s a shift happening in the industry.

Since the release of ChatGPT in 2022:

• We’re moving away from Jupyter notebooks, which focused on Machine Learning.

• Toward full-stack AI engineering, which focuses on the Product first.

Why?

Because most companies no longer need custom models, they need custom AI applications.

And AI applications today are real products, not experiments. That means:

• You need structured codebases, not single-file notebooks

• You need frontend+backend integration, not just Python scripts

• You need APIs and a database connections, not just streamlit demos

This is why we’ve embraced Next.js + Vercel AI SDK + Supabase + TypeScript as the default stack in our AI Engineering bootcamp. (Python track is also available with FastAPI)

As you see from the graph above, this shift is why so many companies are hiring AI engineers, not ML engineers.

3. So, what is full-stack AI Engineering?

Full-stack engineering means you can build an entire application end-to-end, from the user interface to the backend logic and database.

Imagine this:

That’s full-stack in action.
And you can build this entire flow without a CS degree.

See basic example of an application data flow:

In simpler terms, a full-stack engineer understands:

🖼 Frontend (Client-side)
What the user sees and interacts with: UI, buttons, forms, dashboards, etc.
Built with tools like React, ShadCN, HTML/CSS, and Tailwind.

⚙️ Backend (Server-side)
What happens behind the scenes: APIs, authentication, logic, and model calls.
Commonly built with FastAPI, Node.js, or Next.js API routes.

🗄 Database Layer
Where data gets stored, like user activity, user profiles, or chat logs.
Built with tools like Supabase, Postgres, MongoDB, etc.

🚀 Deployment
Where your app leaves your local machine and is hosted on the cloud.
Handled by tools like Vercel, FastAPI Cloud, or Docker + AWS.

P.S. If you want to learn this tech stack, reserve your spot in the next cohort while tickets last! Deadline June 12th, 2025.

4. Don’t limit yourself

Once you understand how full-stack works, you will unlock more real-world opportunities:

• You stop thinking like a “prompt engineer.”

• You start thinking like a product engineer.

• Most importantly, you will build apps that solve real problems that users are ready to pay for.

Unfortunately, not everyone succeeds, but if you build complete end-to-end projects for your capstone, you can target roles like these: (1), (2), (3), and more!

Or start an entirely new business with AI, just like Autumn did. Watch how she transformed her life in 5 weeks, with no prior SWE background.

🎉 Congratulations!

You made it to Day 10! Tomorrow, you will learn how to deploy your full-stack AI applications according to industry standards.

🚨 PSA for the bootcamp.
There are only 10 Spots Left.

Since yesterday’s email, five seats have already been taken.

That leaves just 10 seats at the lowest price for international learners for the upcoming AI Engineering Bootcamp at $1,575 (normally $2,100)

⏳ Offer expires in 48 hours.

Once these 10 spots are gone, the price jumps, no exceptions, no extensions. You’re getting early access before this goes public tomorrow!

👉 [Secure Your Spot Now] 
🎟 Use code “TIER1” for $525 off

Let’s build full-stack AI together!

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