Master the AI tools
reshaping software development.

AI coding agents are changing how we build—but only if you understand how they work. Learn MCP (the USB-C for AI) and Agent Teams (parallel AI collaboration) through interactive concept cards, diagrams, and hands-on challenges.

Start with MCP FundamentalsExplore Agent Teams
Join 2,100+ developers mastering the tools that matter.
AI in a Shell
The Blind Spot

Using AI tools without understanding the architecture is a liability.

Anyone can generate code. We ensure you understand the systems you're building—so when MCP connections fail or agent teams conflict, you know exactly why.

Master Model Context Protocol and Agent Teams through hands-on concept cards, interactive diagrams, and Socratic challenges that build real competence.

Master modern stacks like RAG, prompt engineering, MCP, LLM full-stack patterns, structured outputs, and more through hands-on Socratic learning.

Synapse AI · ChatGPT course

An Expert that
pushes back.

Watch Synapse vet a curriculum. It doesn't just nod along. It challenges the scope, suggests tradeoffs, and ensures the plan is viable before a single line of code is written.

The AI tutor proposes the curriculum track and milestones.
You approve, redirect, and nudge scope just like a tech lead.
Every exchange is logged as a clear chat between tutor and developer.
Developer working with the AI tutor
Synapse
AI tutor

ChatGPT course · broadcast lesson

Now, let's focus on the magic.

This HTML file is totally self-contained. There's no fetch() call to our server.

Think of this web component like a satellite dish. It can't make its own shows; it can only display what's being broadcast to it.

In this case, the "broadcast" comes from ChatGPT via a special JavaScript object: window.openai.

Take a look at the <script> tag. Where is the first place our code looks for the list of tasks provided by ChatGPT?

Developer

First place we pull tasks is the ChatGPT broadcast:

const tasks = [...(window.openai?.toolOutput?.tasks ?? [])];
AI challenges you ↘

How We Teach Complex AI Concepts

Concept cards, interactive diagrams, and Socratic questions—designed for developers who need to understand, not just copy-paste.

We do not spoon-feed answers.

Every concept card includes Socratic questions that force you to articulate your understanding—just like a senior engineer reviewing your design.

"Why does MCP use JSON-RPC instead of REST?"
"When would you choose stdio over HTTP transport?"
"Why not spawn 50 teammates for every task?"
Outcome: Defend decisions under pressure

Stop generating code you can't debug.

Vibe coding is powerful, but dangerous if you don't know the fundamentals. Synapse ensures you're the pilot, not the cargo.

Surface-Level
Blind AI Usage
High speed • Low control
Using MCP servers without understanding the protocol.
Spawning agent teams that conflict and overwrite each other.
Helpless when connections fail or teammates go rogue.
Copy-pasting code that breaks in production.
Recommended
AI-in-a-Shell Courses
Starting at 8,99 €
One-time purchase • Keep forever
Understanding MCP architecture before implementing servers.
Coordinating agent teams without conflicts or wasted tokens.
Debugging connection issues and teammate failures with confidence.
Production patterns for real-world AI integration.
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Questions we hear a lot

If you are wondering about something else, email hello@ai-in-a-shell.com.