Where senior engineers learn to build with AI — at the depth the job actually demands.
Agent Mesh vs Supervisor: What Holds Up in Production
Open agent meshes lost to bounded supervisor patterns in 2026 production data — the failure surface grows as agent-pairs, not agents, and the token bill grows with it. Here's the data, why Gartner's "context mesh" is a different idea entirely, and the narrow cases where a controlled mesh still wins.
Two Python-agent series. They’re not a choice — they’re a sequence.
Start with Foundations if you’re new — build an agent by hand, no framework. Move to Production once the basics click. Pick by where you are right now.
AI Agents from Scratch in Python
Build a working agent with nothing but Python and one LLM call — no frameworks, so you actually understand the loop.
- Length
- 6 parts (00–05)
- Approach
- Pure Python + a raw LLM call
- Prereq
- Can read basic Python (Part 0 teaches it)
- You'll build
- Your own agent loop — tools, reasoning, memory — by hand
Agentic AI in Python: Zero to Production
Take a real agent all the way to a deployed, observable service using LangGraph — state, tools, memory, and shipping.
- Length
- 7 parts (01–07)
- Approach
- LangGraph + deploy & observability
- Prereq
- Comfortable with agent fundamentals
- You'll build
- A real agentic app, deployed as an observable service
Build it, in real Python
Tools worth your time
Design systems that hold up
Grow in the AI era
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