Hands On AI Agent Mastery Course
AI RoadmapLearning Outcomes Built 15+ production-ready agents with proper error handling and monitoring Implemented scalable architectures handling concurrent requests and resource management Deployed agent systems with CI/CD pipeline
| Platform |  | Pricing | Freemium | Publishes | Daily |
|---|---|---|---|---|---|
| Issues | 145 | Founded | a year ago | Last Issue | 41 hours ago |
| Active | |||||
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Lesson 9 — ReAct Loop
Introduction
Introduction
Lesson 8 — Multi-Agent Orchestration
Introduction
Introduction
Lesson 7 — Sandboxed Code Execution
Introduction
This lesson isolates untrusted Python before it can touch the host. AI agents often emit runnable snippets; executing them raw is unsafe. A child process, blocked imports, and timeouts form a minimal sandbox. Outcomes fee...
Lesson 6 — Observability Stack
Introduction
This lesson adds observability to an AI service. Requests emit JSON and contribute latency measurements. RED metrics turn runtime behavior into operational signals. A dashboard presents percentiles, throughput, failures,...
Lesson 5 — Security Hardening
Introduction
This lesson adds an output-side security layer to the AI service. It scans generated text for leaked secrets and PII before responses leave the system, and signs payloads with HMAC so integrity can be verified downstream....
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AI Agent Roadmap — a structured, hands-on path from LLM fundamentals to deploying production-grade multi-agent systems. Most engineers know AI Agents are coming. Fewer know how to actually build them.
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