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5 in-depth free course articles on setup, real workflows, and production patterns — written for builders shipping with AI.
Your agents work on your laptop. Now what? This final guide covers everything you need to ship agents that run reliably in production: Docker containerisation, VPS vs serverless, structured logging, health checks, cost controls, and the monitoring setup that wakes you up before your users notice something broke.
In Part 1 you built the loop. Now give it real tools: web search, code execution, and file writing - plus the error recovery patterns that separate demo agents from production ones. Copy-paste Python, no frameworks.
Most tutorials start with code. This one starts with the right mental model. Learn exactly what an AI agent is (and isn't), how it differs from a chatbot, and the four components every agent needs - with Python examples you can run today.
Your agent forgets everything the moment a session ends. This guide covers the three memory patterns every AI agent builder needs: in-context, external file, and vector database - with Python code for each.
Your single agent can now use tools and remember things. But one agent has a ceiling. This guide covers the three orchestration patterns that scale agents from demo to real work: pipeline, supervisor/worker, and fan-out. Python code for each.