They're like riding a bike: easy, and you don't get it until you try.

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Building LLM agents is surprisingly simple and accessible. Using just the OpenAI API and basic Python, developers can create functional agents with tool-calling capabilities in under 50 lines of code. The post walks through implementing a working agent from scratch, demonstrating context management, tool integration, and multi-turn conversations. It argues that understanding agents requires hands-on experience, challenges the necessity of frameworks like MCP, and explores open engineering problems around context engineering, token allocation, and balancing determinism with agent autonomy.

You Should Write An Agent