NirDiamant/agents-towards-production

End-to-end, code-first tutorials for building production-grade GenAI agents. From prototype to enterprise deployment.

Agents Towards Production is an open-source collection of hands-on tutorials for building AI agents that are ready for real-world use — not just demos. The project's goal is to help you take a generative-AI agent from a prototype to something you could actually deploy in a company.

What's inside:

  • 28 production-grade tutorials, each in its own folder with runnable notebooks or code files. Topics include stateful workflows, vector memory, real-time web search APIs, Docker deployment, FastAPI endpoints, security guardrails, GPU scaling, browser automation, fine-tuning, multi-agent coordination, observability, evaluation, and UI development.
  • Sponsor-contributed tutorials from companies like LangChain (agent framework), Redis (memory/vector database), Contextual AI (RAG), Bright Data (web data), Tavily (web search API), Arcade (secure tool calling), JetBrains (Kotlin AI framework), Mem0 (AI memory), RunPod (GPU cloud), and Inngest (durable execution).
  • A companion book — AI Agents Made Simple — a no-code decision guide with 28 chapters covering what each agent pattern does, what breaks, what it costs, and when it's overkill.

Beyond the tutorials:

  • A YouTube channel with short, one-idea-per-episode explainers (e.g., "AI Agents Are Just While Loops," "Context Is the New Code").
  • A newsletter (DiamantAI) with over 50,000 subscribers, offering early access and discounts on the author's books.
  • A Reddit community (r/EducationalAI) for discussing AI research and agent development.

The project is created by Nir Diamant, and the README encourages starring the repo to help others discover it.

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