{"id":13145,"date":"2026-08-10T10:55:15","date_gmt":"2026-08-10T10:55:15","guid":{"rendered":"https:\/\/nokobox.com\/index.php\/item\/udemy-game-development-and-llms-build-games-with-langchain-2025-10\/"},"modified":"2026-08-10T10:55:15","modified_gmt":"2026-08-10T10:55:15","slug":"udemy-game-development-and-llms-build-games-with-langchain-2025-10","status":"publish","type":"digital_item","link":"https:\/\/nokobox.com\/index.php\/item\/udemy-game-development-and-llms-build-games-with-langchain-2025-10\/","title":{"rendered":"Udemy \u2013 Game Development and LLMs: Build Games with LangChain 2025-10"},"content":{"rendered":"
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Descriptions<\/h2>\n

Game Development and LLMs: Build Games with LangChain, In this project-based course, you\u2019ll use LangChain and the OpenAI API to transform game ideas into intelligent, interactive experiences. We\u2019ll begin by establishing the fundamentals that make LLM systems predictable and cost-effective: prompt templates that separate content from structure, chains that combine multiple steps into reliable workflows, callbacks for tracing and telemetry, and memory strategies that keep context tight without increasing token costs. Once these building blocks are ready, you\u2019ll move on to RAG (Retrieval-Augmented Generation), enabling NPCs to answer questions and make decisions based on your own game lore and documents. You\u2019ll also create agents that safely call in-game tools through validated, schema-driven function calls and strict allowlists. Throughout the course, you\u2019ll instrument your code, test behaviors deterministically, and implement guardrails to ensure outputs stay on policy. The course concludes with two platformer mini-games in which an agent and NPCs compete, adapting strategies using memory and retrieval to outplay each other. By the end, you\u2019ll have a reusable toolkit\u2014prompts, chains, memory, RAG, and agents, along with portfolio-ready demos you can extend or deploy.<\/p>\n

What you\u2019ll learn<\/h3>\n