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​Build AI Agents with Langbase

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Learn to build AI agents with Langbase. We just posted a course on the freeCodeCamp.org YouTube channel that will teach you how to create context-engineered agents that use memory and AI primitives to take action and deliver accurate, production-read… 

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Learn to build AI agents with Langbase.

We just posted a course on the freeCodeCamp.org YouTube channel that will teach you how to create context-engineered agents that use memory and AI primitives to take action and deliver accurate, production-ready results using Langbase.

Langbase is a powerful serverless AI cloud for building and deploying AI agents. A great alternative to bloated frameworks, Langbase gives you simple AI primitives including Pipes, Memory (RAG), Workflows, and Tools, allowing you to easily build, deploy, and scale serverless AI agents.

Context-engineered agents are AI agents powered by LLMs and enhanced with tools and long-term memory (Agentic RAG). Instead of only responding to prompts, they can also:

  • Retrieve knowledge from documents and data.

  • Take real-world actions with tools.

  • Maintain workflows and context across conversations.

In this course, you’ll:

  • Create your first Agentic RAG system using Langbase Pipes and memory agents.

  • Deploy and scale serverless agents in Langbase Studio.

  • Vibe code AI agents using Command.new.

The course covers cover:

  • Explaining context engineering and the agentic RAG pipeline.

  • Building memory agents.

  • Using Langbase AI primitives including Workflow, Parser, Chunker, Embed, and Memory to build any type of AI agent.

  • Deploying and scale serverless AI agents without frameworks.

Watch the full course on the freeCodeCamp.org YouTube channel (1-hour watch).