AI Agent Architecture: Reasoning, Memory, and LangGraph

Board Infinity follows an agent from architecture foundations into structure, memory and persistence. A research-assistant project provides the final evaluation setting. This intermediate course is useful when the next question is how an agent maintains state and how its behavior can be checked.

What you will learn

• Organize a structured agent workflow.
• Explain memory and persistence responsibilities.
• Evaluate a research-assistant agent against a defined task.

Who this suits

Learners with basic Python and familiarity with language models or generative AI. Earlier framework experience is unnecessary.

Before you enroll

Those foundations are recommended. Check the current LangGraph APIs and model-access requirements, and examine whether saved state contains information that should not persist.

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Put it into practice

Build a small research workflow over public documents. Test a restart from saved state and a question with no supported answer in the sources.

Source and review

This overview is based on the provider's published information, checked on 12 October 2026. It is an editorial assessment, not a claim that we completed the resource. Time filters are approximate study ranges; projects and exercises can take longer.

View the curriculum and current access options at Coursera.

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