Learn how to design smarter, effective AI agents using the 6 essential context types: Instructions, Memory, Tools & more
InstructorVivian AranhaComidoc has tracked 35 coupons for this course since 2025, last checked 2d ago. On average, a new coupon appears roughly every 10 days.
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The curriculum organizes agent design into distinct categories including instructional requirements, memory patterns (short-term and long-term), and tool integration via function calling.
Some learners find the explanations easy to understand, noting that a slower pace can aid in grasping foundational concepts.
Editorial course preview
These 2 complementary views highlight concrete, legible examples from the course presentation.
This course outline details key learning objectives for designing intelligent AI agents, including prompt engineering, memory architecture, and tool integration.
The main title slide introduces the course topic of mastering context design for intelligent AI agents, featuring a subtitle about designing smarter and more effective systems.
Learner signals suggest a deficiency in concrete code samples, screenshots, or full prompt examples necessary for practical application.
The practical examples provided may feel too basic for those seeking real-world agentic workflows with models like Claude or Gemini.
The curriculum aligns with the stated goals for developers and product managers interested in agent architecture.