AAIDC Core Components Test Your Understanding
About this lesson
In this video, we break down some of the most misunderstood concepts in agentic AI systems — memory, reasoning, and autonomy and clarify what’s actually happening under the hood. You’ll learn why “memory” in AI agents is not what it sounds like, how context is managed externally rather than learned internally, and why so-called reasoning and decision-making are better understood as carefully designed behaviors rather than true intelligence. We also explore an important question: who is really making decisions in agentic systems — the agent, or the designer? Timestamps: 0:00 - Introduction to core components of agentic AI 0:08 - Why “memory” is a misleading term 0:41 - Memory as managed and persisted context 1:17 - Is there real reasoning or planning in AI agents? 2:12 - Autonomy: who is really making decisions? 3:02 - Bias, fairness, and designer responsibility Watch this video if you’re building agentic AI systems or trying to understand what autonomy really means in production AI applications. This video is part of the Agentic AI Essentials Certification Program by Ready Tensor. Enroll Now: https://www.readytensor.ai/agentic-ai-essentials-cert/ About Ready Tensor: Ready Tensor helps AI and ML professionals build, evaluate, and showcase real-world agentic AI systems through hands-on certifications, competitions, and project-based learning. Learn more: https://www.readytensor.ai/ Like the video? Subscribe for more deep dives into agentic AI system design, architecture, and production best practices.
DeepCamp AI