AI Agents Explained - How They Actually Work

How AI agents can search, code, debug, and fix — all without you touching the keyboard? It's not a smarter AI. It's the same language model with different scaffolding. In this video, I break down exactly what's happening inside AI agents — the loop, the tool calls, the memory systems, and where it all falls apart. What you'll learn: → The ReAct pattern that powers virtually every agent framework → How tool calling actually works (model proposes, your code executes) → Why agents forget and how memory systems solve it → Common failure modes you'll hit if you build with agents → A mental model you can use to understand any agent system This isn't about any specific product — it's the architecture beneath all of them. Whether you're evaluating agent tools, building your own, or just curious how the trick works — this explanation can help. 🕐 TIMESTAMPS 0:00 - Intro 0:36 - The Core Analogy 1:48 - The Agent Loop Explained 3:15 - Tool Calling Mechanics 4:44 - Memory: Why Agents Forget 6:42 - Where Agents Fail (6 Common Issues) 8:06 - Key Takeaways 8:51 - Outro SOURCES • ReAct Paper (Yao et al., 2022): arxiv.org/abs/2210.03629 • Mem0 Research (Chhikara et al., 2025): arxiv.org/abs/2504.19413 More Videos : AI - https://www.youtube.com/playlist?list=PLWP-VtjCVpWzpsPL0Knxrb-m70KxiDGwR Software Egineering Basics - https://www.youtube.com/playlist?list=PLWP-VtjCVpWyLNBm3zz_sGyC5mVwiAOvj Software Design - https://www.youtube.com/playlist?list=PLWP-VtjCVpWx7kPq30XRN6O6LjVQ4VL95 #AIAgents #LLM #MachineLearning #Programming #AIExplained #SoftwareEngineering #TechEducation