Fundamentals of Building Autonomous LLM Agents

Description

In this video, I review "Fundamentals of Building Autonomous LLM Agents" and turn it into a practical blueprint for agentic LLMs, covering agent architecture, perception, reasoning system, memory module, execution, and multi-agent orchestration. You'll learn when to use chain-of-thought, self-consistency, and tree-of-thought, how to structure decomposition–plan–parallel–merge workflows, and how to harden tool use, code generation, and GUI automation with validation and reflection. If you're building agent architecture for agentic LLMs, this walkthrough shows how to connect a robust reasoning system and memory module to reliable execution, and why multi-agent patterns improve resilience. Keywords: agentic LLMs, agent architecture, reasoning system, memory module, multi-agent. Agentic LLMs and agent architecture are emphasized throughout to maximize practical relevance. Subscribe for new AI builds → https://www.youtube.com/@GiveMeTheMic22?sub_confirmation=1 All my links, resources, and starter kits → https://m-sml.mtrbio.com/public/smartlink/givemethemic — LINKS FROM THIS VIDEO — 🤖 Get Your GiveAway Here → https://airtable.com/appYhFgDpOECPnPEl/pagcdZ3v31fLhTWoR/form 🤖 Paper → https://arxiv.org/pdf/2510.09244 — CHAPTERS — 00:00 Introduction & why this paper matters 01:12 Paper overview: Fundamentals of Building Autonomous LLM Agents 02:43 Vibe coding vision and early-stage AI (new species analogy) 05:03 Research objectives: perception, reasoning, memory, execution 07:24 Key challenges in agentic LLMs (GUI grounding, loops, adaptability, performance gap) 12:01 Primer: LLMs vs LLM agents, transformers, workflows vs agents 13:21 Agent architecture and building blocks overview 14:01 Perception system fundamentals (multimodal sensing) 16:18 Core systems overview: reasoning, memory, and action 19:29 Proposed agent architecture diagram 20:30 Perception architecture and pitfalls (encoders, projectors, latency, context limits) 26:11 Reasoning frameworks and techniques (planning, CoT, ToT) 31:12 Reflection and self-evaluation systems; multi-agent orchestration 34:26 Execution system: tools, APIs, UI automation, robotics 35:02 Conclusion and next — ABOUT THE CHANNEL — I’m Samer, a Fortune 500 exec turned AI educator. I publish AI educational, and practical tutorials, so you can learn, ship, and scale, even without a tech background. — CONNECT — Website → https://givemethemicofficial.com/ LinkedIn → https://www.linkedin.com/in/samerkhaddad/ X → https://twitter.com/@ai_samerhaddad Instagram → https://www.instagram.com/ai_samerhaddad TikTok → https://www.tiktok.com/@ai_samerhaddad — HASHTAGS — #GiveMeTheMic #agenticLLMs #agentarchitecture #reasoningsystem #memorymodule #multiagent #LLMagents #RAG #multimodal #tooluse #AIengineering — FILENAME — FileName: GMTM2