AI Agent Architecture Explained: LLMs, Context & Tool Execution @DevOpsToolkit
AI Agent Architecture Explained: LLMs, Context & Tool Execution  @DevOpsToolkit
Uploaded November 2025 | Updated September 2026, 3 days ago
You type "Create a PostgreSQL database in AWS" into Claude Code or Cursor, and it just works. But how? Most people think the AI does everything, but that's wrong. The AI can't touch your files or run commands on its own. This video breaks down the real architecture behind AI coding agents, explaining the three key players that make it all work: you (providing intent), the agent (the orchestrator), and the LLM (the reasoning brain). Understanding this matters if you're using these tools every day.

We'll walk through increasingly sophisticated architectures, from basic system prompts to the complete agent loop that enables real work. You'll learn how tools get executed, what context really means, how the agent manages the loop between you and the LLM, and why the LLM is stateless. We'll also cover practical considerations like MCP (Model Context Protocol) for integrating external tools and context limits that affect performance. By the end, you'll understand that the agent is actually the only "dumb" actor in the system—it's pure execution with no intelligence. The LLM provides the brains, you provide the intent, and the agent coordinates everything to make it happen.

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Sponsor: RavenDB
🔗 ravendb.net
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#AIAgents #LLM #HowAIWorks

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▬▬▬▬▬▬ 🔗 Additional Info 🔗 ▬▬▬▬▬▬
➡ Transcript and commands: https://devopstoolkit.live/ai/ai-agent-architecture-explained-llms,-context--tool-execution

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▬▬▬▬▬▬ ⏱ Timecodes ⏱ ▬▬▬▬▬▬
00:00 AI Agents Explained
01:02 RavenDB (sponsor)
02:16 How Do Agents Work?
05:42 How AI Agent Loops Work?
09:36 MCP (Model Context Protocol) & Context Limits
11:38 AI Agents Explained: Key Takeaways
AI Agent Architecture Explained: LLMs, Context & Tool ExecutionWhy Your Platform Needs AI AgentsThe End of Static UIs: How LLMs Are Taking Over VisualizationI Built a Tool to Manage Multiple AI Agents at OnceDevOps Q&A: GitHub Actions Security, DB Migrations, CNIs, and Self-Hosted LLMsWhy Generic AI Tools Arent EnoughMiscellaneous - Feat. Dapr, KusionStack, and OpenFeature (You Choose!, Ch. 05, Ep. 06)The Mona Lisa Heist Explains AI SecurityDevOps AMA: AI Agents, External Secrets, and Career AdviceFrom Zero to Fully Operational Developer Platform in 5 Steps!DevOps Q&A: AI in Platform Engineering, Kubernetes Networking, and ObservabilityEp18 - Ask Me Anything About Anything with Scott Rosenberg and Jon Shanks
DevOps & AI Toolkit |

AI Agent Architecture Explained: LLMs, Context & Tool Execution

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