Agentic AI - Episode 03 - How Agents Think ?

🧠 Inside the agent's mind — the implementation layer most builders miss.
In Episode 3 of the WealthWise AI Agentic AI Deep Dive series, we go beyond platforms and patterns to the implementation details that determine whether an agent actually works in production.
What we cover:
• Short-term memory: context windows, their limits, and why they cause most production failures
• Long-term memory: vector databases, embeddings, and RAG (Retrieval Augmented Generation)
• System prompt engineering: the 6-component framework for production-grade prompts
• Tool design: 5 principles for AI-reliable tools that don't hallucinate or cascade-fail
• ReAct prompting: chain-of-thought reasoning inside agents
• Planner vs Executor: the architecture pattern that handles complex multi-step workflows
• A complete production agent architecture — put it all together

⏱ TIMESTAMPS
00:00 — Cold Open
01:30 — Episode 2 Recap
04:00 — Episode 3 Overview
05:30 — PART 1: Short-Term Memory and Context Windows
08:30 — PART 2: Vector Databases and Long-Term Memory
12:00 — PART 3: System Prompt Engineering
15:30 — PART 4: Tool Design Principles
18:30 — PART 5: ReAct Prompting and Chain-of-Thought
21:00 — PART 6: Planner vs Executor Pattern
23:30 — PART 7: Complete Production Architecture
25:30 — Episode 4 Preview: Financial Trading Agents
26:30 — Subscribe and Like
27:30 — Audience Challenge + Close

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Видео Agentic AI - Episode 03 - How Agents Think ? канала WealthWise AI