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Building AI Agents: Architecture Patterns, Tool Calling, and Memory Management
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Building AI Agents: Architecture Patterns, Tool Calling, and Memory Management

Learn how to build production-ready AI agents by mastering tool calling contracts, structuring agent loops correctly, and separating memory into session, knowledge, and execution layers. Includes working Python code examples.

· 5 min read
AI Agents: What They Actually Do and Why Production Matters
Learning Lab

AI Agents: What They Actually Do and Why Production Matters

AI agents observe, decide, and act in loops — then repeat based on what happened. Learn what makes them different from prompts, why they work better on complex tasks, and how to build one that doesn't loop infinitely.

· 5 min read
Building AI Agents: The Three Patterns That Actually Work
Learning Lab

Building AI Agents: The Three Patterns That Actually Work

Three architecture patterns for AI agents, from simple tool routing to agentic loops. Learn how to structure tool calling, set memory limits, and avoid the most common failure modes—with working code.

· 5 min read
Building AI Agents: Tool Calling, Memory, and Loop Patterns
Learning Lab

Building AI Agents: Tool Calling, Memory, and Loop Patterns

AI agents are loops, not chatbots. Learn the core architecture pattern, how tool calling works, memory management strategies, and the code shape that actually handles failures in production.

· 5 min read
AI Agents Explained: From Chatbots to Autonomous Systems
Learning Lab

AI Agents Explained: From Chatbots to Autonomous Systems

AI agents aren't chatbots. They perceive, decide, act, and adjust — solving multi-step problems without human intervention. Learn what changed in 2025-2026, why they matter, and how to build one today.

· 6 min read

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