Foundations
Agentic vs Chat
Chatbots respond to individual messages in a turn-by-turn exchange, while agentic systems take autonomous actions across multiple steps, using tools and making decisions in a loop without waiting for human input at each turn. The key distinction is agency: an agent decides what to do next, executes that action, observes the result, and iterates until it reaches a goal or determines it needs human guidance. This shift from reactive conversation to goal-directed task execution is what makes agentic coding fundamentally different from a basic chat interface, and recognizing the boundary tells you when agent patterns are worth the added complexity versus when a simpler chat-based approach is the right tool.
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resources
Building Effective Agentsanthropic.comAnthropic's research paper defining agentic systems and their design patterns (anthropic.com)LLM Powered Autonomous Agentslilianweng.github.ioLilian Weng's comprehensive overview of LLM-powered autonomous agents (lilianweng.github.io)Agentic Design Patternsdeeplearning.aiAndrew Ng's breakdown of the four major agentic design patterns (deeplearning.ai)What Are AI Agents?cloud.google.comGoogle Cloud's explanation of AI agents and how they differ from traditional chatbots (cloud.google.com)