# AI Agents and Patterns Hub > [!Note] > Sub-hub for the model-side and pattern-side of AI agents — what an > agent is, the prompting techniques that drive it, the loops that make > it autonomous, and the retrieval systems that ground it. ## 1. The agent itself - [[AI Agent]] - [[Agentic Loop]] - [[Ralph Loop]] - [[Multi-Agent System]] - [[Orchestrator-Subagent Pattern]] - [[Subagent Context Isolation]] - [[Compressed Summary Return]] - [[Ephemeral Subagent]] --- ## 2. Driving the model - [[Prompt Engineering]] - [[System Prompt]] - [[In-Context Learning]] - [[Chain-of-Thought]] - [[Self-Consistency]] - [[Tree of Thought]] - [[Reasoning Model]] --- ## 3. Action and reasoning patterns - [[Tool Use]] - [[Function Calling]] - [[Tool Taxonomy]] - [[Tool Schema Is the Prompt]] - [[Native vs Semantic Function]] - [[Structured Outputs]] - [[ReAct Pattern]] - [[Agent Planning]] - [[Prompt Chaining]] - [[Reflection]] - [[Agentic Feedback Taxonomy]] - [[Optimise Turns Before Tier]] --- ## 4. Retrieval and grounding - [[Retrieval-Augmented Generation]] - [[Vector Database]] - [[Semantic Search]] - [[Embedding-Based Retrieval]] - [[Term-Based Retrieval]] - [[Hybrid Search]] - [[RAG Chunking Strategy]] - [[Query Rewriting]] - [[Contextual Retrieval]] --- ## 5. Threats and failure modes - [[Prompt Injection]] - [[Hallucination]] - [[Agent Failure Modes]] - [[Compounding Error]] --- ## 6. Anchor sources - [[Chain-of-Thought Prompting (Wei et al.)]] - [[ReAct (Yao et al.)]] - [[Retrieval-Augmented Generation (Lewis et al.)]] - [[Building Effective AI Agents]] - [[Multi-Agent AI Systems in 2026 (FlowHunt)]] - [[The Architecture of Scale - Anthropic Sub-Agents (Oswal)]] - [[AI Agents in Action - Micheal Lanham]] - [[AI Engineering - Chip Huyen]] --- ## Up - [[0 - Modern AI Software Engineering Hub]]