AI & Agents

Concepts, patterns, and techniques for building and working with AI systems — from prompt design to autonomous agent architectures.

Entries

• Prompt Engineering — Crafting effective inputs for language models
• Agent Patterns — Architectural patterns for autonomous AI systems
• Context Windows — Managing the finite memory of language models
• Chain-of-Thought — Eliciting step-by-step reasoning from LLMs
• Tool Use — Extending AI capabilities through external tool integration
• Evaluation Frameworks — Measuring AI system performance and reliability
• Function Calling — Structured tool invocation by language models
• Grounding — Connecting model outputs to verifiable sources
• Hallucination Mitigation — Reducing fabricated or incorrect model outputs
• Multi-Agent Systems — Coordinating multiple AI agents for complex tasks

Related Domains

• Machine Learning — Foundational algorithms and training techniques
• Architecture — System design patterns applicable to AI systems