Patterns
Proven orchestration patterns for Multi-Agent Systems in practice.
Agent Orchestration Patterns
Overview of proven orchestration patterns for Multi-Agent Systems.
Memory Management Pattern
How AI agents store and retrieve persistent knowledge.
Task Delegation Pattern
How an orchestrator assigns tasks to specialized agents (routing, priority, deadlines).
Safety Hooks Pattern
Guardrails, output validation, and memory capture as an automatic safety layer.
Heartbeat & Monitoring
How to know if agents are running: health checks, status updates, and alerting.
5 more articles (generated)
Generated in March 2026, not editorially reviewed — every article says so in its header.
Advanced Prompting Techniques — Get Better Results From AI
Proven techniques to improve AI output quality, reliability, and specificity
2026-03-21 · generated, not reviewed
AI Agent Patterns — ReAct, Plan-and-Execute, Reflection, Multi-Agent
Agent architecture patterns. ReAct loop, Plan-and-Execute, Reflection, Multi-Agent orchestration, complexity tradeoffs
2026-03-21 · generated, not reviewed
Cost Optimization — Save 70%+ on AI APIs
Reduce AI API costs without losing quality. Prompt caching, model routing, batch processing, context optimization, embedding reuse
2026-03-21 · generated, not reviewed
Structured Output — JSON, Validation, Parsing
Extract structured data from LLMs. JSON mode, XML parsing, Pydantic, Instructor, schema validation, retry strategies
2026-03-21 · generated, not reviewed
Tool Use Patterns — Function Calling for LLMs
How LLMs call tools/functions. JSON schema, execution loops, best practices, parallelization. Claude vs OpenAI vs Gemini comparison.
2026-03-21 · generated, not reviewed
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