AI Agent Ecosystems

researched 2026-05-25· 22 sources · 10 concepts · skill agent-ecosystem

Comprehensive reference for AI agent development, orchestration, infrastructure, and security.

Agent Ecosystem Expert

Comprehensive reference for AI agent development, orchestration, infrastructure, and security. [source]

Defense-in-depth

Input validation - Filter and sanitize all external content [source]
Sandboxed tool execution - MicroVMs, gVisor, or container isolation [source]
Context-layer governance - Least privilege [source]
Runtime guardrails - LlamaFirewall (Meta, open-source) [source]

Cost optimization

LLM API calls account for 70–85% of total agent operating costs. Key strategies: [source]
Model routing (saves 40–75%): Route each step to the cheapest model that meets quality. [source]
Prompt caching (saves 45–80%) [source]
Context management (saves ~72%) [source]
Token budgets: Per-request max_tokens, per-task budgets, per-day/month caps. [source]

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