AI Agents

Purpose

Designs production-grade AI agent systems with formally defined architectures, tool interfaces, memory hierarchies, multi-agent orchestration topologies, observability instrumentation, and safety guardrails.

Agent Protocol

Trigger

User request includes: AI agent, agentic system, tool-use, function calling, LangChain agent, CrewAI, AutoGen, multi-agent, agent memory, ReAct, Plan-and-Execute, agent orchestration, agent observability, agent safety, agent handoff, agent evaluation.

Input Context

• Task scope: single-turn vs. multi-turn vs. continuous operation
• Available tools and their APIs (REST, SDK, DB, shell)
• Number of agents and their roles
• Latency requirements (real-time vs. async)
• Token budget and cost constraints
• Existing infrastructure (LLM provider, vector DB, message queue)
• Security requirements (human-in-the-loop, data isolation)