AI agent development workflow for building autonomous agents, multi-agent systems, and agent orchestration with CrewAI, LangGraph, and custom agents.

AI Agent Development Workflow Overview Specialized workflow for building AI agents including single autonomous agents, multi agent systems, agent orchestration, tool integration, and human in the loop patterns. When to Use This Workflow Use this workflow when: Building autonomous AI agents Creating multi agent systems Implementing agent orchestration Adding tool integration to agents Setting up agent memory Workflow Phases Phase 1: Agent Design Skills to Invoke ai agents architect Agent architecture autonomous agents Autonomous patterns Actions 1. Define agent purpose 2. Design agent capabilities 3. Plan tool integration 4. Design memory system 5. Define success metrics Copy Paste Prompts Phase 2: Single Agent Implementation Skills to Invoke autonomous agent patterns Agent patterns autonomous agents Autonomous agents Actions 1. Choose agent framework 2. Implement agent logic 3. Add tool integration 4. Configure memory 5. Test agent behavior Copy Paste Prompts Phase 3: Multi Agent System Skills to Invoke crewai CrewAI framework multi agent patterns Multi agent patterns Actions 1. Define agent roles 2. Set up agent communication 3. Configure orchestration 4. Implement task delegation 5. Test coordination Copy Paste Prompts Phase 4: Agent Orchestration Skills to Invoke langgraph LangGraph orchestration workflow orchestration patterns Orchestration Actions 1. Design workflow graph 2. Implement state management 3. Add conditional branches 4. Configure persistence 5. Test workflows Copy Paste Prompts Phase 5: Tool Integration Skills to Invoke agent tool builder Tool building tool design Tool design Actions 1. Identify tool needs 2. Design tool interfaces 3. Implement tools 4. Add error handling 5. Test tool usage Copy Paste Prompts Phase 6: Memory Systems Skills to Invoke agent memory systems Memory architecture conversation memory Conversation memory Actions 1. Design memory structure 2. Implement short term memory 3. Set up long term memory 4. Add entity memory 5. Test memory retrieval Copy Paste Prompts Phase 7: Evaluation Skills to Invoke agent evaluation Agent evaluation evaluation AI evaluation Actions 1. Define evaluation criteria 2. Create test scenarios 3. Measure agent performance 4. Test edge cases 5. Iterate improvements Copy Paste Prompts Agent Architecture Quality Gates [ ] Agent logic working [ ] Tools integrated [ ] Memory functional [ ] Orchestration tested [ ] Evaluation passing Related Workflow Bundles ai ml AI/ML development rag implementation RAG systems workflow automation Workflow patterns Limitations Use this skill only when the task clearly matches the scope described above. Do not treat the output as a substitute for environment specific validation, testing, or expert review. Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.

ai-agent-development