Stage 04 of 6 · The Closed Loop
Reason — Stateful orchestration, sub-agent decomposition and human-in-the-loop checkpoints.
Stage 04 of Implement Agentic's six-stage closed loop. Below: process, technologies, ecosystem partners, build-vs-buy guidance, project lifecycle and the benefits clients see.
Process
- Step 01
Model the workflow as an explicit state machine with checkpoints and retries.
- Step 02
Decompose into sub-agents with curated toolsets (≤10 tools each — bloated tool sets are the #1 failure mode).
- Step 03
Add human-in-the-loop gates wherever the action is irreversible (contracts, customer comms, production writes).
- Step 04
Use cheap models for routing/classification, escalate to frontier models only when needed.
- Step 05
Cache prompts (Anthropic ~75%, Gemini ~80%) to amortize repeated context.
Technologies
The 2026 production stack for this stage. Implement Agentic is deliberately model- and vendor-neutral.
Agent frameworks
- LangGraph v1+ (production winner)
- Anthropic Claude Agent SDK + Skills
- OpenAI Agents SDK
- CrewAI (fastest prototyping)
- Microsoft Agent Framework
- Google ADK
Foundation models
- Claude Opus 4.7
- GPT-5.4
- Gemini 2.5/3 Pro
- Llama 4
- Mistral
- DeepSeek V4
Tool protocol
- Model Context Protocol (MCP)
- A2A (agent-to-agent)
Ecosystem partners
LangChain / LangGraph
Outer orchestrator with state, checkpoints, time-travel debugging
Anthropic
Claude Agent SDK + Skills + Managed Agents harness
CrewAI
Inner role-based crews for sub-task execution
See the full Ecosystem partners page for our tool catalog.
Build-vs-buy decisions
Buy when…
Buy when the workflow is horizontal (Glean, Notion 3.0, Salesforce Agentforce, ServiceNow AI Agents).
Build when…
Build with LangGraph + Claude Agent SDK when the workflow is vertical and proprietary to your business.
Implement Agentic's recommendation
LangGraph as the outer orchestrator wrapping CrewAI inner crews. MCP keeps tools swappable across vendors.
Project lifecycle
| Phase | Timing | Outcome |
|---|---|---|
| Workflow design | Week 1 | State machine, sub-agents, tool boundaries documented. |
| Build + eval | Weeks 2–6 | Working agent with golden test set in CI. |
| Pilot in prod | Weeks 7–10 | Shadow-mode → assisted → autonomous with checkpoints. |
| Operate | Ongoing | AgentOps tunes routing, prompts, tools and Skills weekly. |
Benefits
- Time-travel debugging: replay any production trace step-by-step.
- Cost control via complexity-routed models and prompt caching.
- Vendor portability: change models without rewriting tool integrations (MCP).
Failure modes we prevent
- Bloated tool catalogs the agent can't pick from.
- No human checkpoint on irreversible actions.
- Single monolithic agent instead of sub-agent decomposition.