Public posters love a clean ladder: Plan → Build → Validate → Operate, twelve boxes, each with a Tools row. LangChain here, LangSmith there, Docker at the end. Fine as a checklist. Terrible as an architecture.

We shipped a runnable POC that walks all twelve steps and refuses to treat those logos as the control plane.

The pattern

Plan     → use case + risk/policy before model choice
Build    → evidence RAG, prompt contract, input walls, MCP two-wall tools
Validate → output gates, Agent Run trace, eval / red-team flags
Operate  → continuous identity posture + Decision Ledger iterate

Invariant: fail closed. If input injection or a risky tool hits a wall, later steps are skipped — we do not pretend Deploy still “secured” the request.

What we built

Path: pocs/llm-guardrails-monitoring-poc/backend/pipeline.py

• Deterministic mock model (no API key required for the classroom demo)
• Keyword RAG over two policy docs with an evidence sufficiency flag
• Input scan over user + RAG + tool description text (not jailbreak-only)
• Step 7 blocks transfer_funds via a simulated MCP scope wall
• Step 9 emits an Agent Run-shaped trace (goal → steps → model → outcome)
• Step 12 writes a ledger action: ship_answer or escalate_human

UI on port 8020 with four probes: happy path, injection, risky tool, weak evidence.

What we did not do

• Live LLM providers or real vector DBs
• Real Entra / APIM / OAuth (see claims-mcp-oauth-poc for that)
• Durable workflow runtime for long MCP tools
• Production eval suites in CI

Those belong in later phases. This POC proves the sequence, not the cloud shopping list.

Corrections vs the poster

Poster habit	XingAI correction in the POC
Tools column = architecture	Walls and contracts; tools fill slots
Input guard = user jailbreak	All untrusted observations
Tool control = agent SDK logos	Scope wall + policy wall
Monitor = latency/cost only	Agent Run trace
Deploy last = security done	Auth posture from Plan; Deploy is continuous

Links

• POC: https://github.com/xingaiapp/xingai-enterprise-ai-pocs/tree/main/pocs/llm-guardrails-monitoring-poc
• ADR-010: https://github.com/xingaiapp/xingai-enterprise-ai-pocs/blob/main/docs/adr/010-llm-guardrails-monitoring-poc.md
• Design article: https://github.com/xingaiapp/xingai-enterprise-ai-design/blob/main/articles/2026-07-17-llm-app-guardrails-plan-build-validate-operate.md
• Wiki critique: https://github.com/xingaiapp/xingai-ai-learning-wiki/blob/main/wiki/syntheses/llm-guardrails-monitoring-vs-xingai.md

Disclaimer

Educational POC and post. Not production software, legal advice, or a security certification.