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    Enterprise Automation Architect — Production Workflow Design & Reliability

    by Vivek K

    1

    The problem Teams “automate the happy path” and discover duplicates, missed revokes, and silent API failures in production.

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    You say

    Process: CampusAccess — after-hours building access exceptions

    Manual today:

    1. ServiceNow request (building, rooms, window, reason)
    2. Clerk checks Workday employment active
    3. Clerk checks LMS safety training complete
    4. Clerk creates temporary badge grant in access-control system
    5. Slack #campus-security + email requester
    6. BSL-2 / lab after 10pm needs lab director signature (PDF today)
    7. Morning revoke often forgotten → orphan grants

    Volume: ~80/week, ~200/week at semester start SLA: 4 business hours for standard buildings Constraints: reuse Temporal; no secrets in repo; no orphan grants after window

    Ask: full production automation architecture (design mode). Do not execute.

    Your agent does

    Enterprise Automation Architecture

    1. Decision Summary

    | Field | Value | |---|---| | Process | CampusAccess after-hours access exceptions | | Mode | Design | | Paradigm | event-driven (ServiceNow) | | Scale band | medium at semester peaks | | Build vs buy | Orchestrate on Temporal + modular adapters | | Maturity | NEEDS-HARDENING |

    2. Human-automation boundary (excerpt)

    | Step | Verdict | |---|---| | Workday + LMS checks | AUTOMATE | | Standard building grant | AUTOMATE (after checks) | | Lab / BSL-2 after 10pm | KEEP-MANUAL path with director APPROVE | | Revoke after window | AUTOMATE (compliance) | | Policy waivers | KEEP-MANUAL |

    3–4. Paradigm & build recommendation

    Event-driven async workflow (not nightly batch). Reuse campus Temporal for durability, approval waits, and revoke timers. Thin adapters for ServiceNow, Workday, LMS, access control, Slack/email — not a second iPaaS.

    5–6. Contracts & reliability

    • Grant create: effectively-once via idempotency_key = ticket_id
    • Webhook: at-least-once with dedupe
    • Notify: at-most-once (never block grant on Slack failure)
    • Exception tree: inactive/untrained → auto-deny; access auth fail → escalate; lab after 22:00 → park for APPROVE; revoke fail → escalate + orphan report

    7–8. Security & HITL

    Threats: stolen creds, over-privileged bot, webhook spoofing, PII in logs. Secrets manager only. Least-privilege grant/revoke role. HITL: lab-after-10pm director APPROVE; standard path AUTO when policy passes.

    9–10. Observability & rollout

    Metrics: auto-approve rate, time-to-grant, orphan_grants_count, revoke failures. SLO: 4h standard decisions; zero orphans older than 24h. Rollout: Shadow (simulate) → Canary (one non-lab building) → Full (labs stay APPROVE).

    11–14. ROI, testing, runbook, maturity path

    Labor assumption ~20 clerk hours/week; payback often 1–2 semesters if validated. Tests: policy, idempotency, revoke timer, chaos on access API. Runbook: detect → triage by ticket_id → recover → communicate. To PRODUCTION-READY: confirm OpenAPI maps, orphan scanner, director UX, shadow period.

    15. JSON

    Full Automation Architecture JSON (boundary, adapters, steps, threats, slo, rollout, cost_model, testing, runbook, assumptions).

    What you get

    Design a new multi-system business automation from a process descriptionDecide AUTOMATE vs ASSIST vs KEEP-MANUAL for each stepChoose build vs buy vs orchestrator (Temporal / Airflow / n8n / SaaS)Harden a brittle automation (retries, dedupe, exception tree)Plan shadow → canary → full rollout with rollbackBuild a cost/ROI case versus manual effort

    About this skill

    The problem

    • Teams “automate the happy path” and discover duplicates, missed revokes, and silent API failures in production.
    • Not every step should be automated — high-judgment and high-liability steps need human-in-the-loop design up front.
    • Build-vs-buy and orchestrator choice are often made by habit, not by volume, durability, and ops ownership.
    • Leadership asks for ROI and SLA accountability, but the design never defined metrics or a safe rollout.

    What it does

    • Classifies the automation paradigm (batch, scheduled, event-driven, streaming, human-triggered) and scales the design to real volume.
    • Draws a human-automation boundary: AUTOMATE, ASSIST, or KEEP-MANUAL per step with reasoning.
    • Recommends build vs buy vs orchestrate (e.g. Temporal, Airflow, n8n, SaaS) with a clear rationale.
    • Designs modular adapters with data contracts and delivery guarantees (at-most / at-least / effectively-once).
    • Specifies idempotency, retries, rate limits, and an exception decision tree (retry / escalate / skip / compensate / park).
    • Builds a security threat model, secrets plan, and HITL gates (AUTO / CONFIRM / APPROVE).
    • Defines observability + business metrics + SLA/SLOs, a shadow → canary → full rollout, cost/ROI, testing, runbook, and a maturity path to production.

    Frameworks & tools

    • Orchestrators and integration platforms commonly used in enterprises (Temporal, Airflow, n8n, iPaaS) plus custom adapters.
    • Works across ERP, ITSM, HRIS, LMS, messaging, access control, and other SaaS/API systems you name.
    • Compatible with Claude Code, Cursor, Codex CLI, OpenClaw, and other SKILL.md agents — no live execution required for design.

    Why this beats prompting it yourself

    • Forces the hard questions: what not to automate, what needs approval, how duplicates are prevented.
    • Typed delivery guarantees and exception trees instead of “add a retry.”
    • Security and PII logging constraints designed with the workflow, not bolted on later.
    • Rollout stages with exit criteria and rollback — not a big-bang cutover.
    • ROI and SLOs stated with explicit assumptions, not invented precision.
    • Maturity verdict with a concrete path (e.g. NEEDS-HARDENING → PRODUCTION-READY).

    How to install

    Drop the file into your AI Agent. Works with Claude, Cursor, ChatGPT, and 20+ more.

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    Creator

    Vivek K
    Vivek K

    20 skills on Agensi

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