From Repetitive Task to Production Workflow

Consider a shared inbox that receives supplier invoices. An employee downloads each attachment, copies fields, checks the supplier, requests approval and updates accounting. The goal is not “use AI.” The goal is a complete, observable outcome.

1. Trigger

Capture the event reliably: a new email, upload or API record. Assign an idempotency key so retries do not create duplicates. Store the original item and timestamp.

2. Context

Retrieve supplier records, purchase orders, tax rules and approval limits using the identity and permissions appropriate for the workflow. Context should be explicit and traceable.

3. Reasoning

Use document extraction and AI classification where formats vary. Ask for structured output, validate required fields and retain source references. The model proposes; validation determines whether the result can continue.

4. Control

Apply deterministic rules for duplicates, totals, supplier matching and approval thresholds. Route uncertain or high-risk cases to a reviewer with the document, extracted values and failed checks in one view.

5. Action

Create the accounting entry, update status and notify the right person. Record each state transition and external response. A failed action must retry safely or move to an exception queue.

Release progressively

Start in observation mode and compare proposed outputs with real decisions. Then automate a narrow low-risk segment. Expand only when quality, exception handling and recovery meet agreed thresholds.

The same five layers apply to lead routing, recurring reports and support triage. Production quality comes from the boundaries between layers: validated data, explicit permissions, controlled state and visible exceptions.

Define the state machine

Give every item an explicit state such as received, validated, awaiting approval, posting, completed or exception. State changes should be atomic and logged. This prevents an email retry or service restart from creating invisible duplicate work.

Design idempotent actions

Before calling an external system, check whether the intended action already occurred. Send idempotency keys where supported and store external identifiers. Repeating the same message should not create a second invoice or customer record.

Treat model output as untrusted input

Require structured schemas, type checks, allowed values and business-rule validation. Escape content used in downstream systems. Retrieved documents and email bodies may contain instructions that the workflow must never treat as authority.

Build the exception queue first

Show the original item, failed checks, proposed values and next allowed actions. Assign ownership and service levels. Exceptions are not miscellaneous errors; they are a product surface for the people keeping the process correct.

Test the end-to-end path

• Duplicate event arrives twice.
• Supplier or customer record is missing.
• Model response violates the schema.
• Approval is rejected or expires.
• External API times out after processing the request.
• Workflow restarts halfway through.

Release metrics

Track completion rate, straight-through rate, exception categories, active review time, end-to-end cycle time and reconciliation differences. Quality thresholds should be agreed before expanding scope.

Operational handover

Document architecture, credentials, owners, runbooks and known limitations. Train operators on exception handling and technical staff on recovery. Schedule a review after launch when enough real cases exist to challenge the original design.