01

Start with the process, not AI

Document ten recent executions. Count active minutes, waiting, rework, exceptions and system changes. If nobody can define a correct result, the process is not ready for automation.

Volume

Occurrences by day, week and season.

Variability

Distinct paths and the percentage of exceptions.

Friction

Active time, waiting, application switching and corrections.

Risk

What happens when the system is wrong or unavailable.

02

Classify the work

Not everything needs an agent. The cheapest solution that meets the objective is usually the easiest to maintain.

Deterministic rule

Use conventional code when conditions are stable.

Extraction or classification

Use models for ambiguous input while validating critical fields.

Generation

Define criteria, examples, voice and risk-based review.

Agent

Reserve it for work involving decisions, tools and error recovery.

03

Calculate full value

Count quality, speed and released capacity as well as integration, inference, maintenance and supervision.

  • Baseline before building.
  • Estimated cost per run and per month.
  • Maximum acceptable human-review rate.
  • Value of fewer errors or faster responses.
  • A clear threshold to stop or redesign the pilot.
04

Design control and exit

The company should understand the flow, switch providers and recover its data. Separate business logic, model, connectors and observability.

  • Client-controlled data and credentials.
  • Fallback when a provider or model fails.
  • Traceable decisions without logging secrets.
  • Human approval before irreversible actions.
  • Delivered code, documentation and operating procedure.