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Notes from the operation.
What we learn putting AI agents to work in regulated companies. Written for the people who decide.
How to tell if an AI agent is working: five metrics for management
An agent in production generates plenty of activity. Five metrics, measured against a baseline, show whether it is resolving the work and doing it well.
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- Choosing the first process for an AI agentThe first process decides whether the project continues. Six criteria to choose it, examples of good and poor starting points, and a checklist to run before approving.
- One WhatsApp for the whole company: how it works, what it takesYour customers write to one number and each question reaches the team that resolves it. What it takes to do it right, from Meta’s rules to Law 1581 of 2012.
- One version of the numbers: how to stop arguing about the figuresWhen every department brings its own spreadsheet, the meeting goes to reconciling figures. Why it happens, and the decisions that let the whole company read the same number.
- How to tell if your company is ready for AIBefore investing in AI, review eight areas of the organization. This is the synthesis we use in every diagnostic.
- AI agents vs. traditional softwareFixed rules work in stable processes and break in the ones that change. A simple test to decide where each one belongs.
- AI that cites its sources vs. AI that improvisesTwo approaches with the same technical name and very different results: one cites the source of every answer, the other improvises with confidence.
- Six decisions before you approve your first agentWhat management should be clear on before signing: where the value is, who runs it, which controls to require and how to measure it.
- AI in finance: which controls to requireAI is not banned in finance: it is audited. Five controls an agent must meet before it serves a single customer.
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