Field notebook · BI & Data Analytics

A consultant, augmented by AI.

Claude, AI agents and augmented workflows, reshaping data work — from raw data to the published report.

Scroll the lifecycle
The manifesto

The Augmented Consultant Manifesto

Why AI didn’t come to replace consultants. It came to raise the game.

Artificial Intelligence didn’t come to replace consultants who think. It came to challenge consulting that just executes tasks, with no context, no judgment and no impact.

In Data & Analytics, Reporting and Business Intelligence, AI can already accelerate analysis, documentation, metric creation, prototyping, technical review and solution development. But accelerating is not the same as deciding. Producing faster doesn’t mean delivering better.

The augmented consultant uses AI to explore more hypotheses, cut repetitive work and free up time for what still demands human experience: asking good questions, interpreting context, validating results, communicating clearly and turning data into decisions.

AI can generate a first version.The consultant is still responsible for the right one.

AI can suggest answers.The consultant is still responsible for asking the right questions.

The new advantage isn’t just using AI tools. It’s knowing how to redesign the work, direct agents, apply critical thinking and make sure every deliverable has quality, meaning and real impact.

AI doesn’t lower the bar for consulting.It raises it.

The future belongs to consultants who can combine data, technology, business and artificial intelligence to work better, decide better and create more value.

AI doesn’t replace the consultant who thinks.It replaces the consulting that stopped thinking.
Read the full manifesto
The augmented BI lifecycle
01 / 09

Data

Raw sources land — CSV, SQL, APIs, a spreadsheet someone emailed.

AugmentedAI agents pull, catalog and tag the sources automatically.

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Future of reporting

The static report is dying

Why the dashboard is no longer the default destination for business questions.

Power BI · AI agents

Reviewing 200 DAX measures with Claude

A client model had grown to 200+ measures over three years. Nobody fully understood it anymore. So I pointed an AI agent at it, and let it read every line.

What the agent caught

Three measures, three names, one identical calculation. The agent proposed a single canonical measure and the rename map for the rest.

“The model didn’t need more measures. It needed someone to read all of them at once.”

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