Personalised playlists for radio listeners

An hour of curation per listener, down to seventy seconds.

Sector : Media — A French-language national radio station

The context

A radio station offers its listeners a personalised playlist, built from their answers to a questionnaire: their age, the artists they name, the memories they share.

The problem

Genuinely curating those twenty-five tracks takes an hour: you have to respect the category quotas, the balance across decades, the share of French-language tracks, and exclude everything aired in the last three weeks. An hour per listener, Monday to Friday.

What was built

The selection is made by the code, from the catalogue, the quotas and the blocklist of recently aired tracks. The model only steps in afterwards, to write the reasoning behind each choice — and if its answer breaks the constraints, a second call corrects it.

What it changes

An hour of curation down to seventy seconds, for one listener served every weekday. The email that arrives justifies each of the twenty-five tracks.

How it works

A sixteen-node n8n workflow: catalogue and blocklist loaded from Google Sheets, merged, deterministic selection by crossed language × decade quotas, a call to Claude through OpenRouter for the justifications, a validity test, a corrective call if needed, blocklist update, and the HTML email. A full GDPR pack ships with the delivery.

What this could look like for you

This is the demonstration that reassures managers who fear an AI will "make things up": the business rules decide, the AI explains. Wherever you have non-negotiable constraints — a chart of accounts, a nomenclature, a regulation — that is the division of labour to aim for.