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Success story

Training 80 PMs & EMs in Data & AI

Leboncoin runs more than 70 AI features in production. To help its Product and Tech teams make the most of that potential, the company called on Hymaia to train 80 Product Managers and Engineering Managers in Data & AI challenges.

Photo d'une personne visitant le site de Leboncoin sur son ordinateur

AI sits at the heart of leboncoin's product strategy. But effectively embedding AI into digital products takes more than technology: it requires a solid grasp of its specific challenges, and smooth collaboration between Product, Tech and Data.

Leboncoin chose Hymaia to support and train its 80 PMs and EMs through a tailor-made program, blending acculturation, upskilling and hands-on practice.

A clear goal

Give PMs and EMs all the groundwork they need to:

  • Understand the fundamentals of Data and AI, tied to real product and business use cases
  • Tell Data/AI products apart from classic software products: uncertainty, iteration, dependence on data
  • Adapt Product Management tools and methods to the specific context of AI projects
  • Bring AI into their daily work to maximize their productivity

    • Teaching rooted in real usage

    The program combines three complementary formats:

  • The Data & AI Fresco to build a shared view of the ethical, technological and business challenges
  • The Data & AI Product Management program structured around concrete cases, hands-on workshops and theory accessible to non-tech people
  • Small-group formats encouraging peer exchange, product-tech collaboration and the gradual spread of good AI practices

    • Support aligned with the company's AI ambitions

    Leboncoin's work on AI rests on strong principles: industrialize without turning it into a gadget, measure impact, favor transparency and equip teams properly.

    Hymaia's support addresses these challenges directly:

  • Build PM & EM acculturation so they drive the detection, scoping and steering of AI opportunities
  • Structure Product-Tech-Data exchanges to gain in fluidity, relevance and accountability
  • Foster a cross-functional Data culture, consistent with embedding Data Scientists within product squads

    • Concrete results

    Training 80 PMs and Engineering Managers means making sure product decisions already account for AI's specifics today. It also gives teams the means to:

  • Prioritize the right use cases
  • Choose the right models
  • Monitor the right indicators
  • Ship features that are useful, durable and measurable
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