AI Product Factory

An AI product factory is a productised platform and operating model that lets many feature teams repeatedly build, evaluate, govern and operate AI products through shared capabilities, golden paths and reusable domain accelerators.

Operating layers

1. Unified foundations: governed data, training, evaluation, serving and engineering interfaces [src-236].

2. Platform product management: internal-customer discovery, prioritisation, adoption and measurable outcomes [src-236].

3. Production standards: shared evaluation, observability, model access, ownership and agent framework [src-236].

4. Domain accelerators: reusable templates that assemble standard platform capabilities around a use case [src-236].

5. Agent-ready interfaces: MCP, CLIs, SDKs, skills, plugins and documentation that serve software agents as platform users [src-236].

Important distinction

This concept concerns the organisational production of AI-enabled products. It is distinct from the infrastructure meaning of an AI Factory as a data-centre-scale system that produces model training or inference throughput.

Related

Source references

  • [src-236] Marco Saetta / Doctolib — "From one AI product to an AI factory" (2026-07-10)

Robin Cartier perspective

This page is part of Robin Cartier's working AI knowledge graph: a practical research layer for production AI, recommendation systems, experimentation, GEO, and agentic web readiness.

The useful next step is to connect this concept back to applied product leadership and operating models.

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