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4 fiches

Economy & Market Auto-verified translation

Starving Genies

Economics of AI usage limits for augmented coding — Expand phase — Limiting resources — Monetization strategy — Substack

#augmented coding#genies#usage limits

Kent Beck

Transformation & Adoption Auto-verified translation

L'IA générative est plus une affaire de produit technologique qu'un projet d'IA

Op-ed by **Olivier Rafal** (Consulting Director Strategy at **WeNvision**) published on **February 23, 2024** on **CIO-Online** (*Tribune* section), which puts forward a thesis that was still counterintuitive at the time: **generative AI is more a matter of technological product than of an AI/data science project**. **Argument 1 — data science is not the core of the issue**: building a *foundation model* from scratch requires *« several months, millions of euros, and access to enormous quantities of data »* — reserved for players with specific, monetizable datasets (e.g. **Bloomberg** and its **BloombergGPT** for finance). For nearly all companies, the right reflex is therefore not to hire data scientists. **Argument 2 — a skills mismatch**: what's mainly needed are **development and integration engineers** (back/front), **strong cloud skills**, and **DevOps**. Client quote: *« You don't necessarily need to be a data scientist, but you do need to understand the basic concepts, have back-office development skills, and strong cloud skills. »* **Argument 3 — platform architecture (orchestrators + API)**: building an enterprise **plateforme d'IA générative** via orchestrators and API makes it *« easy to work with the best LLMs on the market and switch between them as they each evolve, without reworking the applications »* (anti vendor lock-in). **Argument 4 — from project to product**: *« The platform […] must itself be considered a product »*; instead of a one-off investment, plan for a **monthly funding stream** (continuous iterations, ongoing innovation). **Argument 5 — governance & shadow AI**: the unprecedented democratization of GenAI generates *« as much shadow AI as strong expectations toward the DSI »* → governance to capture business needs, **prioritize products by value**, and oversee proper operation. **Paradigm shift** announced: *« we are moving from classic algorithmic programming to agents Langchain that handle part of the decisions »*. **Relevance for the watch**: a **founding text (2 years ahead)** of WeNvision doctrine (product > project, platform/API, flow-based funding, governance, shadow AI) that the fiches [[wenvision-ai-agents-enterprise-deployment-2025-10-01]], [[habert-ia-agentique-production-2025-10-29]] and [[rafal-wenvision-tokenomics-foundation-finops-ia-2026-06-04]] will extend (FinOps/token, flow-based funding → financial governance). It also prefigures the *harness/platform around the model* (Dropbox/Okumura: *systems around the model*) and **model independence** through an orchestration layer.

#generative AI#technological product#product vs project

**Olivier Rafal** · *Consulting Director Strategy* chez **WeNvision** (cabinet de conseil FR). Tribune publiée dans la rubrique *Tribune* de **CIO-Online**. Auteur déjà présent dans la veille (cf. fiches WeNvision/Atlas/Tokenomics). Publié le **23 février 2024**.