# alafrench-grymonprez-adeo-ia-agentique-grands-groupes-2026-06-18

## Veille

Podcast interview « À la French » (French-language tech channel, recorded at DevSummit) with Mathieu Grymonprez, Global CDO of the Adeo group (Leroy Merlin, Obramat, Weldom). How a century-old family retail group embraces the agentic AI wave: culture vs structure, accountability, token cost and FinOps, enterprise intelligence lock-in, company memory and agent orchestration. Domain: digital transformation, agentic AI, retail, IT strategy.

## Titre Article

Comment l'IA agentique bouscule les Grands Groupes ? Partie 2/2 #DevSummit

## Date

2026-06-18

## URL

https://www.youtube.com/watch?v=p4yg2JCAw-s

## Keywords

Agentic AI, digital transformation, CDO, retail, Adeo, Leroy Merlin, Decathlon, accountability, make vs buy, token cost, FinOps, lock-in, company memory, agent orchestration, Claude Code, Vertex AI, context engineering, sovereignty, RFID end-to-end, AI ROI

## Authors

Mathieu Grymonprez (Global CDO, groupe Adeo) — invité ; Jean-Baptiste Kempf, Steeve Morin, Mehdi Medjaoui (hôtes du podcast « À la French »)

## Ton

**Profile**: first-person conversation, oral and informal register (tech podcast among peers), high technical level but deliberately made accessible. Perspective of a practitioner-executive who « got his hands dirty ».

**Style**: an experience-based narrative punctuated with anecdotes (the 2012 Brazilian crash, the first Check Point firewall, the bulk screws at Leroy Merlin), recurring humor (the running gag « Hermès » the AI agent vs. the luxury house; « Allatoubon » on anglicisms; the « pickaxe sellers ») and memorable phrases. Notable metaphors: « trust is earned in drops and lost in liters », « 4 days of engineering, 6 years of surfing », « pay to see », « I'm not a Markov chain », « when it's not logical, it's historical » (a quote attributed to the director of the Louvre), Boris Cyrulnik (« to teach Paul math, first understand how Paul thinks »). **Authority**: 26 years with the company, 8 years as CDO, career path from network-security engineer → expat in Brazil → group strategy. **Target audience**: CDOs, CTOs, tech executives at large groups undergoing transformation.

## Pense-betes

- **Make vs Buy** at Adeo is « at least 70% » make: no competitive differentiation in full buy.
- Every transformation is won on **two fronts at the same time**: culture AND structure. The same playbook (which drove digital transformation: waterfall → agile, product, platforms, tech radar, APIs, microservices) is being replayed with AI.
- **Accountability** remains human and tied to organizations, all the way to legal: « I don't want some guy telling me it's broken in production but it's not my fault, it's the agent ».
- **Documentation debt** (mediocre product docs, nonexistent process docs) « is going to slap us in the face very soon »: an agent can't read documentation that doesn't exist.
- Mathieu **never talks technology at the board**: he talks customer experience, ROI, profitability, investment.
- He **doesn't even ask for extra budget** for AI: the gains (compressing JIRA tickets, ops) fund the new work (« at flat »). A **reuse** logic: the time saved is reinvested in service of the in-store salesperson / the customer.
- No fantasy of « firing all the developers thanks to Claude Code »: on the contrary, he anticipates an **avalanche of requests** — P10/P15 projects move to P2 because « no project costs too much anymore ».
- His big **« wake-up call »**: Claude Code (recreating a VM without having coded in a long time), then seeing Karpathy and others « ship » more, then his personal agent **« Hermes »** (with memory).
- **Token cost**: confident it will fall as cloud FinOps did (FinOps muscle built after BigQuery queries costing 30k). Levers: inference chips (Google TPUs), open-source models catching up (~9-month gap China/Anthropic), distilled models running on a laptop (Gemma 4, MoE 26B / 4B active, « designed in Paris »). A frontier model isn't needed for the group's ~300 digital products.
- **Model variation = a real production problem**: when a model changes, retesting is required (different results); providers requantize / downgrade / route to lower capacity. They stopped upgrading once it was « good enough » (marketplace sorting: 15M products → 7M published, via OpenAI). The goal is « to be fast, but on one's own terms ».
- **Production awareness**: Google has it while startups (OpenAI, Anthropic) don't yet (e.g. a bug where Codex/Claude limits were burned through in 1 hour instead of a full day, reset at 5pm).
- His **biggest concern**: **lock-in of the company's intelligence** (the company's configuration baked into an agentic harness / « adeo.md »; « redoing the ERP of AI »). Countermeasures: standard Kubernetes (no proprietary Cloud Functions), regularly testing APIs with other hyperscalers, attention to **memory management** (cold/hot, context engineering, where it's stored, who owns it).
- **Missing open-source building block**: **agent orchestration** (registry, lifecycle, permissions — « which agent is allowed to do what » —, sharing skills company-wide). n8n / MCP only cover a small part of it.
- **Company memory** (« company brain »): « when it's not logical, it's historical » — capturing the context behind decisions. E.g. Leroy Merlin doesn't sell mattresses because the company is **run on revenue per square meter** (a bed takes up too much space for what it brings in); this should go into the company brain so a future product manager doesn't re-pitch the idea.
- **RAG / access control**: hard to know what the person asking the question is entitled to (multiple authorization levels) — an unresolved problem for enterprise chatbots.
- **AI stack**: Vertex AI (GCP), model selection based on need. Always keep an eye on « the exit door » (sovereignty).
- **Advice to another CDO**: transformation is **bespoke** (culture, available capital); identify the **real competitive differentiator** in the customer experience. If the board can't even articulate it → basic IT / operational maintenance. If it can articulate it → go all in, build something complete end-to-end, set the precedent. Understand the technology mainly « so as not to get fleeced by vendors and hype ».
- **Decathlon end-to-end RFID**: a success because they manufacture a large share of their products themselves (chip embedded at the start of the industrial chain) all the way through to downstream security. Simple metric: time saved across the whole chain (staff + customer) = instant ROI. Adeo only manufactures half → getting all suppliers' industrial tooling to change is very complicated.

## RésuméDe400mots

The second part of an episode of the « À la French » podcast recorded at DevSummit, this interview brings together Mathieu Grymonprez, Global CDO of the Adeo group (Leroy Merlin, Obramat, Weldom), and hosts Jean-Baptiste Kempf (creator of VLC), Steeve Morin and Mehdi Medjaoui. Mathieu, 26 years with the company and 8 years as CDO, traces a career path from network-security engineer (first Check Point firewall) to leader of « Digital Tech and Data »: after urgently resolving an Oracle database crash in Brazil (2012) and then overhauling the local IS during six years as an expatriate, he rationalized the group's 24 IS / sites / PIM into digital platforms (customer & commerce, supply chain, retail, corporate) supported by a tech radar, documented APIs and microservices (which became « big products »).

His thesis: **every transformation is won on two simultaneous fronts, culture and structure**, and the digital transformation playbook (waterfall → agile, product, more make than buy) is being replayed with AI. On the culture side: reconfigure to embrace the technology, keep critical judgment and above all **accountability** — responsibility remains human, « it's not the agent's fault ». On the structure side: close the documentation debt, manage agents' rights and permissions. Remembering the failure of the « Retail Apocalypse » (Amazon, e-commerce negotiated too late), the watchword is « we won't get caught out again »: take AI seriously, but with the same values (pragmatism, customer service, leading brand). If ChatGPT builds a better basket than the in-house app, « that's my problem ».

At the board, Mathieu never talks technology but customer experience and ROI; he doesn't even ask for an AI budget, funding the new work through the gains (compressing JIRA tickets), in a logic of reuse serving the in-store salesperson. He doesn't anticipate the end of developers but an avalanche of requests (P10 projects become P2). On costs, he is confident: token FinOps will follow the path of cloud FinOps, driven by inference chips (TPUs) and open-source models catching up (Gemma 4 on a laptop). But model variation is a real production problem (retesting, requantization, silent downgrades), and Google has a « production awareness » that OpenAI or Anthropic don't yet have. His biggest concern: **enterprise intelligence lock-in** (agentic harness, « adeo.md »), hence the attention paid to standard Kubernetes, API portability and memory. He points to the missing open-source building block — agent orchestration (registry, lifecycle, permissions, skills) — and company memory (« when it's not logical, it's historical »). Final advice: transformation is bespoke; understand the technology mainly to avoid getting « fleeced » by pickaxe sellers.

## GrapheDeConnaissance

- Mathieu Grymonprez —dirige→ Adeo (ORGANISATION, 0.97)
- Mathieu Grymonprez —travaille_chez→ Adeo (ORGANISATION, 0.98)
- Adeo —affirme_que→ "On ne va pas se refaire avoir (après le Retail Apocalypse)" (CITATION, 0.88)
- Transformation IA —est_basé_sur→ culture et structure simultanées (CONCEPT, 0.93)
- Accountability —s_applique_à→ organisations et humains (CONCEPT, 0.92)
- Mathieu Grymonprez —recommande→ parler ROI et expérience client au board, jamais technique (AFFIRMATION, 0.94)
- Claude Code —améliore→ productivité de développement (CONCEPT, 0.9)
- IA agentique —permet→ avalanche de projets jadis non prioritaires (P10 → P2) (AFFIRMATION, 0.88)
- FinOps —s_applique_à→ coût des tokens (CONCEPT, 0.9)
- Gemma 4 —permet→ inférence locale sur laptop (MoE 26 Mds / 4 Mds actifs) (AFFIRMATION, 0.85)
- Variation de modèles —s_oppose_à→ stabilité de la production (CONCEPT, 0.9)
- Kubernetes standard —réduit→ lock-in fournisseur (CONCEPT, 0.91)
- Lock-in de l'intelligence d'entreprise —s_oppose_à→ autonomie du groupe (CONCEPT, 0.87)
- Orchestration d'agents —affirme_que→ "rien en open source ne marche bien pour ça" (CITATION, 0.86)
- Mémoire d'entreprise —est_basé_sur→ "quand ce n'est pas logique, c'est historique" (CITATION, 0.85)
- Leroy Merlin —mesure→ chiffre d'affaires au mètre carré (MESURE, 0.9)
- Decathlon —utilise→ RFID end-to-end (puce en entrée de chaîne industrielle) (TECHNOLOGIE, 0.92)
- Google —surpasse→ OpenAI et Anthropic sur la conscience de la prod (AFFIRMATION, 0.8)
- Vertex AI —permet→ sélection du modèle selon le besoin (CONCEPT, 0.88)
- Mathieu Grymonprez —recommande→ comprendre la techno pour ne pas se faire enfler par les vendeurs (AFFIRMATION, 0.9)

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Canonical: https://www.thekb.eu/en/fiches/alafrench-grymonprez-adeo-ia-agentique-grands-groupes-2026-06-18/