Editorial article **SFEIR AI** published on sfeir.com on **September 6, 2026** (~9,000 characters, seven sections, two sources noted). It recaps an episode of the **DataGen** podcast hosted by **Robin Conquet**, recorded at the **Dev Summit** co-organized by **Adeo** and **Decathlon** (Lille, **May 26-28, 2026**, more than **2,000** attendees), with **Matthieu Grymonprez**, who heads digital, tech, and data at Adeo (Leroy Merlin, Weldom, Obramat), and **Romain Taillade**, Global CTO of Decathlon. Three takeaways. **(A)** The platformization carried out over five years to absorb Leroy Merlin's marketplace (**60,000** in-store references, several million online) and Decathlon's expansion (**more than 50** countries) was not aimed at agentic AI, but forms its foundation: *"the platform built the muscles, the age of intelligence builds the nervous system."* **(B)** Three named workstreams — the development **harness**, zone-based **security** across the IT system (zero agentic activity on payment, the checkout flow, and the supply chain), and **data semantics**, tackled by vertical and where Adeo admits it is in debt. **(C)** A precedent the group paid for: self-service BI produced more than **150,000 dashboards** before the return to certified data products. Grymonprez's framing sentence holds it all together — *"an agent has no common sense"*: it applies the definition as given and accelerates disorder wherever it is lacking. Continues, with the same executive, [[alafrench-grymonprez-adeo-ia-agentique-grands-groupes-2026-06-18]].
#Agentic AI#platformization#API-exposed business domains
SFEIR AI (voix éditoriale du cabinet) · article non signé individuellement. Restitue un entretien de Matthieu Grymonprez (Adeo) et Romain Taillade (Decathlon).
Article by **Chase Covington**, **Tomer Slaney** (partners, New York) and **David Pralong** (senior partner, Charlotte), published by the *McKinsey Transformation Practice* in **September 2026** (exact day unspecified, dated the 1st by convention); 8 pages, 2 exhibits whose content is not reproduced in the text. **(1)** Finding: the transformation office (TO) is slow to modernize its own tools; in a turnaround involving **3,000** employees, **more than 15** people produced a **300-page** report every four weeks. **(2)** Three pillars entrusted to agents: *performance intelligence*, *single source of truth*, *conversation facilitation*. **(3)** Reported gains: **35 to 40%** of time on core tasks, sometimes **70%**; a central team reduced from **ten to three** people. **(4)** Guardrails: cascading errors between agents, false alerts, traceability of each step. **(5)** Sequence: reporting first, action automation next, change management within the TO. The authors present the text as "a first look at the opportunity for TOs". The cases are not named, no measurement method is described, and two of the tools cited (**Wave**, **Lilli**) belong to McKinsey. The text follows on from [[sternfels-mckinsey-60000-people-20000-agents-officechai-2026-01-14]], where McKinsey already counts its agents among its workforce.
Capgemini (Aiman Ezzat, CEO) — Investir interview, "boss special": IA agentique as an operational breakthrough, not just another technology; €2bn invested, +30% on application development and −20% incidents, >11% of Q1 bookings, TAM of over $400bn/year by 2030 — but "very far from plug and play" (Investir / Les Echos)
#Aiman Ezzat#Capgemini#IA agentique
Aiman Ezzat (directeur général de Capgemini) · propos recueillis par La Rédaction d'Investir
**Boris Cherny** (Creator & Head of Claude Code @Anthropic) publishes a framework table on LinkedIn, **« Steps of AI Adoption »**, mapping an engineering team's adoption of agentic AI across **5 stages (0→4)**, each characterized by an **order of magnitude of agents driven** and a **transformation of the engineer's role**: **0 Gated** (0 agents, locked-down access), **1 Assisted** (~1 agent — "you + one agent", supervised pair programming), **2 Parallel** (~10 agents — **orchestrator**), **3 Supervised autonomy** (~100 agents — **manager of managers**, an org tree), **4 AI-native** (~1,000+ agents — **VP steering by intent**). The table crosses five columns: number of agents, *what it looks like*, *the bottleneck*, *the products that help*, *the guardrails*. **Central thesis**: consuming more tokens does not move you up a level — advancing to the next stage requires **identifying and breaking the next bottleneck** AND **building the next set of guardrails**. Concretely: giving Claude a trustworthy **self-verification loop** (tests + build + lint + e2e on a real environment), enabling **Auto mode** (avoiding blocking permission prompts), making **code review and security review the default**, adopting multi-agent interfaces (Agent view CLI, Desktop, iOS/Android apps, Tag), then `/loop`, `/batch`, `/goal`, **dynamic workflows** and **worktree isolation** for subagents. On steering: usage (dashboard) measures **activity, not return**; the right question is *"would we have spent engineering effort on this anyway? if so, how many manual engineer-hours would it have cost?"* — that's the ROI. The real payoff arrives when **fixing and maintaining happens in the background** and teams focus on *building*. Anthropic sits at **stage 3, heading toward 4**; Boris Cherny states he has personally reached **level 4**.
#Boris Cherny#Claude Code#Anthropic
Boris Cherny (Creator & Head of Claude Code @Anthropic)
Third installment of Ashish Singh's « New Engineering Disciplines for the AI Era » series, devoted to **KDLC — Knowledge Development Life Cycle**: an **8-stage** life cycle for turning enterprise knowledge into an **engineered asset**, on a par with code or data. Thesis: AI initiatives fail not for lack of the right LLM choice or a deployed RAG system, but because they **do not address the underlying structure of knowledge** — « AI is only as effective as the knowledge it can discover, understand, retrieve, and trust ». The KDLC chains Discovery → Extraction → Structuring → Knowledge Graph → Embedding → Index Optimization → Retrieval Evaluation → Refresh. It contrasts **traditional RAG** (isolated documents, keywords) with the **Enterprise Knowledge Fabric** (Knowledge Graphs + Semantic Search + Vector DB + Hybrid Search), where agents understand « relationships, context, and business meaning ». Signature line: « Models provide reasoning. Memory provides continuity. Knowledge provides understanding. » Three examples (finance/compliance, software engineering, healthcare) illustrate the impact.
#KDLC#knowledge development life cycle#knowledge life cycle
Podcast interview on « 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 costs and FinOps, enterprise intelligence lock-in, corporate memory, and agent orchestration. Domain: digital transformation, agentic AI, retail, IT strategy.
#agentic AI#digital transformation#CDO
Mathieu Grymonprez (Global CDO, groupe Adeo) — invité ; Jean-Baptiste Kempf · Steeve Morin · Mehdi Medjaoui (hôtes du podcast « À la French »)
Video interview recorded at **VivaTech** (**Scaleway** booth), broadcast by the media outlet **République**, bringing together **Damien Lucas** (CEO of Scaleway) and **Franck Le Moal** (Global Technical Officer of the **LVMH** group). **Central thesis**: the emergence of a **"tech geopolitics"** is forcing multinationals to abandon the single global solution in favor of an **information system regionalized into three blocs** (United States, Europe, China). LVMH (€80bn in revenue, 75 maisons, 100+ countries) formalizes a **cloud partnership with Scaleway** to build an **autonomous European building block**, alongside Google Cloud (data, since 2021), SAP, Salesforce on the Western side and Alibaba Cloud / Huawei / Tencent on the Chinese side. The group describes itself as **"hybrid"** and **autonomous** rather than **"sovereign"** (a word it rejects, deemed ambiguous). Scaleway positions itself as a **European cloud provider** immune to extraterritorial laws and protected against a **kill switch** ("not science fiction," given the weekend's news). Damien Lucas's economic argument: **€1 spent with Scaleway = 68 cents that stay in the European economy** (vs < 20 cents with a US hyperscaler, even when hosted in France). Timeline: PoCs completed, rollout starting at **Sephora and Louis Vuitton**, significant footprint targeted within **12-18 months**. Scaleway's stated mission: focus on **IaaS/PaaS** (no verticalization such as office productivity software), relying on a partner ecosystem (sovereign applications, European chipsets and servers). Scaleway's **Nvidia GPU / AI** offering is **not planned in the short term** but remains open (open source models for autonomy + economic performance).
**Bertrand** — journaliste / présentateur du média **République** (partenaire de VivaTech) · conduit l'entretien. **Damien Lucas** — CEO de **Scaleway**. **Franck Le Moal** — Global Technical Officer du groupe **LVMH**.
Philippe Ensarguet (Orange) argues that fifty years of design patterns form a continuous lineage: at a time when AI commoditizes code and breaks the traditional way architects are trained, "pattern literacy" (reading a system through its invariant forces) becomes the durable skill to teach — as a grammar, not as catalogues.