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 « 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.
#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.