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7 fiches
Anthropic launches Claude Fable 5 (a Mythos-class model made safe for general use) and Claude Mythos 5 (the same model, with guardrails lifted, restricted to cyberdefenders via Project Glasswing): state-of-the-art performance in software engineering, vision, long-context memory, and life sciences.
Anthropic
Op-ed by **Olivier Rafal** (Consulting Director Strategy, **WeNvision** — **SFEIR** group; former editor-in-chief of *Le Monde Informatique*) published on **June 1, 2026** in **CIO-Online**, structured around a **paradox**: in the AI era, software engineering **changes everything… and nothing changes**. **What changes = the operating model.** Roles are redefined: the **Product Owner** shifts from backlog breakdown to **generating context usable by AI**; the **developer** shifts from writing code to **framing, directing, and reviewing** agent execution; **QA** gains the ability to define **expected proof** upfront. Team structure shifts from *"double pizza teams"* (hand-off chains of ~8 people) to ***"sandwich teams"***: a **tight pairing of a business expert and a tech lead, both AI-augmented**, with other skills in support. Internal **Sfeir** figure: *"this pairing now drives roughly 80% of the production chain"*, with the remaining ~20% (architecture, data governance, security) centralized. Pivot quote: ***"The issue is not a tooling issue, but an operating-model issue."*** **What doesn't change = the discipline of the cycle.** The **SDLC** phases (define → build → verify → deploy → maintain) remain identical and non-negotiable; AI removes none of them, it **intensifies** them: ***"all the slack that human-paced work absorbed, one way or another, becomes, at AI speed, industrial-grade defects"*** (amateur-vs-professional sport metaphor). Hence **three inviolable *gates*** (human control): **specification, planning, delivery review**; validation **by proof** (not by AI's own assertions); **systematic capitalization** (each cycle enriches the next) → measured result: **−30% correction iterations after ~10 cycles**. Principle: ***"the faster the execution, the stricter the framework must be."*** Concepts drawn on: **harness** (agentic rules adapted to context), **vibe-coding** deemed **untenable in the enterprise**. **Third pillar = governance, FinOps & value-driven steering**: **variable and recurring** AI costs (~**€10/hour** per augmented seat), a shift from flat-rate licensing to usage-based billing (a 2010s cloud parallel); **FinOps** does not aim to cut costs but to *"optimize tool efficiency"* (cost weighed against value); aligning **business metrics** upfront (time-to-market, features, performance, eco-design). **Conclusion**: acceleration makes the fundamentals **non-negotiable**; the challenge is **organizational and cultural**, not technological — without securing the business relationship and collective discipline, an AI-boosted SDLC merely **amplifies problems** (hitting the wall faster). Extends the WeNvision doctrine from [[rafal-wenvision-ia-generative-produit-techno-pas-projet-2024-02-23]] and [[rafal-wenvision-tokenomics-foundation-finops-ia-2026-06-04]]; converges with *systems around the model* [[dropbox-okumura-beyond-code-generation-engineering-productivity-ai-agents-2026-05-28]], *harness engineering* [[osmani-agent-harness-engineering-2026-04-19]], agentic Salesforce, and the *agent manager* debate (BFM/Girard, SFEIR).
**Olivier Rafal** · *Consulting Director Strategy* chez **WeNvision** (groupe **SFEIR**). Ancien **rédacteur en chef du *Monde Informatique*** · et auparavant consultant analyste du marché IT (~10 ans). Tribune publiée dans la rubrique *Tribune* de **CIO-Online**. Publié le **1er juin 2026**.
Continuous Delivery as the non-negotiable foundation of AI-assisted development — Dave Farley, on his channel *Modern Software Engineering*, argues that without CD, AI is not an accelerator but a trap (theory of constraints and Jevons paradox applied to generated code, ATDD/BDD as a safeguard, deployment pipeline as quality arbiter).
Dave Farley (Modern Software Engineering — YouTube channel)
AI-native job interview at Sierra — Overhaul of engineering hiring process — Plan/Build/Review — Sierra Blog
Bret Taylor
Jevons paradox applied to developers, Red Queen effect, sysadmin→DevOps evolution as analogy
Simon Wardley
Building Claude Code - AI-first Architecture - Product Engineering - Pragmatic Engineer
Gergely Orosz (auteur de l'article) · Boris Cherny · Sid Bidasaria · Cat Wu (équipe fondatrice de Claude Code)
MCP Replaces the Browser - AI Agent Interactions - Frontend Developers - LogRocket Blog
Peter Aideloje