SFEIR article (in French) that formalizes an **AI-driven SDLC in 11 phases (0 to 10)** and argues that the industry is converging on it. Starting observation: in 2025, organizations added AI tools without transforming their operating model — hence a paradox of "everything changes… and nothing changes" (execution speed multiplies without a proportional gain). The real answer is not a choice of tools but a **redesign of the cycle** for machine-led execution. The SFEIR cycle rests on **three immovable human gates** (Define, Plan, Ship), automatic phases between them, and **two compounding moments** (Compound-1 pre-deployment, Compound-2 in production) that turn lessons into reusable rules. Three principles: **AI executes** (complete artifacts + proof of execution, never trusting the agent's claims), **the human retains control of intent**, and **the system learns cumulatively**. Measured results (a redesign from 6 months to 1 day, **−30% of iterations** after ten cycles) and claimed convergence with ADLC, Google, and DORA 2025.
Sixth installment on the ADLC: Williams describes the P7 "Distill" phase as the component that drives cost down on every run. Two halves: post-merge simplification (deduce after the code exists, not before — "deduplicating before the code exists is speculative") and lesson mining (a "lesson foundry" turns recurring findings into lint rules, skills, and new interrogation questions). Each lesson is paid for once, then demoted from expensive probabilistic detection to free deterministic prevention. The right unit of account is "cost per merged, verified change," and "flat cost is failure."
Product announcement from Stack Overflow (official blog) launching **Stack Overflow for Agents**, an *API-first* knowledge-exchange platform designed for the agentic era. Founding thesis: coding agents work **in isolation**, without access to a shared, verified knowledge base. Hence the **"Ephemeral Intelligence Gap"** — agents worldwide independently solve the same problems, wasting tokens and compute, then lose the solution at the end of the session; the same architecture patterns are rediscovered in a loop. Guiding principle: *"generating plausible answers has become cheap, but verifying which ones hold up in production hasn't."* Four-step workflow: **search first** (consume validated knowledge) → **contribute if a gap exists** (the agent drafts, the human approves before publication) → **verify** (results, modifications, context conditions) → **compound the signals** (votes, answers, verifications produce a consensus). Three machine-readable formats: **Questions**, **TIL** (debug traces), **Blueprint** (reusable patterns, highest quality bar). Trust rests on **community moderation** and **multi-agent verification loops**; humans claim ownership of their agent via Stack Overflow SSO (a "community anchor" tying the agent to a human reputation). Differentiated benefits: developers (fewer retry loops), AI labs (high-signal data for fine-tuning/eval), enterprises (**Stack Internal**, a proprietary knowledge layer with no data exfiltration).
#Stack Overflow for Agents#coding agents#knowledge base
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**.