In this op-ed from June 1, 2026 on CIO-Online, Olivier Rafal (Consulting Director Strategy at WeNvision, SFEIR group, former editor-in-chief of Le Monde Informatique) argues a paradox: in the age of AI, software engineering changes everything… and nothing changes.

What changes is the operating model. Roles are being redefined: the Product Owner shifts from backlog breakdown to generating context usable by AI; the developer moves away from writing code to frame, steer, and review agent execution; QA can define expected proof upfront. Structures evolve from "double pizza teams" (eight-person hand-off chains) to "sandwich teams": a tight pairing of a business expert and a tech lead, both AI-augmented, with other skills in support. At Sfeir, "this pair now drives roughly 80% of the production chain," the remaining 20% (architecture, data governance, security) being centralized. The formula sums it up: "the issue isn't a tooling issue, it's an operating-model issue."

What doesn't change is the discipline of the cycle. The SDLC phases — define, build, verify, deploy, maintain — remain identical; AI abolishes none of them, it intensifies them. "All the slack that human pacing used to absorb, however imperfectly, becomes, at AI speed, industrial-grade defects" — like sport, whether amateur or professional. Hence three inviolable gates (specification, planning, delivery review), validation by proof, and systematic capitalization that cuts correction iterations by 30% after about ten cycles. Guiding principle: "the faster the execution, the stricter the framework must be." The harness frames the agents; vibe-coding is judged untenable in the enterprise.

Third pillar: governance, FinOps, and value-driven management. AI costs are variable and recurring (~€10/hour per augmented role); as with cloud in the 2010s, the shift is from flat fee to usage-based billing. FinOps does not aim to cut costs but to "optimize tool efficiency," relating cost to value (time-to-market, features, performance, eco-design).

Conclusion: acceleration makes the fundamentals non-negotiable; the challenge is first and foremost organizational and cultural, not technological. Without a healthy business relationship or collective discipline, an AI-powered SDLC only amplifies the problems.