DORA 2025

DORA 2025 measures a split result: AI adoption correlates positively with delivery throughput and product performance, and negatively with delivery stability when the foundations do not keep up. The report states the mechanism as amplification. AI reflects and accelerates the state of the organization it enters, multiplying the ones that already have foundations and speeding up the disorder of the others.

Paula Hingel's six-stage guide for Augment Code, published 8 June 2026, takes that negative correlation as its starting point and reads the imbalance as the symptom of uneven adoption carried out without redrawing review boundaries. Process maturity counts for more than the tool. Her testing stage names circular validation, AI-generated tests confirming AI-generated code, as the central risk.

SFEIR cites the report eight days later as one of four convergent sources behind its eleven-phase SDLC, next to the ADLC and Google's whitepaper on the new SDLC. Its own diagnosis of 2025 is the amplifier finding restated from the practitioner side: organizations deployed AI tools without transforming their operating model, and execution speed multiplied without a proportionate gain.

Which foundations count is left open. At Adeo and Decathlon, five years of platformization, decomposing the information system into business domains exposed by API, produced the substrate an agentic model expects without having been built for it. Matthieu Grymonprez draws the corollary: whoever has not finished that transition has two revolutions to run at once. The measurement locates the gap and stops there.