Talk deck by **Dorra Bartaguiz** (CTO, **Arolla**), presented at the **Dev With AI** conference and published as a PDF on LinkedIn on **October 15, 2026**; **61 slides**, in French with examples in English. Thesis: when AI causes velocity to surge, quality is regained through tooled *craft* practices built around the model — *harness engineering*.
#harness engineering#velocity#code review
Dorra Bartaguiz — CTO d'Arolla (conseil et formation, « agentic software crafters ») ; slides de son talk Dev With AI publiées sur LinkedIn.
Third installment in the ADLC series: Williams turns testing into the specification in the only language the builder cannot contest. Where TDD is an optional quality practice for human-written code, it becomes the load-bearing trust mechanism of the entire lifecycle once agents write the code. Three "rail discipline" rules: separated authoring contexts (specs-only before implementation), mechanical freezing at the tool level (not the prompt), and adversarial audits ("does a test fail if the feature is deleted?"). Mutation testing is preferred over coverage percentage, which is Goodhart-able at machine speed.
Fourth installment in the ADLC series: Williams reframes code review as adversarial "prosecution" rather than collaborative evaluation. Charter agents to refute ("find what's wrong"), deploy single-lens reviewers with fresh contexts (correctness, security, contract compliance, spec alignment, test quality), act only on verified findings (reproduced by a failing test), and loop until two consecutive passes yield zero findings. Measure calibration by planting known bugs, mutation-testing style. Exit gate: zero open findings, two dry passes, green tests, empty test diff.