Insights

Research for regulated engineering teams.

Working references from Certance Advisory: what we measure, what it costs, and what to change first. Every figure traces to a primary source.

October 2026 · Quality engineering

Quality assurance vs quality engineering: what changes when AI writes the code

What a passing pipeline proves, what it cannot, and why the difference decides whether AI-written code deserves trust.

Read the article

September 2026 · DORA

Test evidence under DORA: what Articles 24 and 25 require

DORA's first supervisory year turns on evidence. What Articles 24 and 25 ask for, where automated test suites go blind, and how to map coverage to business risk.

Read the article

October 2026 · The Standard

The Certance Standard: quality for agentic software development

Edition 2026.6: fourteen chapters, from the five merge gates to testing AI inside the product, and the twelve statements, for teams where AI agents write most of the code.

Read the Standard

September 2026 · Fifth edition

AI token efficiency: how teams cut Copilot and Claude spend

Cut what your coding agents spend, keep the quality, and make the bill predictable on GitHub Copilot and Claude Code: shorter agent sessions, a warm prompt cache, filtered tool output and the right model for each task.

Read the article
July 2026 · Research

AI maturity assessment: why fluent teams cannot show return

Adoption climbs, acceptance rates look healthy, and the board asks what the licences return. The four findings that recur in almost every team we assess, why they happen, and the seven dimensions that measure them.

Read the article

New pieces go to subscribers first, together with the full AI Token Efficiency Guide.

Subscribe