Welcome: Modernizing Quality Engineering While AI Rewrites the Rules
Practical guidance for QE modernization in a fast-changing AI landscape
If you lead Quality Engineering in a growing mid-market company or a large enterprise, you can feel it.
The pace of change is rising. AI is accelerating how software gets built. The old assumptions about testing, automation, and release confidence are being stressed. Some patterns still hold. Others are breaking.
I am not going to pretend there is a finished playbook.
Quality Reimagined is a set of field notes and practical frameworks for QE leaders modernizing their organizations while the landscape shifts. The goal is to help you make good decisions with imperfect information, and build an operating model that stays resilient as capabilities evolve.
What you will find here
Decision frameworks for modernization when the path is not obvious
Operating model patterns that scale across teams and portfolios
Governance and controls that preserve confidence as change volume increases
Quality signals leaders can trust for real release decisions
Practical experiments and lessons learned translated into enterprise action
Conversations with industry leaders
I will also be speaking with QE and engineering leaders, SI partners, and testing tool builders about how they are navigating this transition inside real organizations.
No hype. No vendor theatre. The focus is what is changing, what is not, where teams are getting stuck, and what patterns are emerging that actually scale.
Recommended starting points
If you want the curated roadmap of cornerstone essays, start here.
To ground the conversation, start with the QE Modernization Diagnostic.
If you prefer practical assets you can use immediately, browse the QE Leader Toolkit.
If you want a lightweight sanity check, reply after you review the diagnostic with:
your section totals (A–E)
your top constraint (one sentence)
I will respond with a few priority moves to consider.
What I mean by modernization
Modernization is not predicting the future. It is building a QE system that can adapt:
faster feedback loops
clearer ownership and fewer handoffs
automation that stays worth maintaining
governance that matches delivery reality
reporting that supports release decisions under uncertainty
Transparency
This publication is vendor-neutral by default. If I ever include any financial relationship tied to a recommendation, it will be disclosed clearly in the post.