Welcome: Modernizing Quality Engineering While AI Rewrites the Rules
Practical guidance for QE modernization in a fast-changing AI landscape
Quality Reimagined
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.
Start here: the QE Discovery Framework
Most QE teams are about to invest in AI tooling without knowing where the effort actually goes. The Discovery Framework fixes that.
It is a structured walkthrough that maps your testing operation across all ten lifecycle stages, every test type, and every release type — so you can see exactly where AI would deliver the most impact before you spend a dollar.
The framework includes:
A routing section so you only complete what is relevant
Full and lightweight lifecycle assessment templates
An “art of possible” comparison for every lifecycle stage
A priority matrix to sequence where to invest first
A results summary template you can take to your CTO
Subscribe and I will send you the framework directly. It is free.
What else 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.
Other starting points
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) and 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, and 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.