Here is what I do when I write code these days. I describe the change I want to one agent and let it write the code. I hand the result to a second agent, configured as a reviewer, using Bryan Finster’s Agentic Dev Team plugin for Claude. The reviewer reads what was written and gives […]
The Wrong Human-in-the-Loop Read More »
A few years into my QA career, my manager asked if I had any tips for handling support tickets efficiently. I said of course, and put together a wiki page (this was before Confluence removed wiki from companies, anyways) describing exactly how I had my desktop set up. Most people never followed it. Some said
Inconsistent AI results come from a lack of shared understanding Read More »
Session two closed with a question I couldn’t answer.1 When a product scores 78% on a given metric, what tells you whether that’s good enough to ship? I flagged it as something session three would probably address, and it did, though not in the way I expected. The question can’t be meaningfully answered until you’ve
The anatomy of a metric Read More »
You know the feature inside out. You have tested it, broken it, rebuilt the test suite around it twice. So you ask the AI to generate a few test cases. Save yourself twenty minutes. What comes back looks reasonable. The structure is right. The naming conventions are close enough. Then you start reading. The first
You were promised speed. You got a new job instead. Read More »
I’ve been seeing a lot of posts on LinkedIn recently that make the same claim: speed of writing code was never the bottleneck in software engineering. The real bottleneck was always thinking, choosing the right thing to build, understanding the problem. AI has just made that painfully obvious. I partly agree, but the framing is
Why the bottleneck was never just about thinking Read More »
Sometimes I despair about the QA profession. Not because the work is hard, or because quality is complex. Both of those are true, but they always have been. What gets to me is where so much of our collective energy still goes. We have much bigger fish to fry. We have the tools to do
AI did not break testing Read More »
That day I rage quit my project It finally fell apart over a UI reskin. I had an application that mostly worked. It was not polished, but it was coherent, testable, and good enough to keep moving. When I asked the AI to reskin it using my brand colours, what I expected to be a
Stop vibe coding before you delete your repo Read More »
AI has been the background noise of every software conversation lately. Some people treat it as a superpower that will solve everything. Others point to low-quality AI slop online and see it as the end of original thought. I am somewhere in the middle. I use AI a lot, and I trust it for some
AI, curiosity, and a little procrastination Read More »
Every tester has had that moment. You look for guidance on a current problem and end up with advice that feels twenty years old. You find articles on writing test cases in Excel, or long arguments about whether automated testing can ever replace manual testing. It is a little surreal. It is easy to assume
The reason so much testing content feels stuck in the past Read More »
The experimenter’s mindset beats the automation mindset A few months ago, someone at a conference asked me whether I thought testers would still have jobs in five years. It wasn’t a joke. You could hear the anxiety in the room, because the arrival of generative AI has reignited a very old fear in our industry:
Why the Experimenter’s Mindset Outlasts Automation in Software Testing Read More »
