Senior Consultant @ TTC Global | Data and automation testing

Melbourne, Australia
Joined June 2026
Now that the 3rd part is psublished, a repush of the series as a whole. This last month has been about the 3 part series about testing in the age of GenAI. The series uses the concepts of induction and maps them onto the traditional challenges of testing; then performs a deeper
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dive exploring how these shift and change once machine learning / generative AI is introduced. The last part is thin on philosophy, using the toolbox built in the previous parts to offer practical grounded advice on, well, testing in the age of GenAI.
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If you're just in it for the practical advice, the 3rd part can be read as-is (it begins with a short recap for relevant context). If you’re curious about more abstract discussions, I’d recommend starting from part 1 and working your way up from there. pthenq.io/blog/series/at-the…
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New blog post, wrapping up our series on testing in the age of GenAI. Surprisingly, this one actually tells you about testing in the age of GenAI! It's thin on philosophy, overwhelmingly practical piece. You can even read this one as-is if you'd like. pthenq.io/blog/series/at_the…
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New blog post, continuing our Testing in the age of GenAI series. In part 1 we asked: can we justify projecting from a few passing tests to "the system works"? Hume says no. Now for part 2, where we concede and say, fine, let's just assume we can. What then?
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But wait, even worse things are yet to come: Once you throw GenAI into the mix, the rules it lands on are alien to human rationality. Every tactic and implicit assumption you've built up over a career was tuned for systems written by people who think like you.
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New LinkedIn article on why agents need their own data layer, why you can't prompt your way out of this one, and what implications this has for testing, quality and assurance. Short and concrete, this isn't my personal blog endless walls of text. lnkd.in/p/gSihFXHb
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New blog post, starting a 3 part series about testing in the age of GenAI through the lens of induction. Most of this part will be an analysis of Hume's riddle of induction, examination of what this teaches us about testing, and setting things up for the series as a whole.
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Hello everyone! 👋 The 231st issue on #SoftwareTesting is out. 👉 softwaretestingnotes.substac… Great articles and resources by @YaronAssa, @buger , @TestAndAnalysis, @hexdee606, @artofvision, @OLeij and more ! 👏 #QA #testing
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New post on the blog: What the surprise exam paradox (and Gödel's theorems) has to do with a green risk register, why the 15% buffer line is a category error, and why "we'd have found it by now" is the most expensive sentence in project management.
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New blog post, this time using Susan Wolf's "Moral Saints" to give you a rigorous, well structured, academically respectable licence to hate your coworkers. What could be better?
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New blog post, harnessing the anti-rational, amphetamine fuelled philosophy of Nick Land to celebrate the under-utilised practice of exploratory testing. It's gonna be lots of fun (and lots of rats, as Land is... special that way) pthenq.io/blog/the_rat_in_ex…
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New post in the blog, asking whether GenAI can be said to know anything, from an epistemological point of view. First we build a toolbox: the classic definition of knowledge, the ways it failed, and the concept of sensitivity that came out of the wreckage.
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Then we borrow from evidence law to turn the abstract into something more concrete. Armed with that, we unpack "does AI know" into terms you can actually argue about, and argue we shall.
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