This is where I publish research notes, technical explainers, and commentary on software engineering, computing education, C++, AI-assisted development, and the practice of building software.
Research notes
Methodological decisions, experiments, literature reflections, study design, and work in progress. These posts distinguish evidence from interpretation and document uncertainty where it exists.
Education
Technical explanations and learning material designed to build useful mental models without hiding the behaviour that matters.
Commentary
My interpretation and opinion on developments in software engineering, research, AI, and computing education. These pieces are arguments, not research findings.
What to expect
- Research notes separate evidence, method, interpretation, and uncertainty.
- Technical explainers include runnable examples, measurements, or concrete mechanisms wherever possible.
- Commentary makes the argument explicit and does not present opinion as a research finding.
Latest writing
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From Prediction to Evidence: Teaching False Sharing as an Observable System
A practical false-sharing experiment showing how prediction, measurement and model revision can turn performance folklore into systems reasoning.
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Teaching Performance Without Folklore: Why Simplified Models Need Somewhere to Go
Why systems education needs simplified models that learners can test, revisit and progressively refine as their understanding develops.
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Why Systems Programming Feels Hard, and How to Make It More Observable
Why systems programming feels difficult, what computing education research says about mental models and visualisation, and how observable experiments can help learners reason about hidden runtime behaviour.
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What Actually Happens When Your C++ Code Touches Memory
A practical look at what happens when C++ code touches memory, from object layout and cache behaviour to undefined behaviour, using runnable experiments and measured evidence.
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The beginning of the journey
Why this site exists, how I approach learning and technical work, and why engineering, research, and education belong together.