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Selected examples of improving products, delivery and customer experience, with the context behind the results.

Featured case study

Sustaining quality across two mobile apps and their content delivery platform.

The Economist app, the Espresso app and the platform behind them: regression for the flagship app went from 4–5 days to 1–2 hours of automated test execution, while collaboration, layered automation, platform integration testing and physical-device coverage helped sustain ratings of 4.9 on the App Store and 4.8 on Google Play.

Context
The Economist · 2021–2025 · Senior QA/QE Manager, mobile and content delivery
Result
Regression before a release of The Economist app went from 4–5 days to 1–2 hours of automated test execution, while ratings of 4.9 on the App Store and 4.8 on Google Play were sustained.

Quality & scale, Quality engineering, Test automation, Integration testing, Device testing

  1. Case study 02

    Clearing the way for a release train at an AI-native language-technology platform.

    Code changes lost much of their time to manual handovers and constant rebasing. I measured where the time went and planned a release train. In QA’s part, which I lead, the share of Playwright test runs passing without a retry roughly doubled; the train itself has not run yet.

    Context
    An AI-native language-technology platform · 2026 · Head of Customer Trust
    Result
    Between August and late September, the share of Playwright test runs that passed without a retry roughly doubled, while more tests checked each build. By early October the Playwright test stage took less than half as long as in August and September.

    Quality & scale, Test reliability, CI/CD, Delivery flow, Engineering leadership

  2. Case study 03

    Modernising quality engineering at a UK property-technology company.

    Leading QA across the UK and EMEA, I drove an automation transformation spanning desktop and API testing. We replaced legacy TestArchitect automation with FlaUI, reduced regression execution from 15 hours to 1–2 hours, and introduced a Playwright API testing framework covering 100% of endpoints.

    Context
    Reapit · 2025–2026 · Head of QA, UK & EMEA
    Result
    The clearest outcome was faster regression feedback, supported by comprehensive API endpoint coverage and a more consistent approach to Quality Engineering across distributed teams.

    Quality engineering leadership, Automation modernisation, Desktop and API testing, Quality strategy and governance, Distributed team leadership

  3. Case study 04

    Making AI evaluations trustworthy at an AI-native language-technology platform.

    I reviewed the platform’s AI evaluations to make sure they tested the feature, not just the judges’ criteria. Improving unstable tests and assertions raised the pass rate from just over half to three in four within a month, and new dashboards made the evals’ effectiveness, time and cost, and the success rates of live user journeys, visible.

    Context
    An AI-native language-technology platform · 2026 · Head of Customer Trust, AI workflow quality and release confidence
    Result
    Within a month, the evals’ pass rate rose from just over half to three in four, and the failures that remained were known product issues rather than faults in the tests.

    AI evaluation, Test design, Test reliability, Observability, Customer trust

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