It’s some time since I added a blog post to this site. Since my last article (3 years ago), my role has changed and I’ve been less of a hands-on tester than before. I’m still involved in helping Software, DevOps and Quality Engineers, evaluating new products and trying to find ways to make their lives easier investigating tool integrations and more recently AI.
AI seems to be on everybody’s lips so I was keen to separate the myth from reality when I took part in a hackathon hosted by Google with a team from Lloyds Banking Group’s Quality Engineering Centre of Excellence (QECoE). The hackathon focused on exploring ways that generative AI could be applied to help in the workplace.
Our team’s challenge was to develop an application that could enhance quality assurance processes by assessing and providing feedback on testing documents compared to “golden standards”. We created separate golden standards for different types of test plans like accessibility, functional, and performance testing. The application we built used Python to make API calls to Google’s Gemini Pro large language model, with a Streamlit web frontend. When a user uploads a document, it is compared with the relevant golden standard checklist and feedback is provided.
Since many of us weren’t experienced coders, we used AI assistants like ChatGPT and Claude for help with coding the application. Their code completion capabilities were amazing! After the hackathon, we added chat functionality so the app could interactively guide users on improving their documents based on feedback.
Our innovative solution allowing live assessment of document quality against configurable golden standards won in the “documentation” use case category. Presenting it live to the judges was a great experience.
You can read more detail here:
LinkedIn: Producing “Gold Standard” Documentation using AI
