Using AI in Quality Coaching

If a team approaches you with questions on how AI can assist in testing, grab it! Any motivation to improve testing is a plus, and if AI is the tool to help improve their test efforts, then use it.

Problem, Experiment, Observe, Evaluate

There are many ways to use AI to help a team. The key is to realise that AI is a tool like any other. A quality coach can assist the team in taking a systematic, experimental approach to adopting AI.

The heuristic "Problem, Experiment, Observe, and Evaluate" supports such an approach.

Identify the Problem you want AI to help solve

While a team may come to you with a tool in mind, it's important to understand the problem the team wants to solve. What exactly do they want AI to help them with? Teams typically ask, "How can I improve test coverage?" and "How can I reduce the time to write tests?" So, this is an excellent place to start. I'm sure, in time, you will find many other problems that AI can help solve.

Once you understand the problem, ask the team how they will measure success. Will it be improved test coverage, reduced test creation time, or faster test creation?

💡

Avoid focusing too heavily on quantitive data if the team doesn't have existing baselines. Qualitative data is sufficient for team focused early stage experimentation.

If the team has quantitative data around an agreed-upon metric, you can use that. Otherwise, qualitative data is acceptable. For example, agreeing to a team discussion on the pros and cons of an experiment and coming to an agreed-upon outcome may be the more appropriate 'definition of success' and nicely circumnavigates the need to collect baseline data, which may be overkill in early-stage experimentation.