The debate around the eventual adoption of AI for software engineering tasks is over: it’s happening, and more businesses will adopt Large Language Model and Prompt Engineering in the future for software development needs. As modern day Software Engineers, what pivots should we make, in our skillset to transition accordingly?

Having spent a significant time in my career in Software Quality Assurance, I assert that many skills which make up the prototypical ‘tester’ are those that will become more relevant to all Software Engineers in the future. Solid code reviews, leveraging test-driven development, validation and automation of acceptance criteria in DevOps, measuring for success in Production; these are the skill sets that developers can enhance today. Combining these skills, with robust CICD systems, means that our “value” as engineers can come from helping businesses adapt to a high-frequency stream of AI submitted changes, and validate that the quality of those submissions is sound.