7 hours ago
- Automatic programming with AI accelerates software development but often produces code with lower structural quality than the best hand-written code, though it can match or exceed average human-written code.
- There is a tradeoff between quality and development speed; using AI can reduce project timelines from months to weeks, but quality may suffer.
- In software QA and testing, LLMs enable a new form of automation that does not compromise quality, overcoming limitations of traditional testing such as coverage gaps and integration complexity.
- The author describes a methodology where an AI agent is instructed via a markdown file to perform manual QA on new releases, including checking commits, running specific tests, and identifying impacted areas.
- This approach can evaluate software from a user perspective, catching surprising, undocumented, or sloppy features that would otherwise require manual inspection.
- Automatic QA has the potential to raise the quality bar for new releases and compensate for the lower quality of code produced at high speed with automatic programming.