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Developers unimpressed by the early returns of generativeAI for coding take note: Software development is headed toward a new era, when most code will be written by AI agents and reviewed by experienced developers, Gartner predicts.
At Thoughtworks, we are strong practitioners of TestDrivenDevelopment (TDD). Naturally this leads to the question of how generativeAI can help with this technique. Paul Sobocinski writes a brief memo explaining how some of our teams have used TDD with GitHub Copilot.
Our industry is in the early days of an explosion in software using LLMs, as well as (separately, but relatedly) a revolution in how engineers write and run code, thanks to generativeAI. This means shipping sooner, observing the results, and wrapping your observations back into the development process.
Our industry is in the early days of an explosion in software using LLMs, as well as (separately, but relatedly) a revolution in how engineers write and run code, thanks to generativeAI. This means shipping sooner, observing the results, and wrapping your observations back into the development process.
A good next step is asking an AI assistant to generate unit tests, either for existing code or some new code (which leads to test-drivendevelopment). Unit tests are a useful exercise because testing logic is usually simple; its easy to see if the generated code is incorrect.
Software Development The biggest change we’ve seen is the growth in interest in coding practices; 35% year-over-year growth can’t be ignored, and indicates that software developers are highly motivated to improve their practice of programming. Yet here we are, and we don’t have ChatGPT or generativeAI in our taxonomy.
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