Its not about writing easy entry programs, it’s about writing code robustly.
Writing out test code where tests are isolated from each other, cover every edge case, and test every line of code, is tedious but pays dividends. AI makes it far less tedious to write out that test code and practice proper test driven development.
A well run dev team with enough senior people that manages the change properly should increase in velocity if they’re already writing robust code, and increase in code quality if they’re not.
AI makes it far less tedious to write out that test code […]
Completely disagree.
In my experience, LLMs constantly generate bad code that needs to be thoroughly checked, to the point that writing by hand is more practical.
We use copilot literally every day and it’s extremely helpful, literally not a single developer at our company disagreed on the most recent adoption survey.
Maybe you’re trying to use it to do too much, or in the wrong way?
Its not about writing easy entry programs, it’s about writing code robustly.
Writing out test code where tests are isolated from each other, cover every edge case, and test every line of code, is tedious but pays dividends. AI makes it far less tedious to write out that test code and practice proper test driven development.
A well run dev team with enough senior people that manages the change properly should increase in velocity if they’re already writing robust code, and increase in code quality if they’re not.
Completely disagree.
In my experience, LLMs constantly generate bad code that needs to be thoroughly checked, to the point that writing by hand is more practical.
We use copilot literally every day and it’s extremely helpful, literally not a single developer at our company disagreed on the most recent adoption survey.
Maybe you’re trying to use it to do too much, or in the wrong way?