Machine Learning

ML code generation vs coding by hand  ↦

Matija Sosic (Co-founder & CEO at Wasp) shares what he thinks programming is going to look like in the near future.

When thinking about how ML code generation affects the overall development process, there is one thing to consider that often doesn’t immediately spring to mind when looking at the impressive Copilot examples. The question is - what happens with the code once it is generated? Who is responsible for it and who will maintain and refactor it in the future?

Although ML code generation helps with getting the initial code written, it cannot do much beyond that - if that code is to be maintained and changed in the future … the developer still needs to fully own and understand it.

Generated code accepted blindly is creating tech debt!

In other words, it means Copilot and similar solutions do not reduce the code complexity nor the amount of knowledge required to build features, they just help write the initial code faster, and bring the knowledge/examples closer to the code (which is really helpful). If a developer accepts the generated code blindly, they are just creating tech debt and pushing it forward.


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