As I said elsewhere: The future of tools like github is a platform for manual testing, where you write a prompt, the AI proposes a change and you can experiment with the UI and attach notes for the next iteration. AI can take user requests, prioritize, aggregate into tickets, and turn them into pull requests.

For a lot of end users, this may be enough, no programmers will be needed to get software built and shipped. For the rest, it lets programmers fill the remaining gaps, doing the manual testing to make sure the system works correctly, test for regressions and make sure the LLMs add those to the test suite, and then manage monitoring the rollouts. The bulk of development work going forward is manual verification that the LLM understood the user request correctly.

I'm not as sure that this idea of plugins will pan out; AI will want to make changes to support what it produces.