Not a fully formed thought, and apologies for the brain fart, but...
This post was inspired by an article on latent.space about how, first, human coding "died". Then now we're going to see the demise of the "pull request".
If you're not familiar, a pull request, or "PR", is a request to change some code in software, by introducing some new code that you have written yourself. So someone has to review that code, make sure it's all written "properly" and then approve or reject it.
Code can now be generated 1000x faster by AI. And AI generated code still needs to be merged into the main code. And if every chunk of AI generated code needs a pull request, that's thousands of pull requests to review by humans. We then become the bottleneck.
Then why not get AI to do the review? It can do it much faster than humans. The @latentspacepod article asks why have pull-requests at all? It was AI generating code. Why have the same AI look at it again?
Personally, I disagree, for now anyway. I think we're in a transition period where humans still need some control. And while we don't write code anymore, and I do believe PRs should be reviewed by AI, I think humans should still manage the PR agents - for example defining rules for the review agents to follow, checking that they did follow the rules, etc.
But that's transitional, and besides my point. What I do agree with in article is where humans will be needed. And where we're needed is further up the software development chain, into the realm of requirements and testing.
Code is not created in a vacuum. It is created to automate work. It is created to fulfill a specific requirement. And this requirement will still be created by humans.
And if we can be clear about what we need - the requirements - then we can also run automated tests to check that the code meets our requirements.
If code is cheap, and instant, and humans stop become the bottleneck to deploying code, what does this mean for code ownership?
It means it doesn't make sense to "own" code anymore. So what's worth owning?
Spec and Data.
How your organisation runs, all its rules, all its goals. These make up your software specification (spec).
All the information your org collects, all the information it needs to run. That's your data.
If you have a clear, tight, spec. And a database that holds all your data. Then you can reproduce all the software that you need instantly.
An AI can read your spec. Then create automated tests against that spec. Generate all the code needed. Connect to your data. Test the code against the spec. Verify that it is all correct. Deploy your code. And hand you the keys (login) so you can drive it straight away.
This has several further implications:
- Should an org's investment now turn to speccing and testing?
- Should we work on a more standard way of defining spec and data schemas?
- What does this mean for software development agencies, if producing and reviewing code is not needed anymore?
- When an enterprise buys from Google and Microsoft, what are they really buying, if it's not software anymore?
Definitely more questions than answers. And things will continue to change fast for the software development industry.
And for organisations - if you already create and document great spec, and have automated tests in place, and have good data policies, then you're in a great place.