Why Software Factories Fail
"Read the Code!" is one of the key ideas from Dex Horthy's talk "Why Software Factories Fail".
The author touches on a very hot topic right now: we are actively pushed to put AI-generated code into production, build software factories, and eliminate the human bottleneck from the process. And all of that would be great if, at the same time, the overall quality of software products wasn't going down and the number of incidents wasn't going up.
Dex explains this phenomenon by pointing to a fundamental limitation of current models: they can't maintain and improve the quality of a codebase over time. Models are trained to solve the issue and pass the tests. There is nothing there about good architecture, clean code, or future maintainability.
If the model knew what good code looks like it would write it in the first place.
What to do with that? Dex suggests to do the following:
🔸 Make Product Review: align goals, check mockups, etc.
🔸 Do System Architecture: establish clear component boundaries and API contracts.
🔸 Perform Program Design: define types and method signatures, test approach, program layout, and dependency stack.
🔸 Implement by Vertical Slices: build features vertically, reducing the scope of what an agent can change in a single iteration.
So, it's all about shifting review left to earlier stages and focusing more on architecture and program design (I described similar ideas about code review here). And then let agents make small changes that engineers can actually understand and review.
And yes, we still need to review the changes.
#engineering #codereview #ai
"Read the Code!" is one of the key ideas from Dex Horthy's talk "Why Software Factories Fail".
The author touches on a very hot topic right now: we are actively pushed to put AI-generated code into production, build software factories, and eliminate the human bottleneck from the process. And all of that would be great if, at the same time, the overall quality of software products wasn't going down and the number of incidents wasn't going up.
Dex explains this phenomenon by pointing to a fundamental limitation of current models: they can't maintain and improve the quality of a codebase over time. Models are trained to solve the issue and pass the tests. There is nothing there about good architecture, clean code, or future maintainability.
If the model knew what good code looks like it would write it in the first place.
What to do with that? Dex suggests to do the following:
🔸 Make Product Review: align goals, check mockups, etc.
🔸 Do System Architecture: establish clear component boundaries and API contracts.
🔸 Perform Program Design: define types and method signatures, test approach, program layout, and dependency stack.
🔸 Implement by Vertical Slices: build features vertically, reducing the scope of what an agent can change in a single iteration.
So, it's all about shifting review left to earlier stages and focusing more on architecture and program design (I described similar ideas about code review here). And then let agents make small changes that engineers can actually understand and review.
And yes, we still need to review the changes.
#engineering #codereview #ai