On the first day of Software Engineering 101, you learned about the SDLC — the software development life cycle. You learned that there is a whole lot more to producing quality software than writing some code and deploying it to production. We’ve studied the SDLC every which way, and we know where and how time is spent within it.
The coding is the most interesting part of the SDLC. It is one of a number of steps in the process, but it’s the part that takes up the biggest chunk of the SDLC schedule.
Agentic coding has changed all of that. I wrote earlier this year about the impacts upstream of coding when writing code is no longer the bottleneck. Here I want to think about the impacts for developers downstream — what we can expect to happen after the code gets written — when agents write the code.
Downstream from coding
Even before agentic coding, we developers spent far more time reading and maintaining code than we spent writing it. Maintaining the code and supporting the product has always been the major lifetime cost of the project as a whole. Now that the bottleneck has moved away from the coding process, we will look for ways to apply AI agents downstream of writing code. So, just as agentic AI has made writing code trivial, we can expect it to improve the remaining 60% to 70% of our job as well.
