> Someone asks you to add a feature to an existing program
While I empathize with the tone, even before AI the creativity was largely at the feature definition step, not in the implementation.
Outside of the very few computer scientists working on novel algorithms, the vast majority of software development is a mapping problem between the feature request and the mundane technical details, something repeatedly (and correctly) mentioned here in the context of FAANG algorithm fixated interviews. This has now largely been automated by LLMs
What is left is just creativity part - defining the use cases and features to develop in the first place. But the corollary is that software engineers that start after the requirements have already been defined are obsolete, which is a sobering thought for any of us in that vocation.
Seems to me that feature requests are not all that unique either.
Seems to me you can get feature requests from user feedback.
I also expect someone will figure out a way to have AI "use" your software and suggest features
This is not true. First of all, not all software is written in the context of a FAANG company with “feature requests”. Secondly, writing software is similar to the process of design, this comment reads like “the vast majority of handbag design is mapping problem between features and leather”, ignoring that both the design and implementation can be rewarding to work on. Eg. I’m working on a program for myself and the overall architecture of the program as well as some parts of its implementation are clever and compose well to make the codebase a joy to work in. I am not simply “mapping features to mundane technical details”. It is as much art as the skillfully hand-crafted handbag.
I always think that stuff is funny because it clearly comes from a place of having only worked at faang-level-esque companies. I’ve only ever worked at messy mid-size software companies and have never once had a legit product manager guiding feature work, it’s generally been up to the developers to figure out what needs doing
> Outside of the very few computer scientists working on novel algorithms,
It's a quite a bit broader than that: for instance most of science and engineering is heavily supported by simulations (very useful when the system you're considering doesn't have perfect spherical or cylindrical symmetry), and there is still tons of algorithm development going on. The world is vast, and thus so is the domain of programming.
And halfway through 2026, AI has become a very interesting and helpful partner in algo research too. If it does continue to pull away and zip off to ASI land, hopefully we can leverage the resulting magical technology and catch back up with it...