Ask HN: Has AI coding changed who builds your internal tools?
In a large company, a dedicated team might build an internal tool that dozens of other teams use. If your team needs a feature for its own workflow, you have to explain the use case, agree on how it fits into the shared tool, and wait for it to get prioritised.
With AI coding tools, it might now be faster for the team that needs the feature to build and maintain its own tool or completely scratch the tool and rebuild it if need. I’m curious how that plays out once the tool has been in use for a while.
So is paradigm shifting where we remove centralisation of building internal tools and let teams decide?
I think there are 2 different types of internal tools that are being defined as AI gains traction.
The first is what you mentioned in this post. Tools that are widely used, built and maintained by a dedicated team, and carry highly sensitive data or act as critical infrastructure.
The second is small, simple tools built by an individual or team to address a very specific problem in a tailored way. The first type doesn’t need to change. The same dedicated team can keep bringing their knowledge and abilities, and the use of AI can broaden that across the organization. The second type is something that is owned by a specific person, or a team. These should not be handed off to an IT or engineering team to maintain, and should be built, owned, and maintained by the user.
I work on an open-source project called Pando (https://github.com/trypando/pando) that helps give these sort of things a place, and makes it easy to track what users are building by enabling them to take ownership over their apps.