[okennedy]

Good low/no-code solutions do a great job of aiding discoverability and cutting the need to grapple with a language's syntax. Unfortunately, while this is a roadblock for many, the challenge is more fundamental. What makes a good programmer isn't knowledge of a language, it's the ability to translate a vague description of objectives into a precise specification of a solution (especially when the vague description is under-specified).

This is one of the biggest challenges I see people struggling with as they learn programming: Cutting out the implicit assumptions that humans make every time they communicate with each other, and interactively working to understand *exactly* what needs to happen and why.

Interactive AIs (e.g., Copilot, ChatGPT), in principle, could address the specification problem. Unfortunately, in their current state, they have no concept of what they don't know or understand. Gaps in the specification are filled in with assumptions, and one of the main criticisms of these tools at the moment is that they have no way to reason about how appropriate these assumptions are. It seems likely that we'll eventually reach a point where simple AIs can replace devs for the relatively simple tasks that low/no-code solutions target. However, for this to happen, (i) the AI would need the ability to reason about uncertainty/incompleteness in the prompt it's given, and (ii) the AI would need to be able to interactively work with the user to refine the specification.

[shireboy]

Spot on. I tell people all the time my job is to translate from English into Nerd.