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I think it will be more like airline pilots with the addition of autopilot. Maybe you could write whole services, and networks of services with AI, but you need

I think it will be more like airline pilots with the addition of autopilot. Maybe you could write whole services, and networks of services with AI, but you need engineers to be the guiding hand. Engineers will always be better at using AI to build systems than non-developers. Also, it’s worth pointing out that AI is using existing data. If a new iOS API comes out, the AI will need code bases with it already implemented to be able to train with it. So in my mind, it will hurt the junior developers doing grunt work more than general devs. I think no code/low code products are more of a risk to hurting devs than AI.

Nathanba 4y ago
depending on how advanced this AI will be, it could learn from a few samples and the API docs, possibly itself designed to be optimally consumed by AI. If I knew that AI would consume my custom programming language docs then I would make sure that each API is used once in some kind of sample code so it can give answers to everything. Plus, that's a sensible thing to do anyway.
- reducesuffering 4y ago
  Even better (or worse), tell your AI/LLM to output sample uses of the project to be training data for other AI/LLM. Probably ends up being a knowledge transfer protocol.
- devmunchies 4y ago
  Yeah I was actually thinking that we may see API maintainers publish a lot more sample code with lots of different scenarios for AI to train on. Similar to how JavaScript libs publish a Typescript type def file for people using Typescript.
- larve 4y ago
  Seeding gpt (or using copilot) on snippets of your code is extremely effective. I often paste a function of my codebase before asking code questions, as in: “here is an example of a product class, generate the swagger spec for a user crud api” and it will infer how and even what kind of fields our user class has, without having seen it.
sesuximo 4y ago
Maybe of interest https://www.cnn.com/travel/article/single-pilot-planes/index.html https://www.cnn.com/travel/article/single-pilot-planes/index...
kitsunesoba 4y ago
Additionally, I would expect that AIs wouldn't fare as well in situations where footguns abound, specialization is high, and there's a much smaller body of code to learn from — think things like hardware drivers written in C or C++ or embedded firmware with restricted resources, which is much less forgiving than e.g. CRUD web app backend written in Python.

Nathanba 4y ago

depending on how advanced this AI will be, it could learn from a few samples and the API docs, possibly itself designed to be optimally consumed by AI. If I knew that AI would consume my custom programming language docs then I would make sure that each API is used once in some kind of sample code so it can give answers to everything. Plus, that's a sensible thing to do anyway.

reducesuffering 4y ago
Even better (or worse), tell your AI/LLM to output sample uses of the project to be training data for other AI/LLM. Probably ends up being a knowledge transfer protocol.
devmunchies 4y ago
Yeah I was actually thinking that we may see API maintainers publish a lot more sample code with lots of different scenarios for AI to train on. Similar to how JavaScript libs publish a Typescript type def file for people using Typescript.
larve 4y ago
Seeding gpt (or using copilot) on snippets of your code is extremely effective. I often paste a function of my codebase before asking code questions, as in: “here is an example of a product class, generate the swagger spec for a user crud api” and it will infer how and even what kind of fields our user class has, without having seen it.

sesuximo 4y ago

Maybe of interest https://www.cnn.com/travel/article/single-pilot-planes/index.html https://www.cnn.com/travel/article/single-pilot-planes/index...

kitsunesoba 4y ago

Additionally, I would expect that AIs wouldn't fare as well in situations where footguns abound, specialization is high, and there's a much smaller body of code to learn from — think things like hardware drivers written in C or C++ or embedded firmware with restricted resources, which is much less forgiving than e.g. CRUD web app backend written in Python.