What needs to be done can and is almost always described in natural language.

Whether that is feasible is a different question (https://xkcd.com/1425/), but also can be described in natural language.

Here is something I tried with o3-mini:

> Create a program that takes an input image and can tell if there is a bird in it.

> ChatGPT said:

> Reasoned for 38 seconds

> Below is an example in Python that uses TensorFlow’s Keras API and a pre-trained ResNet50 model to classify an input image. The code loads an image, preprocesses it to the required size, obtains the top predictions, and then checks if any of the top labels appear to be a bird. You can expand the list of bird keywords as needed for your application.

> python code that works

If you take the critical view, you can always find a way to find an exception that will fail. I can see many happy cases which will just work most of the time, even with the currently available technology. Most of the programming work done today is putting libraries and api services together.