Until counting machines got ubiquitous, banks in India would count notes/bills by weight as well.

It wasn't very precise but you could move a lot of money in ball park with this method. Atleast internally across branches.

I've had this many times during interviews.

If you had a chat with me through lunch on some technical intensive questions, It would be a breeze. I could not only answer them, I could list limitations, how to address them, and I could even come with a working plan on how I could get it done.

Do the same in an interview, I will freeze.

Oh well had a talk with a director at office. He says, instead of using AI to get more productive, people were using AI to get more lazy.

1)

What he means to say is, say you needed to get something done. You could ask AI to write you a Python script which does the job. Next time around you could use the same Python script. But that's not how people are using AI, they basically think of a prompt as the only source of input, and the output of the prompt as the job they want get done.

So instead of reusing the Python script, they basically re-prompt the same problem again and again.

While this gives an initial productivity boost, you now arrive at a new plateau.

2)

Second problem is ideally you must be using the Python script written once and improve it over time. An ever improving Python script over time should do most of your day job.

That's not happening. Instead since re-prompting is common, people are now executing a list of prompts to get complex work done, and then making it a workflow.

So ideally there should be a never ending productivity increase but when you sell a prompt as a product, people use it as a black box to get things done.

A lot of this has to do with lack of automation/programming mindset to begin with.