Observability in the Age of AI is an article by Charity Majors and Phillip Carter that speculates about the changes that observability stacks and engineering teams alike will face with an introduction of AI.

This is an article from the company, so of course you have self-promotion here, but there are also very good points:

- If you can compute the answer, you probably should compute the answer
- Often people use AI to try to close the gaps of data they do not collect, yet AI results would be also better if that data is present
- When talking about people, AI is better used as an additional reviewer rather than a creator

And one thing that is not directly related to observability, but has given me a lot of food for thoughts:

- We expect software will bifurcate into two categories: disposable code and the code that runs the world.

I've put direct quotes in italic.

#observability #ai