alt Hacker NewsExcept as every damn AI app says: AI is prone to making mistakes. If AI deskills you with a non-zero chance of getting the problem wrong, that seems deeply, profoundly bad.
You can type the same long division problem into a calculator 65,000 times and you will get the right answer 65,000 times.
Can AI get even CLOSE to that?
Computing tapped out on sources of leverage for solving deterministic problems a while ago. Computers got fast and our algorithms got really good.
We're on to the next frontier, and it's a bit weird. Jagged frontier and all. But it's opening up new worlds.
Luckily loads of problems are amenable to a non-deterministic approach - even better, many have lots of solutions. SRE is in that bucket. There are as many ways to SRE as there are SREs
(source: one of the first SREs at Uber, co-invented Chaos Engineering as a sub-branch of SRE, hosted first chaos eng conf at Uber, played a key role in Uber's global SRE and incident response "Ring0" initiative, managed many SRE teams over a period of roughly 7 years before a career pivot. You could say I know a thing or two about SRE.)
To SRE well you look at the situation and pull from a huge range of tools. With such a broad range of solves, you're better to focus on the outcome: did we achieve our SLOs? Are they aligned with customer expectations? Focus on defining that and providing the right support for it to be achieved and you'll be fine - you might even get a surprise.