41–50 of 58 posts
AI 1: This user is suspicious, lock account User: Ahh, got locked out, contact support and wait AI 2: The user is not suspicious, unlock account User: Great, thank you AI 1: This account is suspicious, lock account
We've shifted our oncall incident response over to mostly AI at this point. And it works quite well. One of the main reasons why this works well is because we feed the models our incident playbooks and response knowledge bases. These playbooks are very carefully written and maintained by people. The current generation of models are pretty much post-human in following them, performing reasoning and suggesting mitigati…
9 times out of 10, you can and should write "using" instead of "leveraging".
We've shifted our oncall incident response over to mostly AI at this point. And it works quite well. One of the main reasons why this works well is because we feed the models our incident playbooks and response knowledge bases. These playbooks are very carefully written and maintained by people. The current generation of models are pretty much post-human in following them, performing reasoning and suggesting mitigati…
PSA: 9 times out of 10, you can and should write "using" instead of "leveraging".
We've shifted our oncall incident response over to mostly AI at this point. And it works quite well. One of the main reasons why this works well is because we feed the models our incident playbooks and response knowledge bases. These playbooks are very carefully written and maintained by people. The current generation of models are pretty much post-human in following them, performing reasoning and suggesting mitigati…
I'm really curious to hear more about what kind of thing is covered in your playbooks. I've often heard and read about the value of playbooks, but I've yet to see it bear fruit in practice. My main work these past few years has been in platform engineering, and so I've also been involved in quite a few incidents over that time, and the only standardized action I can think of that has been relevant over that time is c…
In general, playbooks are useful for either common occurences that happen frequently (ie every week we need to run a script to fix something in the app) or things that happen rarely but when they do happen need a plan (ie disaster recovery)
We've shifted our oncall incident response over to mostly AI at this point. And it works quite well. One of the main reasons why this works well is because we feed the models our incident playbooks and response knowledge bases. These playbooks are very carefully written and maintained by people. The current generation of models are pretty much post-human in following them, performing reasoning and suggesting mitigati…
We've shifted our oncall incident response over to mostly AI at this point. And it works quite well. One of the main reasons why this works well is because we feed the models our incident playbooks and response knowledge bases. These playbooks are very carefully written and maintained by people. The current generation of models are pretty much post-human in following them, performing reasoning and suggesting mitigati…
If you already have those, how much can an AI add? Or conversely, not surprising that it does well when it's given a pre-digested feed of all the answers in advance.
Earlier quoted context omitted.
Sounds like you're projecting your own laziness and shortcomings on others. This is a tool that seems really helpful considering the alternative is 0%.
Personal insults aside, "seems" requires no evaluation if the success rate is outside what could be considered a sane confidence interval on trust. I would literally be fired if I implemented this tool.