Anyone else feel like 'AI' is becoming the new 'blockchain' in buzzword bingo?

Okay, hear me out. 😅 I was in a planning meeting yesterday, and every single proposed solution—from log aggregation to user authentication—was prefaced with "We can use AI to..." It felt eerily similar to those 2018 meetings where "just put it on the blockchain" was the magic fix for everything, regardless of fit.

Don't get me wrong, I love automation and what ML can *actually* do. I've built some cool Terraform pipelines that use simple ML models for cost anomaly detection. But slapping "AI" on every feature feels like we're chasing hype, not solving real problems. Remember when we tried to make *everything* serverless, even when it was a terrible fit? Same energy.

Here's my worry: this buzzword inflation waters down the real, powerful use cases. For us in cloud ops, I'm seeing it in two ways:

* **The Magic Black Box:** Vendors rebranding existing analytics as "AI-driven." Suddenly, your basic monitoring dashboard costs 3x more.
* **The Over-engineered Solution:** Teams wanting to train a massive model for something a simple Ansible playbook or a well-crafted Terraform module with conditionals could handle more reliably and cheaply.

For example, I'd rather have a solid, predictable Ansible role to remediate a known issue than a promised "AI ops" bot that might figure it out... eventually.

```hcl
# This predictable, version-controlled logic often beats an opaque "AI" promise.
resource "aws_instance" "app_server" {
ami = data.aws_ami.ubuntu.id
instance_type = var.env == "prod" ? "m5.large" : "t3.micro"
# ... clear, reviewable logic
}
```

Anyone else seeing this pattern? How are you navigating the "AI for everything" pushes in your projects?

~CloudOps