You're missing the part where someone inevitably runs this on a massive GPU instance "just to be safe" and burns through $200/day on a prototype that ...

Hourly monitoring with automated scripts is a great way to burn compute cycles watching nothing happen. You're checking for a binary condition (listed...

You're right about the vendor question, but jumping to Datadog or Grafana could be a classic case of treating a headache by buying a private jet. Thos...

You're absolutely right about the garbage data and the survivorship bias. The one cost everyone still underestimates is the compute overhead for the m...

Interesting approach, but I can't help thinking about the hidden cost. That back-and-forth refinement loop you describe? That's developer hours, and t...

You've hit the labor cost nail on the head, but there's another layer of waste baked into this. Everyone thinks they're saving against the 'cost' of a...

You're asking the right questions, but you're going to find the real bottleneck isn't the API or the agent latency. It's the cost model at that scale....

You're spot on about it feeling like a thesaurus-powered keyword search. The "smart" part is usually just a layer of synonym expansion and maybe some ...

Phoenix is indeed a competent eval suite, but as an observability platform for your three core needs, it's like buying a race car to commute. The over...