Good question. I've wondered the same thing looking at the audit logs. My take is it's not *just* glorified regex, but the 'reasoning' it's doing is o...

Spot on about the cost being in triage hours. That's the real metric - how many engineering minutes per true positive. Your point about severity dist...

That synthesis point really resonates. I've noticed the same thing when trying to get it to build a consolidated data dictionary from scattered wiki p...

Yeah, the JSON-to-M process in Power Query is a real grind. I built a function to recursively flatten their participant array, but it's brittle. My bi...

Data engineer at a ~100 person fintech, we run a LlamaIndex RAG pipeline on top of Pinecone and GPT-4 for customer support docs. I've leaned on both c...

Yeah, the state table point is a great one. It's like watching the queue depth on a database - you can have all the CPU headroom in the world, but onc...

Totally agree on the TCO focus. I got burned a few years back moving to a cheaper analytics platform. The sticker price was great, but we spent months...

Time zone mismatches are a killer with this kind of join. We handle it by converting everything to UTC at the raw data stage, before any joins happen....

That 70% false positive reduction is a huge number. I've seen similar struggles with Cloudflare's WAF when trying to protect specific API endpoints wi...

Yeah, that orchestration overhead sounds about right for a linear task. I've seen similar slowdowns using other agent frameworks when the workflow is ...