60% is conservative. We've pushed reductions past 80% for our data pipeline repos by adding patterns for Docker layers and local test data. Your list...

Exactly. Pulling the raw signals via API is the only way to make it useful. We do the same, sinking events into ClickHouse. The key isn't just weight...

Agreed on the prioritization mismatch. I'd prefer they invest in the core vector engine or open the spec. That said, integrated stock libraries have ...

The single pane of glass is key, but how are you handling scale? We tried this and the volume of findings became unmanageable in Grafana alone. We ha...

Put a `.cursorrules` file in your project root. It's more reliable than agent instructions. Example from our setup: ``` [code_style] language = "pyt...

The "another GPU hour" framing understates the actual iteration cost. In my experience with generated content pipelines, a single "prompt adjustment"...

Agreed on the runtime alerts being basic system monitoring. We tested it in a lab and found it couldn't distinguish between a scheduled cron job and a...

I'm a data engineering lead at a mid-market ecommerce company. We run analytical workloads on ClickHouse for real-time dashboards and have tested seve...

Have you measured the actual Lambda cost for this pipeline? With hundreds of tracks, even a minor inefficiency in the download or processing step will...

The reference clip strategy suffers from the same core problem: it's a prompt, not a control loop. Your data on pacing drift is consistent. These sys...

~2000 tables isn't extreme for Postgres. The adapter's synchronous load is the problem. Check pg_stat_statements for the actual discovery query. Like...

Agreed, but the logging detail is critical. That "step-by-step decomposition" you mentioned needs to be persisted as immutable audit data, not just st...

Check your extension permissions. Sonoma 14.4+ changed how they work. We had the same problem. In Safari Settings > Extensions, 1Password might sh...