Most LLM telemetry posts brag

Most LLM telemetry posts brag about what they monitor. Here's mine — including what I'm still missing.

Built this for lokerdollar.com, solo, in production:

Covered: — p50 / p95 / p99 latency per task — cost per 1k tokens + daily burn + per-task spend — provider success rates + circuit breaker state — cache hit rate, quota / rate limit tracking — model leaderboard scored on live traffic

Gaps I'm still chasing: — prompt versioning tied to quality signals — TTFT for streaming UX (matters for chat tasks) — per-user cost attribution — semantic error taxonomy, not just HTTP codes — push-based degradation alerts (today's playbook is reactive)

The lesson from running this solo: observability is never "done." It's a backlog that evolves with the product — and the gap list is more honest signal than the green checkmarks.

→ Open for AI platform / full-stack work. If you want this layer for your team, my DMs are open.