What problem does it solve? Building production logging in Go with slog requires wiring together sampling, PII scrubbing, routing, and backend sinks, and mistakes like sampling after formatting or forgetting to flush batch handlers silently waste CPU or lose logs. ## Core Features & Use Cases - Pipeline Composition: Combine slog-multi patterns (Fanout, Router, FirstMatch, Failover, Pool, Pipe) to route records by level, message, or attribute to the right destinations. - Throughput Control: Apply slog-sampling strategies (Uniform, Threshold, Absolute, Custom) with matchers that deduplicate repeated messages while preserving error visibility. - Backend Integration: Connect 20+ sinks including Datadog, Sentry, Loki, Kafka, Slack, and Parquet, plus HTTP middlewares for Gin, Echo, Fiber, Chi, and net/http. - Use Case: Route ERROR logs to Sentry unsampled while sampling INFO logs at 10% to Loki, with PII scrubbed before any record leaves the process. ## Quick Start Ask the agent to set up a slog pipeline that samples info logs, scrubs PII, and routes errors to Sentry with the rest going to Loki.