Dust

Two startups share the same base model yet feel different: explain the moat

Identify what Lakera Gandalf is and its training data value

Retrieval P95 latency tripled after the corpus grew from 1M to 20M vectors: diagnose it

Trace an adaptive RAG gate's retrieve or skip decision across four incoming queries

Why embed and match on small chunks but feed the LLM a larger parent passage?

Match each retrieval technique to the specific failure it is designed to fix

When an explicit message bus beats in process state for multi-agent coordination

Contrast time to first token with tokens per second as serving SLOs

Why a circuit breaker around the primary LLM provider is more than a fancy retry

For 1M-token context decode, which parallelism axis actually relieves KV pressure?