Multi-agent LLM panels often vote 3-0 not because the answer is right but because frontier models share priors. A practical guide to measuring debate diversity collapse and designing ensembles that actually disagree.
Per-app redaction libraries always drift, fork, and get bypassed. Centralize DLP at the LLM gateway as a mandatory egress checkpoint with per-route policies and reversible vault tokens.
Agents that edit calendars, CRMs, and tickets inherit a concurrency bug class their tools were never designed for. The fix is plumbing version tokens through the tool layer.
How engineering orgs govern LLM token spend at the seven-figure threshold: capacity pools, outcome-based chargeback, and the committee that allocates them.
Six weeks of prompt tweaks and the eval score still oscillates in a four-point band? You're at a local maximum. Here's how to diagnose which ceiling you've actually hit — prompt, retrieval, model, spec, or data — and pick the lever that breaks it.
Long conversations quietly erode the system prompt. Why agent personas drift after 8–12 turns, how to measure the half-life, and the reinforcement patterns that hold.
Application logs say the request went to eu-west-1. The provider routed it through US and Singapore during a failover. Build the per-request sovereignty path that turns an audit into a query.
Most retrieval failures are query-shape failures, not embedding failures. A walkthrough of HyDE, decomposition, multi-query fan-out, and rank fusion — and how to diagnose which one your RAG pipeline actually needs before you reach for an encoder swap.
Retiring an AI feature is a migration, not a toggle. A field guide to grandfathering co-authored artifacts, separating writers from readers, and writing exit criteria at launch.
Span names and attribute keys are an undocumented API with consumers across cost dashboards, eval pipelines, and SLO alerts. Treat telemetry like a versioned schema or keep getting paged for breaks that fail silently.
A frozen golden set scores green while production satisfaction quietly collapses — because the users moved, not the model. Detection patterns and an eval-set shelf-life discipline.
System prompts and YAML manifests stop scaling once tool catalogs grow. A dedicated policy engine — OPA with Rego, or AWS Cedar — sitting in front of every tool call gives agents the auditable Policy Decision Point that prompt engineering can't provide.