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A practical 2025-ready guide to agent observability: tracing, eval hooks, and cost and latency metrics that help you debug faster and ship reliable agents.

A plain-English guide to agent evaluation scorecards: what to measure, how to score tool calls, and how to prevent quality and cost regressions every release.

A practical operating model to run AI agents in production: ownership, telemetry, eval gates, incident response, and cost controls before you ship.

Instrument AI agents fast with traces, evals, and cost controls. Avoid the hidden observability traps that cause incidents, slow debugging, and surprise spend.

A practical playbook to add approvals, confidence gates, and audit logs to tool-using agents, so you ship automation without costly surprises.

A 2026-ready checklist to trace agent tool calls end-to-end, catch token and retry spikes early, and ship reliable multi-agent workflows with confidence.

Build a practical RAG system for HR policies that stays accurate, respects permissions, and reduces back-and-forth without exposing sensitive employee data.

A practical 10-step playbook to scale AI-driven email safely with SPF, DKIM, DMARC, list hygiene, throttling, and deliverability gates that protect inbox placement.

A practical guide to deploying AI agents across your B2B demand gen stack—workflows, governance, risks, metrics, and a 30–90 day rollout plan.