A practical guide to AI agent observability, covering request ids, traces, token ledgers, tool calls, error categories, retries, timelines, and retention policy.
A practical playbook for controlling AI API spend with budgets, limits, usage logs, caching, model tiers, retry controls, and monthly reviews.
A practical checklist for configuring Codex, Claude Code, OpenAI-compatible clients, relay APIs, and internal gateways, covering API keys, base URLs, model ids, endpoints, proxies, redacted logs, and smoke tests.