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Posts tagged "Best Practices"

6 posts

How to Track LLM API Costs per Key, Model, and Request

A practical setup for LLM cost attribution: one API key per app or agent, per-request cost traces, per-model usage breakdowns, and spend caps that stop runaway loops — using a gateway ledger instead of month-end spreadsheet archaeology.

|Router One Team

LLM Fallback Strategies: Production Failover That Holds

What triggers fallback, the trade-offs between provider and model changes, how to read the final request outcome, and how request_id supports operational investigation during provider incidents.

|Router One Team

Reselling LLM API Access Safely with Spend-Capped Keys

An honest pattern for building a small AI API business on a managed upstream: one key per customer, per-key spend caps and rate limits, per-request usage data for billing — and a clear list of what key-level reselling does not give you.

|Router One Team

Multi-Agent Orchestration: Patterns for Production AI Systems

Sequential, parallel, hierarchical, and human-in-the-loop multi-agent patterns — when to use which, how to handle failures, and how to keep cost and latency under control in production.

|Router One Team

Claude Skills Explained: Building Custom Agent Capabilities

Claude Skills let agents pick up specialized capabilities on demand. We explain the model, walk through writing your first skill, and show how to ship them safely in production.

|Router One Team

AI Agents in Production: Observability, Cost Caps, Recovery

Learn how to run AI agents safely in production with observability traces, budget guardrails, and automatic fault recovery. Practical patterns and code.

|Router One Team