Cost Optimization
8 articles about cost optimization.
Logging Is Slowly Bankrupting Me - Debug Logging in AI Agent Systems
When debug logging becomes a cost problem in AI agent systems - how verbose logs eat tokens, inflate context windows, and silently drain your budget.
GTC 2026: Inference Is Eating the World
Inference is a recurring cost, not a one-time expense. Every agent action costs tokens. Minimizing LLM round trips is the key to sustainable agent economics.
Multi-LLM Agent Routing - Using Different Models for Different Subtasks
How AI agents route between multiple LLMs - using Claude for orchestration, smaller models for classification, and specialized models for code generation or
Claude Orchestrates GPT and Gemini - Multi-Model Routing for Desktop Automation
Use Claude for planning and reasoning, route execution tasks to cheaper models like GPT or Gemini. Multi-model orchestration cuts costs without sacrificing
When Cheaper AI Models Are Good Enough for Daily Development
Sonnet handles Python wrappers and routine coding just fine. Opus shines for architecture decisions. How to route AI model usage by task complexity and save
Tips for Secondary Models - When to Use Haiku vs Opus in AI Agents
Choosing the right model tier for different AI agent tasks saves money without sacrificing quality. Learn when to use cheap models like Haiku and when to
Claude Code Burned All My Tokens in 30 Minutes - Why Narrow Scoping Fixes This
Running 5 agents in parallel on your codebase without narrow scoping burns through tokens in minutes. Each agent needs a very specific scope to be
Using Opus as Orchestrator, Delegating to Sonnet and Haiku
The real win of using Opus as an orchestrator that delegates to Sonnet and Haiku is not cost savings - it is context window management. Opus burns through
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