LLM Token Optimization Strategies: The Complete Guide for 2026
A comprehensive guide to LLM token optimization. Learn the strategies that actually reduce costs — from context engineering to model routing to prompt caching.
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Practical tips for getting more out of LLMs while spending less.
5 Ways to Reduce Your LLM API Costs Today
Practical, immediately actionable strategies to cut your LLM token spend without sacrificing output quality.
Context Engineering: Why Reducing LLM Token Usage Isn't About Shorter Prompts
The biggest source of wasted LLM tokens isn't your prompt — it's your context. Learn how session management, just-in-time retrieval, and repo memory cut token usage dramatically.
Claude Code: How to Get More Done With Fewer Tokens
Specific techniques for using Claude Code more efficiently — better prompts, smarter context management, and workflow tips.
How to Reduce OpenAI and Claude API Token Costs: A Developer's Guide
Practical techniques to reduce your OpenAI and Claude API costs. Covers pricing tiers, prompt caching, structured outputs, model routing, and the API features that save money.
Cut MCP and Tool Overhead to Save Thousands of LLM Tokens Per Request
Tool definitions and MCP servers can add 55K–134K tokens of overhead before any work starts. Learn how on-demand tool loading can cut that by 85%.
Designing for Prompt Cache Hits: How to Save 90% on LLM Input Tokens
Prompt cache reads cost 10x less than regular input tokens. Learn how to structure your prompts to maximise cache hit rates and slash your LLM costs.
How to Measure and Monitor LLM Token Usage (Before You Can Optimise It)
You can't optimise what you can't measure. Learn how to track LLM token usage with built-in tools, cost APIs, and monitoring patterns that reveal where your tokens actually go.