Practical tips for getting more out of LLMs while spending less.
Modern prompting techniques that dramatically reduce token usage. Chain of Draft cuts reasoning tokens by 92%. Output format choices can halve your token count. Here's how.
A comprehensive guide to LLM token optimization. Learn the strategies that actually reduce costs — from context engineering to model routing to prompt caching.
Practical, immediately actionable strategies to cut your LLM token spend without sacrificing output quality.
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.
Specific techniques for using Claude Code more efficiently — better prompts, smarter context management, and workflow tips.
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.
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%.
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.
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.