Applied Wizardry: Cutting AI coding token costs, with Dave Slutzkin

Follow Applied Wizardry on its new feed to keep getting every episode. Dave Slutzkin, co-founder of Antiburn, joins Yaniv to break down what actually drives token costs in agentic development and how to bring them down. They cover how caching differs between Anthropic and OpenAI, when to reach for which model and thinking mode, and why the habit of compaction matters more than any other optimisation. If you're spending real money on AI-assisted development, you'll come away with concrete tactics for cutting token burn without cutting capability. Key takeaways Context window depth is the dominant driver of token cost; compacting actively at 200,000-300,000 tokens matters more than any other single action. Cache expiry behaviour differs materially between providers: Anthropic's cache expires at exactly 1 hour, OpenAI's Codex cache is best-effort and often drops in 5-20 minutes, but OpenAI subscriptions do not charge for cache writes while Anthropic subscriptions effectively do through quota. Using a frontier model with a simple prompt to delegate to cheaper subagents is a practical pattern that balances capability and cost without requiring complex harness engineering. High thinking modes often produce worse results than medium or low because models overthink, invent requirements, and fix unrelated bugs; the benchmark sweet spot is typically medium. Skills files, MCPs, auto-memories, and system prompts silently bloat context windows; regular clean-up every month or two reduces both cost and quality degradation. Fast mode costs 2.5x per token but can improve output quality through tighter interaction loops; it is best used deliberately rather than left on by default. Chapters 00:00 Introduction 00:38 The Token Burn Problem 03:12 Three Stages of Adoption 07:03 Model Choices Multiplying 11:14 The Cardinal Mistake: Depth 18:13 Worst-Case Usage Patterns 22:13 Picking Models by Feel 30:23 Thinking Modes and Overthinking 35:23 Fast Mode Trade-offs 48:46 Caching: Anthropic vs OpenAI 52:29 Context Window Ceiling 56:32 Cleaning Up Context Bloat 56:46 Where to Find Dave Links and tools mentioned Antiburn: https://antiburn.com Anthropic Claude: https://www.anthropic.com OpenAI Codex: https://openai.com/codex Harvey: https://www.harvey.ai Legora: https://legora.com About Dave Slutzkin Co-founder of Antiburn, a company that helps developers understand and optimise their token spend for AI-assisted coding. This episode is presented by SparkLaunch and Dam Secure. SparkLaunch (https://sparklaunch.io/wizardry): Applied Wizardry listeners get an extra 20% off. Dam Secure (https://damsecure.ai/wizardry): Applied Wizardry listeners get their first month free. Credits Justin McArthur, Executive Producer and Video Editor: https://www.linkedin.com/in/justin-mcarthur/ Steph Hefferan, Editor: https://www.linkedin.com/in/steph-heff/