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Agentic coding costs 1,000× more per task than a chat message — and where the tokens actually go

A Microsoft Research / Stanford study (arXiv:2604.22750, April 2026) found agentic coding tasks consume ~1,000× more tokens than chat on the same model. Input dominates the cost, not output. Accuracy gains can saturate; the dollar cost depends on rates and caching. Here is what that means for the input surfaces you can actually compress.

2026-09-30James Hollingsworth8 min

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Title
Category
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2026-06-13Smaller code context, higher fix rateResearchJames Hollingsworth→2026-06-13A smaller context made the agent more accurateResearchJames Hollingsworth→2026-06-01Perfect retrieval isn't enough: the hidden cost of long LLM contextResearchJames Hollingsworth→2026-05-29How to Reduce Claude Code Token CostsTutorialJames Hollingsworth→2026-05-20One Query Parameter Cut 19% of Our Claude Code Context BurnEngineeringJames Hollingsworth→2026-05-20Why Google Killed CNET's AI Article Strategy (And What We're Doing Instead)ResearchJames Hollingsworth→2026-05-20MCP Token Costs: A Quantitative BreakdownCostJames Hollingsworth→2026-05-20We Compressed a 3,448-Line MCP Gateway to a Searchable Symbol MapEngineeringJames Hollingsworth→2026-05-19Resend bounce handling, PostHog funnel instrumentation, and an AST fence against billing driftEngineeringJames Hollingsworth→2026-05-09How we measure quality at 5× compression: corpora, judge prompts, and anti-bias controlsResearchJames Hollingsworth→
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