FrankenCoder Guides

Practical, measured guides to coding with AI agents — the economics of agent memory, how the orchestration actually works, and the settings that decide what a session costs.

Context Economics

Keeping your AI coding costs low with Anthropic — a practical guide

Where the money actually goes when you code with an Anthropic-powered AI agent — measured across 340,000 messages and 600+ real sessions — and why cache writes, 5-minute TTLs, keep-warm, and shared prefixes change the cost math.

June 14, 2026 · Updated June 16 · 12 min read   Read →
Delegation Economics

Should your smartest model be the one running grep?

We replayed 104,979 real agent turns with their actual token bills. Keeping the smart model planning and verifying while cheap sub-agents do the search-and-edit grunt work cut cost ~43% on real code-heavy sessions — measured, not benchmarked.

June 14, 2026 · 8 min read   Read →