Return on Tokens (ROT)
Brief
In 'Return on Tokens (ROT)' (2026-06-10), Packy McCormick and Markie Wagner diagnose the AI-era mistake of 'tokenmaxxing' — organizational incentives that equate high token consumption with progress after labs moved to consumption-based pricing. They define ROT quantitatively: (Value of Output - Cost of Tokens) / Cost of Tokens × 100, and argue companies must either create more valuable outputs or lower token cost (routing to cheaper models, e.g., Chinese open-source models, is one short-term tactic). The piece cites concrete failures — Uber blew its 2026 Claude Code budget by April; an advisor claims a client spent roughly $500M on Claude Code; Amazon closed its leaderboard — and quotes industry voices (Ramp’s Veeral Patel, Palantir’s Alex Karp, and Sam Altman) to show the problem is widespread.
McCormick and Wagner contend agents are the wrong runtime for most enterprise work because (1) agents improvise and fail to achieve nines-level accuracy for repetitive economic tasks, (2) engineers lack the tacit, on-site rules needed to productize processes, and (3) many deployments have no explicit goals. Their proposed fix: treat AI as a compiler that converts human goals and tacit process knowledge into deterministic code (thinking once, running cheaply forever). Poetic’s methodology is hands-on: weeks on-site, extract thousands of hidden rules, generate code, shadow/backtest changes, and only use tokens when rules change. They claim this approach yields dramatic ROT improvements — about 100× less token use and enterprise-grade accuracy (AIG cited as achieving 99%+ quality on multi-hour processes) — turning businesses into evolving software rather than perpetual agent spend.
Why it matters
Packy McCormick co-wrote 'Return on Tokens (ROT)' with Markie Wagner and published it on 2026-06-10; Wagner (backed by Founders Fund, Kleiner Perkins, Genius Ventures and OpenAI) argues tokenmaxxing became a mass delusion that drove wasted consumption-based spend.
Key details
- ROT is defined explicitly as: Return on Tokens = (Value of Output - Cost of Tokens) / Cost of Tokens × 100; you can raise ROT by increasing output value or by lowering token cost (ideally both).
- Real-world failures cited: Uber burned through its 2026 Claude Code token budget by April 2026; an unnamed consultant reportedly 'accidentally' burned ~$500M on Claude Code; Amazon shut down its AI leaderboard — evidence consumption incentives drove waste.
- Structural limits of agentic architectures: three core problems — agents can't sustain long-running, high-accuracy work; engineers lack tacit, on-site process knowledge; and agent deployments often lack explicit goals. Packy reports current Thinking-Doing Ratio (TDR) ≈ 1000:1.
- Poetic (Wagner's company) uses on-site ethnography and ex-Palantir engineers to compile tacit rules into deterministic code that runs in production; claimed outcomes include 100× lower token usage and '99%+ quality' on multi-hour processes for customers such as AIG, SoFi, and Chime.