More Watts, Less Light
Token burn and business outcomes are not correlated. More burn means more inefficiency, not more value. The electricity problem Imagine you walk into a dark room. Turning on a light helps you see. Turning on every light in the building does not help you see better. It's still the same room. Now every surface is equally lit, the contrast is gone, and you're paying for power you didn't use. Tokens work the same way. A focused prompt with clear scope is the single overhead light over your desk. A sprawling prompt with unlimited exploration is every light in the building — you're burning power, not producing insight. Tokens are electricity, not output. More throughput doesn't mean more value. I've had weeks where I burned through my allocation and looked back at the end to find nothing concrete. Code that worked but went unused. Exploratory branches that dead-ended. Agents that generated plausible-looking output that didn't survive first review. A lot of motion. Not much progress. The ceiling stops you from doing that indefinitely. It forces a moment of reflection: did this burn produce anything real? If the answer is no, more capacity isn't the fix. More discipline is. Three patterns I now use instead I started paying attention to what actually ships versus what just burns context. I gave the patterns names so I could catch myself faster: RTK — Read The Knowledgebase. A focused 15-minute read of the codebase, identifying the exact files and exact changes, saves 200K+ tokens of exploratory waste. The agent doesn't discover the shape of the task — it executes against a known one. Caveman — compress before you prompt. Strip greetings, filler words ("I think", "basically", "Let me know if that makes sense"), and closing courtesies. Every word in your prompt multiplies across every response token. Less fluff in means less fluff out. Ponytail — spec the minimum viable solution. "Robust", "scalable", "enterprise-grade", "comprehensive" — these words invite scope creep. Specif