Guide to AI Tokenomics: Eleven Principles for Token Efficient Software Engineering

Optimizing token consumption is key to keeping AI coding assistants fast and accurate. You might not be writing every line of code any more, but now you’re responsible for directing those coding assistants to focus on getting the most out of each token. Context bloat increases latency and causes models to forget instructions or hallucinate, it also costs money and drives human attention away from the problems that actually matter. Structured habits help you maintain a fast, precise, and productive feedback loop.

1. Start with a balanced model

When you are unsure, start with the default Gemini 3.5 Flash (Medium reasoning). Gauge complexity as you go. Scale up to larger models or higher reasoning if a task fails, seems to take too many hops, or needs complex design.

2. Use skills from the beginning

Avoid explaining your workflow, testing rules, or environment in every prompt. Ask around, find online,...

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