projects. The goal was to determine if these instruction sets provide genuine value or simply act as high-latency noise that bloats token usage and slows down development velocity.
project, the session was completed in just 73 seconds. Token consumption plummeted, dropping from 31% of the session limit down to a lean 13%. This suggests that large instruction files force the model to "run in circles" to ensure compliance with every minor formatting rule, wasting computational resources on non-functional requirements.
to enforce documentation lookups, the model defaulted to outdated version 3 syntax instead of the required version 4. Crucially, the AI skipped running automated tests entirely. This highlights a dangerous blind spot: without explicit enforcement in the context file, agents prioritize speed over verification.
Future Implications: Lean Context Architecture
Blindly deleting your context files is a mistake, but the bloated "slash-init" defaults are clearly suboptimal. The move forward is a Minimalist Context strategy. You must retain two critical directives: test enforcement and documentation lookup triggers. Forcing the agent to verify its own work and consult the latest docs covers the gaps where internal model training fails. Efficiency doesn't come from removing instructions, but from ensuring every line of your
