‘Tis the season. I love it when it slaps them in both directions. Leverage is bondage.
















Prompt-Cloud compression in a production agent system running 24/7. Some findings for anyone burning tokens on repeat system prompts.
Your system prompt is probably 60% behavioral prose and 40% exact values. Compress the prose. Preserve the values verbatim. Numbers, paths, entity names, threshold values: those stay untouched.
The biggest payoff is high-frequency injection points. If a prompt loads on every turn, every cycle, every dispatch, even 30% savings compounds fast across thousands of invocations.
Role definitions and workflow enforcement rules compress clean. They're pure intent. The model reconstructs the same behavioral frame from the dense form.
But security rules with critical negations need to stay verbatim. "NEVER do X" buried inside a compound token can lose the negation. That's not a fidelity tradeoff you want to make.
If you're managing a 1M context window and hitting compaction pressure, PC on the directive layers frees real budget for the things that actually need precision: facts, decisions, operational state.
The workflow that works: keep the .md as your source of truth. Compile a .pc.md for injection. Validate by comparing behavior, not diffing text. If the model acts the same on both versions, the compression held.



