Statecraft: Revoking Accumulated Instructions by Appending a System Message

Agents now run long sessions, and the application around them often changes their instructions midway: it switches the reply language, lifts the rule to ask before each file edit, or lowers the reasoning effort. Editing the system prompt for each change throws away the prefix cache, while appending only the change leaves the earlier instructions in the context, and no message lists all of those still in force. We propose STATECRAFT, an append-only control plane for these instructions: after each change, the application appends the full, versioned list of current instructions, so the latest list alone says what applies. As in any revised list of instructions, one is revoked simply by leaving it off. This keeps the cache but asks the model for something that ordinary instruction following does not: to stop following an instruction that is no longer listed. We build Statecraft-200 to test this, with multi-turn, tool-using tasks that check both that the current instructions are followed and that revoked ones are no longer followed. Frontier models such as Claude Sonnet 5 and Opus 5, DeepSeek V4 Pro, Kimi K3 and GLM 5.3 still follow a revoked instruction in 32 to 65% of later checks, even though the prompt states that anything left off the list no longer applies. We therefore train Qwen3.8-27B with DPO on pairs of its own answers to the same conversation, chosen by an automatic check that rewards following the latest list and penalizes following a revoked instruction. Training removes 81% of its failures on Statecraft-200 overall, enough to lift its overall score past every frontier model we test, and raises its success on the tasks where the instructions change most often from 52% to 82%. The gains hold in unseen workspaces, on kinds of instruction held out of training, after long real conversations and on conversations from the external SEQUOR benchmark whose constraints arrive as snapshots, and scores on IFBench, GSM8K and Multi-IF do not fall.