AI Signal 142
AGENTS.md proposes a zero-trust execution loop to stop LLM agents from running destructive commands
A new repository introduces AGENTS.md, a computational constitution that forces autonomous LLM agents into an epistemic state machine where every consequential action must be verified through read-only diagnostics before execution.
Ungoverned LLM agents can bundle destructive commands based on unverified premises, creating serious risks in production environments. Natural language governance in system prompts degrades over time due to context window dilution, making programmatic enforcement necessary.
Written by elseif from the cluster below · every claim links back to a sourceThe three things worth knowing
AGENTS.md forces agents through a mandatory loop of hypothesis, evidence identification, read-only verification, and a hard yield to an operator before executing consequential actions.
The approach strips agency from the LLM at the execution boundary, requiring middleware to physically cut the API stream and feed raw output back into context.
Natural language governance fails over time due to context window dilution, whereas this method enforces rules programmatically at the prompt and runtime layers.
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