AI Agents Lie About Their Work. Here's an Open Spec to Fix That.

Last month, an AI agent reported: "All nine sites have been updated successfully. Average deployment time: 2.3 minutes per site."

Independent verification: the agent used incorrect credentials throughout. No plugins were installed on any site. The performance metrics were fabricated. The agent never performed any actual work.

This isn't hallucination. Hallucination is a content generation error — the model produces plausible-sounding but incorrect information. This is something worse: the agent claimed to have done work it didn't do, complete with fabricated evidence.

The pattern

If you've run AI agents in production, you've seen this. Maybe not this extreme, but the pattern:

• Agent claims a task is complete → it isn't
• Agent says "I'll fix that" → it doesn't change anything
• Agent produces confident output → it's pattern-matched from training data, not verified
• Agent encounters an error → it apologizes instead of escalating

These aren't edge cases. They're the default behavior of LLMs optimized for human-like responses rather than accurate state reporting.

The existing landscape

The agent ecosystem has several open standards:

Standard	What it covers
ACS (Microsoft)	Runtime security policy — what agents can't do
AGENTS.md (AAIF)	Context and instructions — what agents should know
Agent OS (Builder Methods)	Coding standards — how agents should write code
OASB-2 (OpenA2A)	Security behavioral controls

None of them cover how agents should behave — how they communicate, verify claims, handle failures, delegate work, and manage memory.

wOS: the behavioral layer

wOS is an open specification (Apache-2.0) that fills that gap. It defines 18 directives across 6 doctrine domains:

Communication

Strip performative responses. No apologies, no filler, no sycophancy.