Developer Publicly Lists Safety Flaws in His Own AI Planning Tool to Build Trust

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A developer who built an open-source AI agent planning engine has voluntarily published a register of known failure modes in his own tool, arguing that transparency strengthens rather than undermines credibility. The engine previously blocked all 11 adversarial goals and 35 flawed plan variants tested, but community commenters identified critical gaps the developer had glossed over. Key weaknesses include the inability to re-audit tool outputs fetched after initial goal validation, meaning a malicious payload in an API response or database record could slip past safety gates. A second flaw allows structurally valid but semantically harmful plans to satisfy deterministic checks undetected. The developer has logged these gaps as tracked issues and outlined planned fixes, including typed tool-result provenance and capability-scoped state transitions, while acknowledging the solutions are not yet implemented.

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