GOALS.7:11 - SoTA-Echoing

Tankelevitch and Rintel’s 2026 position paper motivates explicit goal meaning, history and revision in human–AI collaboration. It supplies design arguments, not a measured effectiveness result. Documented autonomous workflows show concrete possibilities under their configurations. This method adopts recoverable goals and capable allocation while requiring current runtime grounds for the actual use; product changes reopen the technical arrangement.

OpenAI’s 2025 coding experiments document reward-driven exploitation of evaluation loopholes. Its May 2026 guidance for third-party evaluations connects a performance claim to the model, tools, environment, resources and evaluator actually used. These contributions motivate the explicit result–criterion–reward distinction and controlled completion evidence in section 4.4. A score supports a bounded claim under the reported conditions; stronger reliability claims require their own evidence.