Opening the Weights: When AI Models Become Objects of Interpretation and Intervention

Neural network weights have long been both the product of training and a medium of intervention. On 2 November 2026, Takehi, Teoh, Zhang and Khattab reported experiments in which GPT-6 Astra inferred characteristics of small neural networks from their weights and, in a separate experiment using tools and feedback, edited a language model to reduce reasoning loops. This conceptual working paper asks what follows if these preliminary capabilities develop. It distinguishes task inference from training-data identification, and behavioral change from precise general control. It proposes a framework for evaluating provenance inference, mechanistic explanation and post-training intervention, and outlines future experiments. No new experiment is reported. Not peer reviewed.