A significant part of teacher work is designing for learning (Goodyear & Dimitriadis, 2013). Teacher knowledge work in creating designs for learning (e.g., lesson plans) are rarely shared with the profession more broadly. This opportunity, for facilitating knowledge-sharing between teachers, was identified in the Open Educational Resources (OER) movement (Downes, 2007). Such approaches had limited uptake in the Australian context, arguably because of the significant time imposition upon to teachers to either search through OER repositories or to share their own resources in a commons.Our work describes a proof-of-concept for the next generation of knowledge sharing platforms that make use of natural language processing, machine learning and semantic web approaches. The guiding design principle is of adding value to what teachers are already doing without adding time imposition. This position paper outlines an approach in which teachers: (1) upload a lesson plan; (2) receive suggestions for ways that the lesson plan might address cross-curricular learning areas; and (3) receive suggestions for lesson plans, technologies, knowledge-objects, and specific text and how they might be used to augment the existing lesson plan.The paper details the way that these technologies work together to create a user experience for the teacher that is an improvement over existing approaches (e.g., use of Google or Facebook groups). It also speculates about the potential that future iterations based on this approach might significantly aid teachers in their design for learning. Specifically, it looks at:Ways that the usability of the platform creates a feedback look in which increasing amounts of teacher knowledge become a part of the professional commons (potentially realising the aims of the original OER movement).Ways that such a platform can serve to break down barriers between subject areas thus facilitating the increasing demand for interdisciplinary learning. Ways that such a platform could be used to assist teachers to cater for diverse learning needs and preferences. It considers the ethical challenges presented by such an approach, such as the potential for (implicit) enforcement of normativity of pedagogical approaches, the need for transparency in machine learning algorithms, and the potential for misuse of such tools by educational authorities.ReferencesDownes, S. (2007). Models for sustainable open educational resources. Interdisciplinary Journal of E-Learning and Learning Objects, 3(1), 29-44. Goodyear, P., & Dimitriadis, Y. (2013). In medias res: reframing design for learning. Research in learning technology, 21.