A robotics planning paper shows why warehouse fleet performance depends less on abstract path optimality and more on realistic execution constraints, model fidelity, and planner scalability.
A mechanism-first reading of SCOPE, a paper showing how LLM guidance can be moved from runtime planning into one-time subgoal initialization for cheaper hierarchical agents.
A cognitive-geometric paper reframes persuasion, leadership, marketing, and AI alignment as problems of whether meaning survives translation across different value spaces.
A live-enterprise penetration-testing study shows that AI security agents are becoming useful not because they are magically smarter than humans, but because scaffolding lets them work longer, wider, and cheaper under controlled conditions.
A mechanism-first reading of why production-grade agentic AI is less about giving agents more freedom and more about engineering away the places where they should not guess.
A business-focused reading of EcomBench, showing why practical e-commerce tasks expose the gap between impressive agent demos and deployable operational reliability.
A close reading of why stronger single-agent foundation models do not automatically become reliable collaborators, coordinators, or multi-agent planners.
A mechanism-first reading of CARLoS, a framework that turns visual LoRA behavior into searchable, governable infrastructure.
A practical reading of interpolation as the governance layer behind forgetting, explanation, ontology reuse, and rule-based AI reasoning.
A mechanism-first reading of REST and REST+ shows why OCR-correct screenshots can still produce modality-dependent answers in multimodal LLM workflows.