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Revolutionizing Education with EduAid and AI How do we use AI to raise the quality of education instead of flooding classrooms with low-grade automation? In this episode, we sit down with Thomas Thompson, founder of EduAid, to explore his journey from educator to edtech builder and how research-driven guardrails, thoughtful prompt design, and teacher expertise are shaping a more responsible future for AI in education. We unpack what actually works, where AI clearly falls short, and why taste, evidence, and human judgment still matter more than raw model capability. 00:02 How COVID accelerated the demand for better classroom tools 01:30 Why high-quality educational research is hard for teachers to access 01:59 Gaps between research and classroom practice 03:25 From open educational resources to AI-powered workflows 03:55 The limits of traditional OER models 05:16 Building EduAid with modular prompts and guardrails 06:15 How AI interprets prompts for lesson planning and differentiation 08:09 Evaluation tools and structured AI workflows 09:37 AI-assisted assessment design 10:33 Why strong inputs matter more than model size 11:57 Personalization and scaffolded learning in classrooms 12:25 Classroom micro-moves that improve learning outcomes 16:53 The role of teacher expertise in AI-generated outputs 28:01 Where AI tutors fall short 29:25 Why relational teaching skills can’t be automated 35:48 Building evaluation infrastructure for AI in education 37:36 Avoiding low-quality AI output and “AI slop” 43:38 Ensuring evidence-based instruction with AI 44:04 Maintaining quality, taste, and instructional standards 45:49 The enduring value of knowledge and discernment 46:47 Why high standards still matter in education Key themes discussed: How the pandemic exposed structural gaps in teacher tools and workflows Why access to quality research is still one of education’s biggest bottlenecks The evolution from static open educational resources to adaptive AI systems Designing AI with modular prompts, evaluation layers, and instructional guardrails The critical role of teacher judgment in shaping meaningful AI outputs Where AI can support personalization without replacing human connection Why relational, embodied teaching remains fundamentally human The importance of transparency, evaluation, and restraint in AI adoption Connect with Thomas Thompson Eduaide.ai LinkedIn: / thomas-thompson-606b71112