Episode Details

• Date: March 16, 2026
• Duration: ~26 minutes
• Host: Pranusha Manchala
• Guest: Mike Kenny, Owner of Math Fact Lab

Episode Summary

In this episode, Mike Kenny shares the inspiring journey of Math Fact Lab, a platform revolutionizing how students master foundational math skills. As a former fifth-grade math teacher with 19 years of experience, Mike discusses how he transformed his classroom materials into a cloud-hosted application that helps students develop math fact fluency through research-based strategies rather than traditional memorization. He reveals how AWS has supported Math Fact Lab's growth from a bootstrapped startup to serving schools and districts nationwide, emphasizing the importance of conceptual understanding and personalized learning in mathematics education.

Key Discussion Points

• Evolution from classroom teacher to EdTech entrepreneur
• Research-based approach to math fact fluency vs. traditional memorization
• Platform design for personalized learning with customizable settings
• Scaling from individual teachers to school districts with rostering integrations
• Student success metrics showing 40% to 90% improvement in fact mastery
• AWS's role in enabling secure, scalable infrastructure for student data
• Future expansion into integer operations for middle school students

Featured Technologies

• AWS Cloud Infrastructure
• Clever and ClassLink rostering integrations
• Visual learning models (dice, area models, ten frames)
• Adaptive assessment systems

Key Takeaways

• Strategy-based learning outperforms memorization for long-term math fluency
• Personalization (adjustable time limits, learning tracks) accommodates diverse student needs
• AWS startup programs provided critical early-stage support for bootstrapped ventures
• Customer feedback drives continuous product evolution and feature development

Resources Mentioned

• Math Fact Lab: mathfactlab.com
• AWS Startup Programs
• Research on math anxiety and timed tests

Tags

#EdTech #MathEducation #AWS #StudentSuccess #K12Education #DigitalLearning #CloudComputing #StartupJourney #PersonalizedLearning #Education

Episode Details

• Date: 2026-03-02
• Duration: ~15 minutes
• Speakers: Leo Zhadanovsky (Host), Zach Pendleton (Chief Architect at Instructure)

Episode Summary

In this episode, Zach Pendleton, Chief Architect at Instructure, shares how the company built Ignite AI—an agentic AI solution powered by Amazon Bedrock—to transform educator and student experiences in Canvas LMS. Zach discusses the journey from concept to beta in just 6 months, the technical architecture decisions, and how they addressed critical concerns around data privacy and responsible AI implementation in education.

Key Discussion Points

• Instructure's 14-year evolution to become the largest LMS in the United States
• Development of Ignite AI to save educators time and automate complex workflows
• Building agentic experiences that go beyond simple chatbots
• Rapid development timeline: concept to beta in 6 months
• Partnership with AWS and leveraging the Generative AI Innovation Center
• Addressing data privacy and residency requirements across global markets
• Educator adoption journey from AI resistance to excitement
• Future vision for multimodal and voice-enabled learning experiences

Featured Technologies

• Amazon Bedrock
• Model Context Protocol (MCP)
• Agentic AI architecture
• Voice-to-voice AI (Sonic model)

Key Takeaways

• Multi-model architecture enabled testing and optimization across different AI models through a single API
• Building evaluation pipelines early accelerates safe experimentation with new models
• AWS's global infrastructure enabled compliance with data residency laws across US, Canada, EU, and Pacific regions
• Successful AI implementation starts with customer problems, not technology-first approaches
• Ignite Agent automates complex tasks like content authoring and student accommodations that previously took hours

Resources Mentioned

• AWS Generative AI Innovation Center
• Anthropic Claude models

Tags

#EdTech #HigherEducation #AWS #AmazonBedrock #AI #AgenticAI #LMS #Canvas #Instructure #DigitalTransformation #GenerativeAI #Education #Innovation

Episode Details

• Date: 2026-02-16
• Duration: ~7 minutes
• Speakers: Leo Zhadanovsky (Host, Enterprise Technologist for Education at AWS), Gayathri Rengarajan (Guest, Associate Director of Data Science at PowerSchool)

Episode Summary

In this special re:Invent episode, Gayathri from PowerSchool shares the journey of building Power Buddy, an AI-powered learning assistant that evolved from a hackathon project to a full suite of products serving over 60 million K-12 students. The conversation focuses on implementing robust content filtering using fine-tuned models on AWS SageMaker, addressing student safety concerns while reducing false positives, and the future of agentic AI in education technology.

Key Discussion Points

• Evolution of Power Buddy from hackathon project to production suite
• Implementation of strict content filtering for student safety in AI interactions
• Challenge of balancing safety with reducing false positive notifications for administrators
• Fine-tuning smaller models (Llama 8B) for domain-specific content filtering

Featured Technologies

• Llama 8 billion parameter model
• AWS SageMaker AI

Key Takeaways

• Fine-tuning smaller models for specific educational use cases reduced false positive rates to less than 3%
• Technology stack and models should remain flexible while keeping security, reliability, and scalability constant
• Close collaboration with cloud providers accelerates AI implementation and optimization
• The future of EdTech AI is moving toward agentic systems with improved observability and evaluation capabilities

Resources Mentioned

• AWS SageMaker AI
• Llama model family
• AWS Agent Core
• AWS Bedrock

Tags

#EdTech #K12Education #AWS #AI #MachineLearning #StudentSafety #ContentFiltering #PowerSchool #SageMaker #AgenticAI #reInvent