AWS Public Sector Blog
How Sphero brings safe, impactful AI to K12 classrooms with Amazon Bedrock
Robots are rolling through K12 classrooms as teachers use them for everything from biology and math assignments to language arts lessons. Students program these robots, often in sessions as short as 15 minutes. Getting stuck is part of the learning process, but with class sizes and finite period lengths, waiting for help isn’t always an option. And even when a teacher can get there, troubleshooting code on the spot isn’t simple.
Sphero, a company that creates programmable robots for K12 education, built a generative AI coding assistant into its Sphero Edu app using Amazon Web Services (AWS) to solve that problem. Students don’t type prompts or interact with an open interface. Instead, they tap a single button and receive immediate, focused feedback on their code. That one-click design reduces the risk of unpredictable outputs reaching students, keeping every AI interaction safe, age-appropriate, and focused on learning. It’s an approach that earns teacher trust and addresses the concerns that have made many schools hesitant about AI in the first place.
Thirty kids, 15 robots, and one teacher
Sphero’s current users are mostly elementary and middle school students in third through sixth grade who use Chromebooks, iPads, or tablets to control a small programmable robot using Bluetooth. Teachers use these robots to supplement learning across subjects, from coding exercises to science experiments.
In a typical session, students write a program, run it, and watch what the robot does. If something goes wrong, they try to figure out why. But in a room full of students working at different speeds, there’s no guarantee the teacher can reach everyone before the lesson ends. “Thirty kids in a classroom with 15 robots rolling around—the teacher can only do so much,” said Brian Kellner, vice president of software engineering at Sphero.
Sphero built the AI assistant to fill that gap, helping teachers support more students in the moments that matter and helping students think through challenges more deeply. Rather than giving students the complete answer, it offers hints, explanations, and guided feedback, preserving the trial-and-error learning cycle that makes robotics effective in the first place.
Why safety shaped every design decision
Before Sphero considered how AI could assist students, the team thought about what could go wrong. Schools have strict and varying policies around technology, and Sphero had already seen a school discontinue use of its products after a student-shared program displayed a cartoon sword image that violated a zero-weapon policy. That experience helped shape how Sphero would approach AI, leading the team to a guiding principle for whatever they built: safe, simple, and valuable, in that order.
“As AI settles in schools, we must be cautious about what power we give students and how schools might respond to what AI can do,” said Micah Daby, product manager at Sphero. Kellner agreed: “If we say safe, simple, valuable, we want to be able to stand behind safe.”
Building on an existing AWS foundation
Sphero had been running its infrastructure on AWS for years. When Kellner began exploring AI, the AWS account team helped move the project from broad ideas to a viable first use case. An AWS-funded proof of concept kicked off in April 2025 and validated the technical approach by the end of May. Sphero spent the summer testing and refining prompts with its internal content team, then released the AI assistant in August for the back-to-school season.
“When we first started looking at adding AI to our products, we were not very grounded,” said Kellner. “The AWS account team guided us to experts to help us refine our ideas into something feasible, then helped us define a scope of work for the first phase. That gave us clarity on what we would build and how it would work.”
How the Sphero Edu AI assistant works
The AI space evolves quickly, and Sphero didn’t want to be locked into a single model. Because of this, the team chose Amazon Bedrock for its flexibility. Sphero can update the knowledge base, switch models, and build new features on the same foundation. For a nine-person software team, that manageability matters. “I can go in and change things in the knowledge base and resync it without heavily involving engineers working on other critical needs,” said Daby.
Amazon Bedrock Knowledge Bases is at the core of the AI assistant. Using a Retrieval Augmented Generation (RAG) approach, the AI pulls from a curated set of Sphero documents to generate grounded responses rather than relying on the model alone. The knowledge base draws from Sphero’s programming wiki and internal documents stored in Amazon Simple Storage Service (Amazon S3), covering robot-specific behaviors, hardware limitations, and common student errors. This means the AI can only respond to Sphero robots and programming, and updates sync in about a minute as the team adds new information. When teachers report that a response was inaccurate, Daby can usually fix it by updating the knowledge base directly, keeping the tool grounded in real classroom use.
What students see is a set of one-click features inside the Sphero Edu app. Explain My Program breaks down what their code does in plain language. Code Review checks for errors, including issues students wouldn’t know to look for, like a spin command that is physically impossible for the motor to execute in the given time. Block Help explains any specific block, tailored to whichever robot is connected. A fourth feature gives Sphero’s content team the ability to embed AI hints directly into structured lessons, so students get guided feedback at the right moment without the AI solving the problem for them.
Amazon Bedrock Guardrails handles safety on the backend, filtering both input and output. Because the AI features are one-click, students can’t enter free-form prompts in most of the app. The only variable the AI receives is the student’s program code, which limits the surface area for misuse. Even in the one lesson where students can type short text into speak blocks, the prompts instruct the model to treat that input with extra caution. The team also ran prompt-injection tests and found that the model recognized and ignored these attempts.
Most students get what they need in one click
Since launching in August 2025, the Sphero Edu AI assistant has been accessed more than 15,000 times per week. The most telling metric is how few clicks students make when using it. About 65% of students who use the Explain My Program feature click it one time and return to their lesson with what they need. “They’re in a 15-minute session with their robot, they click, they get some good feedback, and they get on with it,” said Kellner.
In that context, response speed matters. Staging tests showed that Claude Haiku 4.5 by Anthropic in Amazon Bedrock delivered roughly half the response time at about one-third the cost compared to Claude Sonnet 3.7 by Anthropic in Amazon Bedrock. Sphero decided to transition to Claude Haiku, with responses rarely exceeding 15 seconds. Reliability has been strong, too, with the team recording only eight errors over a recent 3-week period.
Teacher feedback has reinforced the approach. At a live webinar, educators said the tool added value without requiring new purchases or additional training. “It’s so cool that students can interact with AI without having the safety issues surrounding entering their own prompts,” said one educator. “It’s an amazing resource for cross-curricular learning.”
Multilingual support, vision capabilities, and what comes next
Sphero is developing a feature that gives students hands-on experience training machine learning (ML) models using sensor data from their robots—for example, training the robot to recognize when it’s shaken and respond with lights or sound. Daby is also working on multilingual support, so the assistant can respond in the student’s language, extending accessibility to non-English speakers. Vision and image processing capabilities are in the early stages of exploration.
For other education technology (EdTech) companies considering AI for K12, Kellner’s advice is straightforward: “Put yourself in the shoes of the teacher. What is a teacher really going to experience with your tool in the classroom? Teachers have a tough job. Finding what works for them is important.”
Sphero’s educator guide goes deeper into how the company approaches student safety, AI literacy, and classroom resources for teaching AI with hands-on robotics. Read Sphero’s guide now or, to learn more about how AWS supports EdTech companies building AI solutions for education, contact the AWS EdTech team.