Part 2: Taking Back Control—How Schools Can Build Their Own AI-Driven Tools

In Part 1 I laid out the challenges of consolidation and the potential disruption of SaaS by AI, and then Part 2 is about solutions. The education sector doesn’t have to wait for the next wave of mergers or the next PowerSchool data breach to dictate the tools that schools rely on. The advent of AI, combined with increasingly powerful no-code and open-source technologies, presents an opportunity for schools to reclaim control, build custom tools, and shape their own digital ecosystems.

Why Build Instead of Buy?

For decades, schools have been at the mercy of EdTech vendors, forced to choose from a limited menu of software solutions that often fail to fully meet their needs. With the growing accessibility of AI, that dynamic is starting to change. Schools now have the capability to create customized, AI-powered tools that align with their unique instructional models and operational priorities.

Why Schools Should Think Like Builders Instead of Just Buyers:

• Redefining the culture: Encouraging educators to build their own solutions cultivates an innovation mindset, shifting teachers from being passive consumers of technology to active problem-solvers. This process reestablishes educator agency, giving them tools to directly address classroom challenges and rethink instructional models from the ground up.

• Customization & Flexibility: AI allows for tailored solutions that meet the exact needs of a district, school, or classroom.

• Cost Efficiency: No-code and open-source solutions dramatically reduce development costs compared to traditional software procurement.

• Data Sovereignty: Schools can retain control over their student data rather than handing it over to third-party providers.

• Scalability & Adaptability: AI-driven tools can evolve alongside shifting educational needs, avoiding vendor lock-in.

Leveraging No-Code, AI, and Open-Source Tools

The rise of no-code and AI-assisted development platforms means that schools no longer need a dedicated software engineering team to create functional, impactful digital tools. It can be pretty overwhelming to try and sort your way through the noise and options, so I tried to lay out what I think can be a helpful roadmap for those interested in getting involved in building their own solution. As a sort of build-in-public project, please consider this as one pathway to explore and not the ONLY path.

The roadmap should begin with experimenting with free open resources like ChatGPT, Gemini, etc. This can help establish a basic understanding of how LLMs work. It’s also the best place to start when trying to build full applications because it helps refine your idea through a conversation.

How Schools Can Start Experimenting:

• AI-Powered Chatbots for Student & Teacher Support: Tools like Chipp.ai and Poe provide structured, easy-to-implement AI chatbot solutions that can streamline workflows, assist students, and enhance teacher productivity.

• Text-to-Web Design AI: Schools can now leverage AI models that specialize in coding, allowing educators to describe their needs in plain text and have an AI model generate the underlying code. This approach makes software development more accessible than ever.

• Stacking AI Tools for Development: When no-code web design tools struggle to interpret user intentions, AI coding assistants like Cursor or ChatGPT can help debug, refine, and explain the generated code—effectively making custom app development possible for non-technical users.

• Learning Record Stores & Digital Portfolios: Instead of relying on external platforms for credentialing and learning tracking, schools can explore blockchain-based learning records or decentralized academic portfolios.

• Custom Student Dashboards & Learning Analytics: Using platforms like Retool or Glide, schools can create personalized dashboards that track student progress, interventions, and engagement data in real time.

Thinking like an architect can help not only enhance classrooms and schools but also use the mindset and culture shifts as a springboard to further transformation.

Challenges & Considerations

While the potential for AI-driven, school-built solutions is immense, there are important considerations to address:

• Training & Capacity Building: Educators and school leaders need to build the knowledge and skills necessary to leverage no-code and AI tools effectively.

• Data Privacy & Security: Schools must ensure that custom-built solutions comply with student data privacy laws and cybersecurity best practices.

• Interoperability: Custom-built tools should be designed to integrate seamlessly with existing school systems and data infrastructures.

A Call to Action: Schools as Digital Architects

Education is at an inflection point. Schools can continue relying on large EdTech vendors and risk further consolidation, higher costs, and reduced flexibility—or they can embrace AI and no-code solutions to reclaim control of their digital infrastructure. The tools to build custom solutions have never been more accessible, and the time to start experimenting is now.

The transition from consumers to creators will require a mindset shift, but the payoff is significant: a future where schools dictate their own technological needs, ensuring that digital tools serve students and educators first—not just corporate bottom lines.

Over the next few weeks, I’ll share more about my work in this space—including the launch of the 12 in 12 Project, a challenge designed to demonstrate how educators can rapidly build their own EdTech solutions using no-code and AI. Stay tuned for some updates this week!

If you’re interested in following this journey and seeing firsthand how schools can take back control of their technology, let’s connect!