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Summer 2026 Enrollment Open
Build real AI projects with real mentors — for students in grades 7–12
Motivated students collaborate with experienced practitioners and researchers on focused AI projects with real deliverables — apps, research papers, and presentations that strengthen college applications and build the confidence to keep building with AI on their own.
Our Summer 2026 Programs
Summer 2026 has concluded. Here's what our three pathways looked like: intensive, project-driven, and mentor-led, with demo days, deliverables, and clear continuation paths. Summer 2027 details will be announced soon.
Summer 2026
Discovery Labs
Two Discovery experiences this summer · Open to grades 7 through 12
AI Fundamentals through hands-on projects. Online. 3 weeks. Three summer sessions: June 15 to July 3, July 6 to July 24, July 20 to August 7.
Hands-On Ocean Engineering. Offered in person at Pierrepont School in Westport, CT.
Summer 2026
Project Labs
5 weeks · July 6 to August 7, 2026 · 3 to 4 students per mentor
For students with programming experience ready to do real work. Each lab is led by a practitioner working on the problem in their actual career. Students contribute to research, build production-quality components, and present at Demo Day.
Summer 2026
1-on-1 Mentorship
5 weeks · Any five-week window between June 15 and August 7, 2026
For students who want a tailored experience. Four paths in: go deeper on a Project Lab topic with more individual attention, customize a Project Lab to fit your schedule, extend a Discovery Lab into a project of your own, or bring a defined idea and we'll match you with the right mentor. Best for capstones, research projects, and ideas a student wants to take seriously.
What Students Actually Do
Build and Deploy AI-Powered Applications
Students create functional apps—financial analysis tools, mental health platforms, educational systems—used in competitions, college applications, and real-world contexts.
Co-Author Research Accepted to Conferences
Students contribute to peer-reviewed research. Past work has been accepted to venues like NeurIPS and presented at academic conferences.
Present Work at Demo Days and Competitions
Every program culminates in presentations. Students pitch to mentors, peers, and external audiences—building communication skills alongside technical depth.
Continue Projects Beyond the Program
Many students extend their work independently or through Academic Year mentorship—publishing research, entering competitions, or contributing to ongoing systems.
This isn't a lecture series or a coding bootcamp. Students produce real work with real outcomes.
Mentorship, Not Instruction
Our mentors don't lecture. They guide, challenge, and collaborate—moving real work forward.
Mentors are researchers, practitioners, and builders with demonstrated expertise in their field. Every mentor brings real-world context, academic rigor, and the ability to guide students through open-ended challenges.
Mentorship is collaborative and personalized. Students don't watch videos or complete exercises. They work on authentic problems with structured support, regular feedback, and high expectations.
The focus is on moving real work forward. Mentors help students navigate complexity, make decisions under uncertainty, and produce artifacts that matter—papers, apps, research contributions.
Primary Mentor
Experienced practitioner or researcher
Direction, judgment, feedback
Teaching Assistant
Graduate or advanced scholar
Supporting mentors and students, debugging, momentum
AI Co-Teacher
Async scaffolding system
Available when mentors aren't
Why SeqHub AI Academy
We're AI researchers and K–12 educators with 30+ years of combined experience and advanced degrees from Yale, Stanford, and Brown. We build AI applications. We evaluate AI systems. We know what they can do — and where they break. And we know how students learn.
Most programs teach students to use AI. We go further: motivated students collaborate on real projects with experienced practitioners and researchers — learning to question AI's outputs, identify its limitations, and apply it responsibly.
Students leave with more than skills. They leave with judgment, agency, and the confidence to keep building with AI on their own.
Responsible AI Use & Parent Visibility
AI is powerful, and students need guidance. All programs emphasize responsible use, critical evaluation, and judgment—not blind dependence.
Students work within a structured learning environment supported by mentors, teaching assistants, and an AI co-teacher designed for learning—not shortcuts.
Our goal is not just skill acquisition, but thoughtful, healthy engagement with emerging technology.
How Enrollment Works
Enrollment is selective to protect quality and mentor capacity.
1
Submit a short application
Tell us about your background, interests, and goals.
2
We assess readiness and fit
We review each application to match students with the right program and cohort.
3
Families receive confirmation
Accepted students receive next steps, cohort details, and preparation materials.