The same problems top companies solve, built by high schoolers.
Our AI students don't follow tutorials. They pick a real industry challenge, the kind of thing Uber, Amazon, or JP Morgan actually spends engineering resources on, and build a working multi-agent AI system that solves it. Four weeks. Fully open-sourced on GitHub.
wProjects tackle the same challenges faced by
Every project. Every line of code.
Nine projects across nine industries. Each one tackles a challenge that real companies invest serious engineering resources in, and each one is fully open-sourced on GitHub so you can read every line, fork it, and make it yours.
Adaptive Language Tutoring System
Diagnoses learner weaknesses across six skill dimensions: grammar, vocabulary, reading, listening, writing, and speaking. Uses Item Response Theory to adapt difficulty in real time, builds personalized curricula that spend 60%+ of time on weak areas, and maps everything to the CEFR proficiency framework (A1 through C2).
Climate Weather Prediction & Disaster Alert System
Three-agent pipeline that forecasts extreme weather up to 10 days ahead. Ingests real atmospheric data (ERA5/GFS), runs autoregressive inference to detect cyclones, heat waves, and cold snaps on a 0 to 100 severity scale, then dispatches emergency alerts in CAP XML format, the same standard used by FEMA and the Red Cross.
E-Commerce Product Recommendation System
Merges explicit preferences with behavioral signals like browsing history, purchases, searches, and cart activity to deliver personalized recommendations. One agent builds a customer affinity profile, another scores the catalog through a multi-signal model, and a third picks a diverse final set while generating plain-language explanations for every suggestion.
GitHub PR Review Agent
Four agents that automate code review on pull requests. Parses diffs, classifies files by language, then runs two agents in parallel: one scanning for security issues (hardcoded secrets, SQL injection, XSS) with CWE references, the other checking style rules. A final agent deduplicates findings, ranks by severity, and posts inline comments.
Healthcare Prior Authorization System
Reviews clinical data for prior authorization decisions on diagnostic imaging (MRI/CT). Extracts symptoms, diagnoses, and treatment history from unstructured notes, scores each request against ACR Appropriateness Criteria on a 0 to 100 scale, and generates professional determination letters with APPROVED, DENIED, or PENDED decisions.
B2B Lead Scoring & Email Sequence System
Scores inbound B2B leads against an Ideal Customer Profile and generates personalized three-email nurture sequences. Enriches each lead with firmographic and behavioral signals, classifies them as Hot, Warm, or Cold, then tailors messaging by industry pain points, company size, and buying intent.
Soccer Sports Analytics System
Generates post-match summaries and pre-match win probability predictions. Ingests raw match data, produces natural-language reports covering key events and tactical observations, and computes outcome probabilities using team form, head-to-head history, standings, and squad availability.
Surge Pricing Agent System
Four agents simulate real-time ride-hailing supply and demand across five city zones. Computes surge pricing multipliers from demand/supply ratios, recommends driver reallocation between zones, and produces plain-English reports with full reasoning, making every pricing decision transparent and auditable.
Fraud Detection Co-Pilot
Three agents that flag, investigate, and summarize suspicious transactions. A Detector screens with rule-based and ML-driven signals. An Investigator does a deep dive with contextual evidence. A Summarizer compiles structured case reports, with a human checkpoint for high-severity cases before any final call.
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Your kid won't just “learn AI.” They'll walk out with a working system they designed, a GitHub repo they own, a program certificate, and a story that actually stands out on a college application.
Limited spots. Rolling admissions.