AI made traditional programming teaching obsolete. Instead of fighting it, flip it. AI generates unlimited unique problems per student, making each attempt genuinely their own. Real fluency through repetition, fair exams drawn from the same pool.
Launching Fall 2026 · Free pilot for early adopters
def find_shortest_route(graph, start, end):
# A delivery drone needs the fastest
# path between two warehouses...
queue = [(0, start, [])]
while queue:
cost, node, path = heapq.heappop(queue)
if node == end:
return path + [node]
Trusted by CS/CE/EE departments at forward-thinking universities
Educators face an impossible triangle: meaningful assignments, fair assessments, and manageable grading workloads. Something always gives.
A few fixed questions per semester? Easy to cheat or memorize. Many problems? Grading becomes impossible. Ungraded work? Students ignore it. There has to be a better way to motivate students to code.
Creating fresh problems each semester takes days. Reusing them invites plagiarism!
AI generates a unique solution with a single prompt. Detecting copying automatically is now impossible.
ChatGPT can solve any fixed assignment. With static problems, AI becomes a shortcut instead of a study tool.
The only way to learn programming is by writing code. Not listening. Not reading. Not watching videos. Coding. Like reps in the gym, mastery comes from repeated practice.
Follow your curriculum and create topics you want to test: loops, recursion, functions, you decide. Control the number of problems and test cases per topic.
AI creates different versions of each problem wrapped in unique, creative real-world scenarios.
Each student gets a personalized version of every problem. Practice daily. Repetition builds genuine fluency.
Quiz and exam problems are drawn from the same huge pool. Randomized and cheat-resistant. Proctoring is on you. Clarity about what to expect motivates students to study, proven in practice!
Same algorithm, different story every time. AI creates engaging real-world scenarios that keep students thinking, not memorizing.
Students build fluency through spaced repetition. Each rep reinforces the pattern until it becomes second nature.
Lock down exams in a controlled environment. Problems are drawn from the practice pool, randomized per student.
After each assessment, students get targeted, AI-generated feedback explaining what they got right and where to improve.
Track mastery across topics and students. Identify who needs help before they fall behind.
Invite TAs, organize problem sets by topic, and manage multiple sections from a single dashboard.
CS151 Programming Fundamentals is the core freshmen course at Nazarbayev University. Our CS department keeps growing – last semester we taught a class of 300 students. We used to “live grade,” where every student comes in and defends their solution. That became impossible at this scale. With only a few fixed problems, I felt we stopped giving students enough opportunity to practice. To my surprise, by the final exam there were students who could not code at all. So I decided to use AI to generate a large pool of questions at the start of the semester and told students that quizzes and exams would be drawn from that pool. The effect was twofold: first, expectations became crystal clear – students knew exactly what to study and the effort was there. Second, engagement jumped – more students came to office hours trying to clarify specific questions from the pool. And because every student’s quiz was drawn from their own unique set, cheating attempts dropped significantly. Proctoring still has to be airtight, but that’s something I can guarantee 100%.
Launching Fall 2026. Pick a time below to see codereps.ai in action and discuss a free pilot for your course.