Implemented
The site has flagship ML pages, Atlas paths, source-linked evidence, diagnostics, signed-in learner state, saved topics, review entry points, privacy pages, and an iOS companion contract.
Launch packet
This page turns the current product truth into a launch plan: what a serious learner can try, what the demo may claim, what is still experimental, and what must pass before paid growth.
Last reviewed: July 5, 2026
Product truth
The site has flagship ML pages, Atlas paths, source-linked evidence, diagnostics, signed-in learner state, saved topics, review entry points, privacy pages, and an iOS companion contract.
The learner loop uses FSRS-style review state, Q-matrix skill links, and guarded PFA-style mastery updates. Those signals guide study actions; they are not proof of learning lift.
Live production rows are still too sparse for calibrated IRT, validated PFA personalization, or paid-acquisition claims about retention improvement.
Functional funnel
Beta cohort fit
The ask is narrow: one week, one real study goal, and blunt feedback about the next action. That keeps the beta useful before paid acquisition or broad marketing.
Graduate ML applicants, research engineers, self-studying ML practitioners, and math/statistics learners who can spend one focused week testing the loop.
Learners who need a fully guided beginner course, live tutoring, app-store polish, or verified learning-effectiveness claims before trying the product.
Use one topic path, save at least one item, attempt review, and report whether the next action is clear, where the curriculum loses you, and what would make you return.
Marketability
The strongest video asset is not a static explainer. It is a real run through the app: graph, topic, evidence, signed-in state, and mobile continuity. Generated presenter footage is useful only as a finishing layer after real captures pass.
Real browser and simulator capture. Show home, Atlas, one flagship ML page, Evidence, signed-in state, and iOS continuity.
Use one ML path, one evidence boundary, one signed-in action, and one iOS handoff. Include one limit statement.
Run only after activation and retention baselines exist. The creative can show the product, but it must not claim measured learning gains.
Use a presenter video pipeline only after the script is locked and real product footage has passed review.
Public web stills
These are optimized production-style WebP captures recorded in the launch receipt. They are safe for static launch materials, but they do not prove signed-in state, iOS continuity, or learning outcomes.




Static captures are the public-web layer only. Signed-in web, account deletion, iOS continuity, and video footage remain separate release gates.
Monetization boundary
Flagship ML pages, Atlas paths, and evidence surfaces remain useful without payment.
Candidate paid value is advanced review, saved trail history, research interview prep, and private progress reports.
Ads wait for measured activation, day-7 retention, and a repeatable private-beta onboarding path.
Release gates