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Launch packet

Private beta launch packet for the ML theory learner loop.

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

What is real now, and what is not.

Methodology

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.

Experimental

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.

Data-insufficient

Live production rows are still too sparse for calibrated IRT, validated PFA personalization, or paid-acquisition claims about retention improvement.

Functional funnel

The beta should prove that a learner can find a useful next action without a guided sales call.

Beta cohort fit

The first beta group should test the learner loop, not just browse the library.

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.

Good fit

Graduate ML applicants, research engineers, self-studying ML practitioners, and math/statistics learners who can spend one focused week testing the loop.

Not the right fit yet

Learners who need a fully guided beginner course, live tutoring, app-store polish, or verified learning-effectiveness claims before trying the product.

One-week feedback contract

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

Demo media comes after the product path is repeatable.

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.

Five-minute product walkthrough

Real browser and simulator capture. Show home, Atlas, one flagship ML page, Evidence, signed-in state, and iOS continuity.

Ninety-second research demo

Use one ML path, one evidence boundary, one signed-in action, and one iOS handoff. Include one limit statement.

Short ad test

Run only after activation and retention baselines exist. The creative can show the product, but it must not claim measured learning gains.

Generated presenter layer

Use a presenter video pipeline only after the script is locked and real product footage has passed review.

Public web stills

The screenshot set now comes from real captured routes.

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.

Private beta launch packet (Desktop 1440x1100): The launch packet explains product truth, funnel, media, monetization, and release gates.
Private beta launch packet (Desktop 1440x1100)The launch packet explains product truth, funnel, media, monetization, and release gates.
Atlas graph path (Mobile 390x844): The graph/navigation surface can be shown in the demo without sign-in.
Atlas graph path (Mobile 390x844)The graph/navigation surface can be shown in the demo without sign-in.
Flagship ML topic: scaling laws (Desktop 1440x1100): A flagship ML topic can anchor the content-quality portion of the walkthrough.
Flagship ML topic: scaling laws (Desktop 1440x1100)A flagship ML topic can anchor the content-quality portion of the walkthrough.
Flagship ML topic: transformer architecture (Mobile 390x844): A second flagship ML topic can support the short-form and screenshot set.
Flagship ML topic: transformer architecture (Mobile 390x844)A second flagship ML topic can support the short-form and screenshot set.

Static captures are the public-web layer only. Signed-in web, account deletion, iOS continuity, and video footage remain separate release gates.

Monetization boundary

The site can invite beta users now. It should not sell outcomes before the learner metrics support them.

Free public library

Flagship ML pages, Atlas paths, and evidence surfaces remain useful without payment.

Future paid layer

Candidate paid value is advanced review, saved trail history, research interview prep, and private progress reports.

Paid growth gate

Ads wait for measured activation, day-7 retention, and a repeatable private-beta onboarding path.

Release gates

Checkpoints before a broader push.

  • Production web build and critical anonymous flows are green on main.
  • Signed-in web walkthrough covers Today, Atlas, Saved, Profile, and deletion.
  • iOS archive, App Store Connect validation, privacy labels, and screenshots pass.
  • Fresh demo screenshots show real routes without secrets, raw emails, or tokens.
  • Evidence and methodology pages state FSRS, Q-matrix, PFA, and data-insufficient boundaries.
  • Paid acquisition waits for measured activation and day-7 retention baselines.