Not a team and a quarter, but a pipeline and a week: a turnkey digital ecosystem
For an expert partner I designed and built an app, a book, a Telegram bot, three landing pages and a publishing engine — six connected products in one funnel, through AI orchestration, in 10 days.
доказаноevery number checkable in code and gitкак проверяем →
A warm audience with no product — into a funnel of six
The expert partner had years of hard-won expertise in women’s fitness and a warm audience that trusts her. There was nothing that turns that trust into a product: no engineering team, no app, no funnel from free content to payment. The task — turn it into an honestly selling ecosystem.
An 18-sheet program in Excel
The expertise and the warm audience are there. An engineering team, a sellable product and a funnel that turns reach into revenue — are not.
App · book · bot · 3 landing pages · publishing engine · funnel
Six subsystems glued into one funnel. Designed, built, verified, shipped to production.
Three constraints shaped the whole architecture: honesty instead of the market’s dark patterns, safety on a sensitive topic (a route to a doctor, not a protocol) and data-protection law built into the design, not bolted on before launch.
Six products, one funnel
Six subsystems — each a product in its own right, but all glued into one shared customer path. Next to each — its role in the funnel and a scale you can check in the code.
Three landing pages — reach and conversion
Three product entry points in one repository: 8 routes, all statically prerendered; interactivity is targeted client islands, not full hydration of the page. Transparent prices, 0 fake discounts.
olgakashina.ru ↗The book “Biology of a Winner” — the trial product
The trial product (₽880): 43 chapters / 261 A5 pages, PDF + reflowable EPUB 3 (epubcheck — 0 messages), 3 editions from a single source, 59 named cross-references.
book.olgakashina.ru ↗The PWA “Dream Glutes” — the core
The program product (₽2490): an 8-week strength program, nutrition, a progress section, offline sync. 42,510 lines of TS/TSX, 111 components, 21 REST routes, 25 tables, 66 tests.
app.olgakashina.ru ↗olgakashina.ru/app ↗The Telegram bot — top of the funnel
A free 7-day drip series, 16 guaranteed touches, consent before the message. 31 files, 1543 lines, a 7-state state machine. It hands payment off to the app’s checkout — and owns the rhythm itself.
t.me/bootyfit_bot ↗The content machine — strategy and reach
Competitive intelligence: 9 competitors, 785 links, 36 landing pages, 42 verified prices. A unified brand strategy and an ethical frame: for every dark pattern, an honest replacement was found.
t.me/kashina_fit ↗vk.com/kashina_fit ↗Design system and infrastructure
An agent-callable design system (tokens with no hardcoded hex colours), a video-production tool, a meta-repository with CI and document memory: 1 head + 6 nested modules, a single “ecosystem version” commit.
Five stages — from reach to retention
The six products aren’t a set, they’re a route. A subscriber enters at the top on free content and descends to the core program. The principle running through every stage — honesty instead of dark patterns: transparent prices, hooks with no email harvest, a route to a doctor instead of fearmongering.
Reach
no emailA link in the profile plus a hook and a sample chapter. A model of attraction: reciprocity with no strings.
Free 7-day drip series
freeTelegram bot: 16 touches (morning / evening / check-in), consent before the start, hand-off to paid on day 7.
Trial product — the book
₽880“Biology of a Winner” in PDF + EPUB. A landing page with a preview, payment, and an access email.
Core — the program
₽2490A PWA app: sign-in (PAR-Q + consent) → workouts / nutrition / progress.
Retention
Lifecycle notifications in Telegram via an outbound queue, reminders, a small reward for the path completed.
The prices ₽880 and ₽2490 are the expert partner’s product prices in the funnel, not temadev’s service fees.
Behind the speed — senior-engineer decisions
Speed is suspicious — so it matters more to show what’s behind it. This is no trick and no “generate and forget”: under the hood are senior-engineer decisions, each checkable in the code. Here are eight that tell engineering from a prototype.
Offline at the core
localStorage is the source of truth; conflicts resolve by “last write wins”, the server is secondary. A deliberate choice for reliability on mobile with no network.
Payments independent of the provider
A registry maps a provider ID → adapter; providers switch by an environment flag with no single code change. Idempotency via order-id and a re-check request.
Data-protection law: two-way erasure
app↔bot through a reliable outbound queue with reconciliation. Erasure is atomic in one transaction — no break if it fails between “deleted” and “queued”.
Least-privilege tokens
Each channel gets its own secret; a missing secret = the feature is honestly switched off (503), not a crashed process. A safe, staged launch.
Adversarial checking at scale
Each block passes N independent veto lenses plus a 4th layer — a fresh agent with a mandate to “break this”. Not a sequential review, but real adversarial pressure.
One source → many editions
One stream of book tokens → PDF + EPUB + a short summary; one product config → landing pages and offers. Edit in one place, deterministic rebuild — the author touches only .md.
Static at the core, targeted interactivity
Every route is statically prerendered; client JS only where interactivity is needed: targeted islands, not full hydration of each page. “‘use client’ when needed”, not by default.
Health safety as determinism
Sensitive input is routed by fixed regex patterns, not free LLM generation. On risky topics — a route to a doctor, not a prescribed protocol.
Not “I use ChatGPT”, but an adversarial pipeline
How do you fit so much into 10 days? The lever isn’t typing speed but a designed orchestration pipeline: agents research, write and assemble, while I hold the truth and the decisions. The key — checking that isn’t sequential but adversarial: every block is attacked, not just “looked at”.
- step 1Draft
an agent writes a block
- 3 veto lenses ∥Attack, not review
facts · safety · voice — in parallel
- decisionTo production or back
a binary quality gate
- 4th layer“Break this”
a fresh agent hits the assembled block
One adversarial run — the book audit: 62 agents → 77 findings → 53 confirmed, 1 false. 200+ agents ran through the content cycles, each with a real wf_* id.
доказаноthe audit and the agent count — by reports with wf_* idscheck on /proof →
Live. I claim only what’s provable.
The system is shipped to production, YooKassa payments work — the products can be opened right now. I don’t speak of revenue or customers as fact: the first cohort has only just started. I claim only what’s provable — I’ll publish the numbers once I can confirm them.
- in production
YooKassa payments work. The provider switches by a flag: lava.top ↔ YooKassa — with no code rewrite.
- in production
Data protection by law: consent on collection and full erasure on request — in both the app and the bot — built into the code, not bolted on before launch.
- in production
42,510 lines of TS/TSX, 66 tests, CI gates on every module, EPUB epubcheck — 0 messages.
- awaiting the cohort
I don’t pass revenue or customers off as fact — the first cohort has only just started. I claim only what’s provable; I’ll publish the numbers once I can confirm them.
- awaiting the cohort
Reviews and before/after — I publish only with consent and only once I can confirm them.
A designed pipeline — the work of a whole team
Six connected products in one funnel in 10 days and 145 commits — by orchestrating 200+ agents. Not “a person plus ChatGPT”, but a designed pipeline with adversarial checking, where every number is checkable in code — with senior-engineer discipline: CI gates, dated audits, schemas-as-contracts, debt tracked explicitly.
Next — three doors.
How the pipeline works
Not “a person plus ChatGPT”, but a designed pipeline: phases, the human/AI role boundary, adversarial checking across 200+ agents.
Открыть →ApplicabilityPorting it to your niche
The method is niche-independent: 80% of the build carries over as a frame, 20% is rewritten for the subject. Plus the honest limits.
Открыть →ProofCheck every number
Behind every number — code, a git command or an artifact. Don’t take my word for it — check.
Открыть →Common questions
Let’s work out how this applies to your product
The same method ports to another niche. Write to me — we’ll discuss what here gives you the lever.