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Lila — Feature & Startup Strategy Roadmap

Context for any LLM reading this: Lila is a language learning/vocabulary app with two core differentiators: (1) media-based practice — users learn vocabulary extracted from real media they love (e.g., a Shakira song, the first chapter of Harry Potter, or an episode of Breaking Bad), and (2) multiplayer modes — users practice vocabulary together or competitively in real-time sessions. The app is currently at an early MVP stage. The existing MVP was built around OpenWordNet, which is being replaced because it produces unreliable translations (sense-disambiguation issues). The team is migrating the data pipeline to Kaikki, which structures entries per word sense and links translations to specific senses rather than vague general concepts. This migration is the current technical priority. The project is a TypeScript monorepo (pnpm workspaces) with an Express/WebSocket API (apps/api), a React frontend using TanStack Router (apps/web), a data ingestion pipeline (data-pipeline) backed by SQLite/Drizzle, shared packages (packages/db, packages/shared), and Docker-based deployment orchestrated with Caddy. Documentation restructuring (human-readable vs. AI-optimized docs) is being handled in a separate parallel workstream.

Current State (Ground Truth — 2026-05-15)

What Works Today ✅

  • Singleplayer quiz — Duolingo-style, 5 language pairs (en↔it/de/es/fr), 3 or 10 rounds, POS + difficulty filters
  • Multiplayer — Create/join lobby by room code, 2–4 players, simultaneous answers, 15s server timer, live scoring, winner screen
  • Auth — Google + GitHub via Better Auth
  • Deployment — Live at lilastudy.com, Hetzner VPS, Caddy HTTPS, Docker Compose, CI/CD via Forgejo Actions
  • Database — PostgreSQL with Drizzle ORM, daily backups

What's In Progress / Blocked 🚧

  • Kaikki data pipeline migration — Stage 1 (extract) and Stage 2 (reverse link) complete on sample data. Stage 3 (enrich) being rewritten for sub-stage architecture. Stages 4–6 not started.
  • Guest play — No try-before-signup flow yet. Auth required for all game routes.
  • Game session store — Still in-memory. Valkey container exists locally but not wired up.
  • Media ingestion — Not started. No pipeline for subtitles/lyrics → vocab extraction yet.

The Strategic Gap

The app is currently a generic vocabulary quiz. The media-based practice feature (the differentiator) does not exist yet. It depends on:

  1. Kaikki pipeline reaching production (fixes translation quality)
  2. A media ingestion prototype (subtitles/lyrics → text → vocab extraction → quiz)

Stream 1: Documentation Restructure (Parallel Track)

Status: ✅ Complete. Human-readable branch (README, STATUS, ARCHITECTURE, BACKLOG, DECISIONS, DEPLOYMENT, DATA_PIPELINE, MODEL_STRATEGY, LLM_SETUP, design/GAME_MODES) and AI-context branch (00–06, prompts/meta.md, 99-current-task.md) are live in documentation/.

Stream 2: Feature Roadmap (Three Lanes)

Lane A — Attract & Keep Users

Goal: A user lands on Lila, understands the value in 10 seconds, and completes a satisfying vocabulary practice session in under 2 minutes.

Current Reality Check:

  • Singleplayer and multiplayer quizzes are already working and deployed.
  • The app is functional but not differentiated — it's a generic vocabulary quiz right now.
  • The "wow" moment requires the media-based practice feature, which does not exist yet.

Must-Haves for First Users:

  1. Guest Play (Zero-Friction Onboarding) [in backlog next]

    • No signup required for first session.
    • Capture email or OAuth only after the user experiences value.
    • Critical for viral loops and investor demos.
    • Status: Planned in BACKLOG.md. Not yet implemented.

  2. One Polished Media Demo [not started]

    • Pick ONE piece of media and make it flawless end-to-end: subtitles/lyrics → Kaikki-based vocab extraction with sense-disambiguated translations → playable quiz with timestamps/context.
    • Candidates: Breaking Bad S01E01, a Shakira song, or Harry Potter and the Sorcerer's Stone Ch. 1.
    • This is the primary "wow" moment. Differentiates Lila from all other vocabulary apps.
    • Blocker: Requires (a) Kaikki pipeline in production, and (b) a media ingestion prototype.

  3. One Additional Multiplayer Mode [design exists, not implemented]

    • Proves the mode-agnostic lobby architecture works and adds variety beyond the current simultaneous-answer flow.
    • Recommended first mode: Race to the Top (target score, no round limit) — simplest to implement, changes only scoring logic.
    • Alternative: TV Quiz Show (buzzer — first to press answers) — most visually distinct, but requires new answer flow.
    • Status: Lobby infrastructure is mode-agnostic. Each mode adds game logic only. See design/GAME_MODES.md for full designs.
    • Why it matters: Duolingo has no multiplayer. Anki has no multiplayer. Real-time modes are a genuine differentiator even without media.

  4. Social Proof / Shareable Output [not started]

    • Post-game card: "I learned 12 words from La Tortura — can you beat my score?"
    • Image export or copy-paste text for Reddit, Discord, Twitter.
    • This is the organic growth engine.
    • Blocker: Requires media demo to exist first.

Already Shipped (Don't Rebuild):

  • ✅ Singleplayer quiz (5 languages, POS/difficulty filters)
  • ✅ Multiplayer lobby + real-time game (2–4 players, simultaneous answers, 15s timer, scoring)
  • ✅ Auth (Google + GitHub)
  • ✅ Live deployment with CI/CD

Nice-to-Haves (Post-Launch):

  • Additional multiplayer modes (Chain Link, Elimination Round, Cooperative Challenge)
  • Leaderboards
  • Spaced repetition review queue
  • Additional game modes (see design/GAME_MODES.md)

Lane B — Investor-Ready

Goal: Walk into a pitch with engagement metrics and a defensibility story tied to Lila's unique data pipeline.

Checklist:

  1. Metrics Instrumentation [not started]

    • Track: DAU/MAU, session length, quiz completion rate, multiplayer match completion rate, Day 1 / Day 7 retention.
    • Tool: PostHog, Mixpanel, or Plausible (self-hosted).
    • Need 4–6 weeks of real-user data.
    • Note: The app is live but has no analytics. This is a prerequisite for any investor conversation.

  2. Growth Mechanic [not started]

    • The shareable card (Lane A.3) must be live and instrumented.
    • Measure k-factor (viral coefficient). Even 0.3 is a story.
    • Blocker: Requires media demo.

  3. Defensibility Story [partially true, not yet proven]

    • Data moat: Lila's Kaikki → media mapping pipeline produces sense-disambiguated vocabulary tied to specific media timestamps. Competitors using generic word lists or OpenWordNet-style dumps cannot match the precision.
    • Current reality: The Kaikki pipeline exists but is not in production. The media mapping pipeline does not exist yet.
    • What investors would ask: "You have a quiz app. Where's the media feature you pitched?"
    • Requirement: Media demo + Kaikki production data must be live before investor conversations.

  4. Monetization Hypothesis [not tested]

    • Pick ONE model to test:
      • Freemium: Free media, premium for user uploads / unlimited multiplayer / advanced analytics.
      • B2B: Schools and language institutes buy group licenses.
      • Affiliate: Deep-link to streaming services, books, or music platforms.
    • Don't implement yet, but explain LTV/CAC math and pricing assumptions.

Investor Timeline:

  • Now → Month 2: Finish Kaikki pipeline + ship media demo + add metrics.
  • Month 2–3: Soft launch to 100 strangers, gather retention data.
  • Month 3+: Investor-ready if retention curves look good.

Lane C — Co-Founder-Ready

Goal: A potential co-founder looks at Lila and thinks, "This person can build, and there's a real product here."

Checklist:

  1. Clean Codebase + Documentation [in progress]

    • Documentation restructure is complete.
    • README must get a new dev from git clone to docker compose up in < 5 minutes.
    • Status: Docs are done. Code cleanliness is ongoing (BACKLOG.md next/later items).

  2. Live Demo with Real Users [partially done]

    • App is live at lilastudy.com with real auth and multiplayer.
    • Gap: No real users yet. The current app is a generic quiz — not compelling enough for strangers to stick around.
    • Requirement: Media demo must be live before pitching to potential co-founders.

  3. Clear Vision Doc [not written]

    • 1-page: What Lila is, what it isn't, and the 18-month arc.
    • Include: target languages, target media types, target user persona, and what "success" looks like at 6 / 12 / 18 months.

Stream 3: Building the Startup (Technical Founder Journey)

Phase 1 — Differentiate the MVP (Now → Month 2–3)

Duration: 2–3 months
Rule: Do NOT look for a co-founder yet.

Why: The MVP is already built and deployed. What's missing is the differentiating feature (media-based practice). A co-founder won't help you build this faster — it's a technical/data problem. Also, you need leverage: "I built the MVP AND the media pipeline" is stronger than "I have an idea for a media pipeline."

Tasks:

  1. Finish Kaikki pipeline (Stage 3–6)

    • Complete enrich sub-stage rewrite
    • Run full sample, validate quality
    • Production sync to PostgreSQL
    • Timeline: 2–4 weeks

  2. Build media ingestion prototype

    • Pick ONE media piece (Breaking Bad S01E01, Shakira song, or Harry Potter Ch. 1)
    • Pipeline: subtitles/lyrics → text extraction → vocabulary identification → Kaikki sense-matching → quiz generation
    • UI: media selection → quiz with context ("This word appears at 00:04:23")
    • Timeline: 2–4 weeks (parallel with Kaikki pipeline)

  3. Ship guest play

    • Make auth optional on game routes
    • "Try without account" button on landing page
    • Capture email/OAuth after first session
    • Timeline: 1 week

  4. Add metrics instrumentation

    • PostHog or Plausible
    • Track: signups, quiz starts, completions, multiplayer matches, retention
    • Timeline: 1 week

  5. Soft launch to 100 strangers

    • Reddit (r/languagelearning, r/Anki), language-learning Discords, Hacker News Show HN
    • Collect qualitative feedback
    • Timeline: 1 week (after media demo is live)

Phase 2 — Validate & Measure (Month 2–4)

Goal: Prove that the media feature resonates and that retention curves exist.

Tasks:

  • Analyze metrics: Do users who try media-based practice return more than singleplayer-only users?
  • Iterate on media selection and quiz UX based on feedback
  • Polish shareable output (social cards)
  • Fix hardening items from BACKLOG.md Phase 7

Decision gate: If 100 users show positive retention signals (Day 1 > 30%, Day 7 > 10%), proceed to Phase 3. If not, iterate on media feature or pivot.

Phase 3 — Define the Gap (Month 3–5)

Goal: Identify exactly what you suck at or hate doing.

The wrong approach: "I need an MBA."
The right approach: "I need someone who has done [specific thing] before."

Common gaps for technical founders:

Gap Profile What They Do
Fundraising Former founder who raised Seed/Series A Writes deck, runs investor meetings, handles term sheets
Monetization Product/Growth PM from ed-tech Designs pricing, runs experiments, builds B2B pipeline
Partnerships BD person from media/streaming Negotiates content deals, affiliate partnerships
Operations COO-type Runs hiring, finance, legal, day-to-day ops
Marketing Growth marketer Runs paid/organic acquisition, community building

Your job: After 100 users, the gap becomes obvious. If no one converts to signup, you need growth/marketing. If schools email asking for licenses, you need BD/monetization. If investors ask questions you can't answer, you need a fundraising co-founder.

Phase 4 — Co-Founder Search (Targeted, Month 4–6)

Goal: Find 2–3 candidates, work with them on a trial basis.

Where to look:

  • Founder dating events: YC Co-Founder Matching, Indie Hackers meetups, local accelerators.
  • Angel investor intros: Ask any angel you meet for intros to founders they backed who might want a new project.
  • Industry communities: Ed-tech Slack/Discord groups, language-learning subreddits (look for people complaining about Duolingo — they care).
  • LinkedIn outbound: Search "former PM at Duolingo," "former growth at Babbel." Cold DM with the Lila demo, not a resume.

Trial period (4–8 weeks):

  • Work together on a concrete project (e.g., "Design and test a monetization experiment").
  • No equity commitment. Pay as a contractor if needed.
  • Evaluate: Do they deliver? Do you communicate well? Do they care about the mission?

Phase 5 — Formalize (Only After Trial, Month 6+)

Goal: Legal structure, equity split, roles.

Equity mindset:

  • 50/50 is dangerous unless you truly could not build without them from day one. You already built the Lila MVP alone — you have leverage.
  • Suggested: 60/40 or 65/35 with 4-year vesting and a 1-year cliff for both.
  • Vesting is non-negotiable. If they leave in 6 months, they keep nothing.

Roles:

  • You: CTO / Product (own technical vision, architecture, data pipeline).
  • Them: CEO / COO / CMO depending on profile (own business side, fundraising, partnerships).
  • Decision-making: You retain veto on technical/product decisions; they lead business/fundraising.

Legal:

  • Incorporate properly (C-Corp if US, Ltd if UK/EU).
  • IP assignment agreement: everything built so far belongs to the company.
  • Founder agreement: roles, vesting, termination, dispute resolution.

Suggested Execution Order

Month 1 (Now)

  • Week 1–2: Finish Kaikki Stage 3 enrich sub-stage rewrite. Run full sample, validate quality. Start first additional multiplayer mode (Race to the Top recommended).
  • Week 3: Ship guest play. Make auth optional on game routes.
  • Week 4: Start media ingestion prototype (parallel). Pick one media piece, get text extraction working.

Month 2

  • Week 1–2: Complete media ingestion prototype. End-to-end: media → quiz. Complete first additional multiplayer mode.
  • Week 3: Add metrics (PostHog/Plausible). Polish shareable output (social cards).
  • Week 4: Integrate media demo with multiplayer mode. Test combined flow.

Month 3

  • Week 1: Soft launch to 100 strangers. Gather feedback.
  • Week 2–3: Iterate based on feedback. Fix hardening items from BACKLOG.md.
  • Week 4: Analyze metrics. Decision gate: proceed or iterate?

Month 4–6

  • If metrics are positive: start co-founder search (Phase 4).
  • If metrics are weak: iterate on media feature or pivot the value proposition.

Open Questions to Refine This Roadmap

Answer these to make the roadmap more specific:

Product Reality Check

  • What is the exact blocker on Kaikki Stage 3? (Is it the sub-stage rewrite, or something else?)
  • Which media piece should be the first demo? (Breaking Bad, Shakira, or Harry Potter?)
  • Do you have subtitle/lyrics data for the chosen media piece?

Target Audience

  • Who is the ideal first user? (e.g., "German intermediate learner who watches Netflix")
  • What language pair should the media demo target?

Business Model

  • Do you have a monetization hypothesis? (freemium / B2B / affiliate)
  • Any thoughts on unit economics?

Competitive Landscape

  • Who do you see as direct competitors? (LingQ? FluentU? Duolingo? Anki?)
  • What do they do poorly that Lila fixes?

Runway & Constraints

  • Is this full-time or nights-and-weekends?
  • Do you have any funding, savings runway, or revenue?
  • What's your hard deadline for "showable to users"?

Co-Founder Search

  • Local or remote-first?
  • What do you want them to do? (fundraise, partnerships, monetization, operations?)
  • Do you already know candidates, or starting from zero?
  • Equity mindset: 50/50, or majority control for yourself?