LinguaMate

Your daily English tutor in Telegram.

LinguaMate is a personalized AI English learning agent for Indonesian speakers that teaches through daily interactive lessons, progress tracking, and adaptive review. It starts with a placement assessment, builds a custom learning roadmap, and proactively nudges the user to practice in short sessions that fit real life.

Business Goals

  • Reach 1,000 registered users within 6 months of launch with at least 35% weekly active usage.
  • Achieve a 30-day retention rate of 25% or higher for active learners within the first 3 months after launch.
  • Keep AI and infrastructure cost below $1.50 per active learner per month at MVP scale.
  • Convert at least 15% of onboarding users into users who complete 5 or more lessons in their first week.
  • Maintain a user satisfaction score of 4.3/5 or higher on lesson quality and usefulness.

User Goals

  • Help users build a consistent daily English habit with 15–30 minute sessions.
  • Improve vocabulary retention through spaced repetition and repeated exposure.
  • Increase grammar accuracy through targeted explanations and correction.
  • Boost confidence in real English conversations through guided practice.
  • Show visible progress through assessments, summaries, and streaks.

Non-Goals

  • Not a full general-purpose chatbot for arbitrary topics outside English learning.
  • Not a live human tutoring marketplace in the MVP.
  • Not a pronunciation-scoring product unless supported by verified voice technology.
  • Not a complete web-only learning platform before Telegram MVP proves retention.

Rina, Indonesian office worker, 29 - Rina has basic English exposure from school but freezes when writing messages or speaking at work. She wants small, practical lessons she can finish after work without feeling overwhelmed.

Rina, Indonesian office worker, 29

  • As a busy learner, I want a daily lesson that fits 15 minutes, so that I can stay consistent even on weekdays.
  • As a learner who forgets vocabulary, I want the app to review words I missed before, so that I retain them long term.
  • As a learner with low confidence, I want the tutor to correct me gently and explain mistakes in Indonesian when needed, so that I keep practicing.

Dimas, tech-savvy student, 22 - Dimas uses Telegram often and wants to improve English for gaming, tech content, and future job opportunities. He prefers interactive practice over passive reading.

Dimas, tech-savvy student, 22

  • As a learner, I want conversation practice about topics I care about, so that I can use English in realistic situations.
  • As a learner, I want the tutor to adapt difficulty based on my answers, so that lessons are not too easy or too hard.
  • As a learner, I want weekly summaries of my weak areas, so that I know what to study next.

Ayu, returning learner, 35 - Ayu learned some English years ago but has become inconsistent. She needs reminders, measurable progress, and a system that helps her restart without embarrassment.

Ayu, returning learner, 35

  • As a returning learner, I want a placement assessment before lessons start, so that the system does not assume my level.
  • As a learner, I want to pause and resume reminders, so that the product respects my schedule.
  • As a learner, I want to see my streak, lesson completion, and assessment changes, so that I can measure improvement.

Onboarding and Placement Assessment · High priority

  • The product must assess the learner’s current English level before building a learning plan and must collect preferences needed for personalization.
  • Support a short initial assessment with vocabulary, grammar, reading, and short response prompts.
  • Capture preferred study time, daily duration, time zone, and main learning goals.
  • Classify users into an internal level band such as Beginner, Lower Intermediate, Intermediate, or Upper Intermediate.
  • Allow users to skip optional profile questions while still completing onboarding.
  • Store baseline assessment results for future comparison.

Personalized Daily Learning Engine · High priority

  • The system must proactively generate a daily lesson plan tailored to the learner’s ability, history, and available time.
  • Generate a daily plan with recommended activities, estimated duration, and learning objective.
  • Adapt activity mix based on recent performance, time available, and recurring mistakes.
  • Send reminders at the user’s preferred time in their local time zone.
  • Allow the user to request the lesson manually, pause notifications, or reschedule reminders.
  • Keep lessons short and interactive rather than long informational dumps.

Vocabulary and Spaced Repetition · High priority

  • The app must teach practical vocabulary and review it using a spaced repetition schedule that adapts to recall performance.
  • Introduce a default of 5 to 10 new words per day, adjustable by learner performance and duration.
  • Store each word’s definition, translation, example sentence, collocations, and review history.
  • Schedule reviews based on correctness, difficulty, and time since last seen.
  • Distinguish between partially remembered, incorrect, and mastered items.
  • Surface forgotten words more frequently until confidence improves.

Grammar and Conversation Practice · High priority

  • The tutor must teach grammar progressively and apply it in conversation so the learner practices usage, not memorization.
  • Generate grammar lessons with explanation, examples, and exercises.
  • Correct user answers with explanation of why the error happened and how to fix it.
  • Support conversation modes such as casual chat, roleplay, grammar-focused practice, and job interview practice.
  • Avoid correcting every minor issue; prioritize errors that affect clarity or learning value.
  • Summarize recurring mistakes after each practice session.

Progress Tracking and Assessment · Medium priority

  • The product must show measurable progress over time with summaries and periodic assessments rather than motivational noise alone.
  • Track streaks, lesson completion, vocabulary retention, grammar accuracy, and conversation frequency.
  • Generate weekly summaries with strengths, weak areas, and next recommended focus.
  • Run periodic reassessments to compare against baseline performance.
  • Separate activity completion from demonstrated proficiency.
  • Expose a learner-facing progress history with simple metrics and trend indicators.

First-Time User Experience

  • User opens Telegram bot and taps Start.
  • Bot explains the product in one short message and asks permission to begin assessment.
  • User completes a 5 to 8 minute placement assessment with short typed responses and multiple-choice items.
  • Bot asks for preferred study time, daily duration, and time zone.
  • Bot generates a personalized roadmap and sends the first lesson immediately.
  • Time to value target: first useful lesson delivered within 10 minutes of starting onboarding.

1. Daily Check-In

  • Each day the bot proactively sends a lesson notification at the user’s preferred time with a short plan and estimated duration.
  • Include a concise reason for today’s focus, such as weak past tense usage or forgotten vocabulary.
  • If the user misses the reminder, allow a catch-up message later without punishing streaks too aggressively.
  • If the user is paused, suppress reminders and preserve scheduling state.

2. Interactive Lesson Delivery

  • The learner receives one to three small exercises rather than a large lecture.
  • Mix vocabulary, grammar, reading, or conversation based on the plan.
  • Validate typed answers, tolerate minor spelling issues where appropriate, and distinguish acceptable alternatives.
  • If the user is inactive for too long, offer a simpler or shorter next step.

3. Adaptive Correction

  • The bot reviews answers and responds with targeted feedback in English, with Indonesian support when helpful.
  • Explain whether an answer is wrong, unnatural, or acceptable but less natural.
  • Show the corrected sentence and one or two quick examples.
  • Record the mistake type to influence future review schedules.

4. Review and Spaced Repetition

  • Previously learned words and mistakes reappear in later lessons and review sessions.
  • Re-test words at increasing intervals based on performance.
  • Bring back forgotten items before introducing too many new ones.
  • Cap review load so it does not crowd out new learning beyond the available time.

5. Weekly Progress Review

  • At the end of each week the bot sends a summary of progress and recommended focus areas.
  • Show changes in retention, accuracy, and consistency versus the previous week.
  • Highlight repeated mistakes and suggest next-week priorities.
  • Offer a quick reassessment when enough data has accumulated.

Advanced and Power-User Features

  • Voice message support for transcription-based practice when Telegram and AI services support it.
  • Lesson controls for speed, difficulty, and topic preferences.
  • Topic packs for work, travel, shopping, technology, and gaming.
  • Manual review mode for words or grammar points the user wants to revisit.
  • Optional web dashboard for deeper progress views and account settings.
  • Future WhatsApp support using the same learning engine and user profile.

Interface and Experience Principles

  • Keep every lesson message short, segmented, and easy to respond to in chat.
  • Use clear buttons and quick replies for common actions like Practice Now, Review Words, Pause Reminders, and Change Time.
  • Prioritize readability on mobile, with small chunks of text and minimal scrolling.
  • Support bilingual explanations selectively so users are not blocked by English-only content.
  • Ensure fast response times and graceful fallback messages when AI or scheduling services are delayed.

Rina opens LinguaMate on Telegram after work. The bot asks a few placement questions, learns that she struggles most with past tense and practical vocabulary, then creates a daily plan that fits 20 minutes before dinner.

The next day, LinguaMate sends a short lesson on useful work vocabulary and a simple sentence-building exercise. When Rina makes a tense mistake, the bot explains it in plain English and Indonesian, stores the error, and brings it back later in review instead of assuming she has mastered it.

After two weeks, Rina can see her streak, weekly accuracy, and recurring mistakes. She is still studying in short sessions, but now the product is helping her build consistency and measurable improvement, which increases retention and makes the learner likely to stay engaged long term.

User-Centric Metrics

  • At least 60% of active users complete 3 or more lessons per week.
  • At least 40% of active users maintain a 7-day streak within the first month.
  • Vocabulary review accuracy reaches 70% or higher after repeated review cycles for active users.
  • Grammar exercise accuracy improves by at least 15 percentage points after 30 days for users who complete weekly lessons.
  • At least 50% of users report that lessons feel relevant and not overwhelming in in-product surveys.

Business Metrics

  • 30-day retention reaches 25% or higher within 3 months of launch.
  • At least 15% of onboarding users complete 5 or more lessons in the first week.
  • Monthly active learners grow by 20% month over month for the first two growth cycles.
  • Average AI cost stays under $1.50 per active learner per month at MVP scale.
  • Organic referrals or invites account for at least 10% of new signups by month 6.

Technical Metrics

  • Bot message delivery success rate above 99% excluding upstream platform outages.
  • Median lesson generation latency under 5 seconds and 95th percentile under 12 seconds.
  • Scheduled reminder jobs execute within a 2-minute window of the target time for 95% of users.
  • No critical security incidents and all sensitive data encrypted at rest and in transit.

Tracking Plan

  • Track onboarding_started and onboarding_completed with preferred time zone and target duration.
  • Track placement_assessment_completed with baseline level and skill breakdown.
  • Track lesson_generated with lesson type, estimated duration, and selected difficulty.
  • Track exercise_answer_submitted with answer correctness, error category, and response time.
  • Track vocab_item_reviewed with spaced repetition interval and recall outcome.
  • Track reminder_sent, reminder_opened, and reminder_snoozed for notification effectiveness.
  • Track weekly_summary_viewed and reassessment_completed for progress measurement.

Technical Needs

  • Telegram Bot API integration with webhook support.
  • Next.js backend in TypeScript for orchestration and optional web dashboard.
  • Supabase PostgreSQL for user profiles, lesson state, vocabulary, and analytics tables.
  • Background job scheduler such as BullMQ with Redis, or a managed cron/task queue.
  • Structured AI generation with schema validation for lesson plans, corrections, and summaries.
  • Object storage for any future audio or transcript artifacts.
  • Centralized logging and alerting for bot failures, AI errors, and job retries.

Integration Points

  • Telegram Bot API for messaging and interactive buttons.
  • Claude API as the primary model for tutoring and structured response generation.
  • Supabase Auth or custom bot-linked identity for user profiles.
  • Supabase Postgres for persistent storage and row-level security.
  • Optional future WhatsApp Business Cloud API using the same message orchestration layer.

Data Storage & Privacy

  • Store only necessary personal data such as Telegram user ID, learning preferences, and progress records.
  • Encrypt data in transit with TLS and protect secrets in a vault or environment secret manager.
  • Apply row-level security and access controls so each user can only access their own learning data.
  • Provide data export and deletion flows to support GDPR and CCPA-style requests.
  • Avoid storing raw voice or chat transcripts longer than necessary unless explicitly needed for learning history and with user consent.

Scalability & Performance

  • Use asynchronous job processing for lesson generation and reminder delivery.
  • Cache frequently accessed learner profiles and recent review schedules to reduce database load.
  • Design the tutoring engine to be platform-agnostic so WhatsApp can reuse the same core services.
  • Implement rate limiting and retry handling for AI and messaging API failures.

Potential Challenges

  • AI output may become inconsistent or too verbose; mitigate with strict prompt templates and schema validation.
  • Reminder timing can fail across time zones; mitigate with stored timezone fields and UTC-based scheduling logic.
  • Vocabulary review can become too heavy and discourage users; mitigate by capping review volume and adapting difficulty.
  • Voice or pronunciation features may not be reliable; mitigate by clearly labeling them as transcription or practice support rather than scoring.
  • Operating costs may rise with frequent AI calls; mitigate with lesson caching, shorter prompts, and selective use of expensive model invocations.

Team & resourcing - Small team - 2 engineers, 1 product designer, part-time PM, and optional QA support.

Phase 1: Telegram MVP Foundation · Weeks 1-4

  • Telegram bot onboarding and /start flow
  • Placement assessment and profile creation
  • Basic lesson generation from Claude API
  • Supabase schema for users, progress, vocabulary, and reminders
  • Manual lesson request and basic admin logging

Phase 2: Personalized Learning Engine · Weeks 5-8

  • Daily proactive reminders with timezone-aware scheduling
  • Vocabulary lessons with spaced repetition reviews
  • Grammar exercises with correction and mistake logging
  • Conversation practice modes with adaptive follow-up questions
  • Weekly summary messages and baseline progress dashboard

Phase 3: Reliability and Insight · Weeks 9-12

  • Better lesson orchestration and retry handling
  • Analytics events and cost monitoring
  • Assessment comparisons over time
  • Pause/resume reminder controls and schedule updates
  • Improved schema validation and guardrails for AI responses

Phase 4: Expansion Readiness · Weeks 13-16

  • Abstraction layer for WhatsApp support
  • Optional voice message transcription workflow
  • Web dashboard for settings and progress
  • Experiment framework for lesson variants and retention tests
  • Hardening for multi-user scale and operational monitoring

Paste this into Cursor, Bolt, Lovable, or v0 to start building.

Build a personalized AI English learning agent called LinguaMate.

Product summary:
A Telegram-first English tutor for Indonesian speakers that proactively sends daily 15 to 30 minute lessons, starts with a placement assessment, adapts to the learner’s level, tracks vocabulary and grammar progress, and uses spaced repetition plus conversational practice to build long-term consistency. Future expansion should support WhatsApp, voice messages, and a web dashboard, but MVP must be Telegram only.

Core MVP features:
Telegram bot onboarding with /start, placement assessment, preferred study time, timezone, and daily duration
Personalized daily lesson generation using Claude API
Vocabulary lessons with Indonesian translation, part of speech, pronunciation guide, example sentences, and exercises
Grammar lessons with explanation, examples, mistakes, and correction feedback
Conversation practice modes with adaptive follow-up questions
Basic spaced repetition for vocabulary review and recurring mistake review
Progress tracking for streaks, lesson completion, vocab reviewed, accuracy, and weekly summaries
Proactive reminder scheduler with pause/resume/change time controls
Admin-friendly logging and basic usage analytics

Suggested architecture:
Next.js and TypeScript backend
Telegram Bot API webhook integration
Claude API for tutoring and structured outputs
Supabase Postgres for persistent storage
Redis plus BullMQ or a similar job queue for scheduled reminders and lesson jobs
Schema validation for all AI outputs
Row-level security and secure secret management

Primary screens/flows:
Telegram start and onboarding flow
Placement assessment flow
Daily lesson flow with quick reply buttons
Review flow for spaced repetition
Conversation practice flow
Weekly progress summary flow
Settings flow for reminder time, duration, pause/resume, and timezone

Data model:
User profile with Telegram ID, timezone, preferred time, daily duration, target level, interests, and status
Assessment results with skill breakdown and baseline level
Lesson sessions with date, type, generated content, completion status, and AI metadata
Vocabulary items with translation, examples, due dates, confidence, and review history
Grammar mistakes with error category, corrected form, and recurrence count
Progress events and weekly summary records
Reminder schedule records and delivery logs

Implementation requirements:
Use structured JSON outputs from the AI and validate them before sending to users
Keep messages concise, mobile-friendly, and interactive
Support bilingual English plus Indonesian explanations where helpful
Make the learning engine platform-agnostic so WhatsApp can be added later without rewriting core logic
Include basic error handling for AI failures, reminder failures, missing profile data, and invalid user replies

Build the MVP so it is production-minded, maintainable, and ready for iterative expansion.

Business Idea

I want to build a personalized AI English Learning Agent that operates through Telegram initially, with WhatsApp support as a future expansion. The main purpose of this product is to help me, an Indonesian speaker who wants to improve my English gradually, consistently, and practically through daily interactive learning. This should not be a basic chatbot that only responds when asked questions. It should function as a proactive personal English tutor that guides me every day, assigns learning tasks, tracks my progress, remembers my weaknesses, and adapts the learning experience to my actual ability. PRODUCT VISION Build an AI-powered personal English tutor that acts like a patient, supportive, and intelligent English teacher. The agent should help me develop: - Vocabulary - Grammar - Reading comprehension - Listening comprehension - Writing - Speaking - Conversation skills - Sentence construction - Confidence in using English - Long-term learning consistency I want to improve my English from my current level toward intermediate and eventually advanced proficiency. The learning experience must be gradual, practical, interactive, and personalized rather than overwhelming or based on memorizing vocabulary without context. TARGET USER The initial target user is me, an Indonesian speaker who may struggle with English vocabulary, grammar, sentence construction, comprehension, and speaking confidence. The system should begin with an English placement assessment to estimate my current ability. It should identify my strengths and weaknesses and use the results to create a personalized learning roadmap. The agent must not assume that I am a complete beginner or an advanced English speaker without assessing me first. DAILY LEARNING EXPERIENCE Every day, the AI agent should proactively send me a personalized English learning plan through Telegram. I want the agent to tell me: - What I need to learn today. - Why I need to learn it. - What exercises I should complete. - How much time I should spend learning. - What mistakes I need to review. - What progress I have made. The default daily learning duration should be approximately 15–30 minutes, but I should be able to customize it. The AI should send daily reminders at my preferred time, respect my time zone, and allow me to pause or change my learning schedule. Each daily lesson should be interactive instead of sending a large block of information without requiring participation. Potential daily activities include: - New vocabulary. - Grammar lessons. - Sentence-building exercises. - Reading practice. - Listening practice. - Conversation practice. - Review of previously learned material. - A short daily assessment. The AI should adapt the number and difficulty of activities to my learning ability and available time. VOCABULARY LEARNING Every day, the agent should teach me useful English vocabulary with practical examples. The system should introduce approximately 5–10 new words per day by default, with the ability to adjust this based on my performance and retention. Each vocabulary lesson should include: - English word. - Indonesian translation. - Part of speech. - Pronunciation guide. - Example sentences. - Indonesian translation of example sentences. - Common expressions and collocations where relevant. - Similar or related words when useful. - Interactive exercises. For example: Word: Improve Meaning: Meningkatkan / memperbaiki Part of speech: Verb Example: I want to improve my English every day. Translation: Saya ingin meningkatkan bahasa Inggris saya setiap hari. Practice: Ask me to create my own sentence using the word. The agent should prioritize vocabulary that is useful in real-life conversations, work, technology, gaming, shopping, travel, and other practical situations. It should also explain differences between similar words, formal and informal expressions, and common mistakes. VOCABULARY RETENTION AND SPACED REPETITION The agent must remember vocabulary that I have learned and review it regularly. Implement a spaced repetition system that adapts to my performance. The system should track: - Words I have learned. - Words I frequently forget. - Correct and incorrect answers. - Review history. - Vocabulary confidence. - Words that require additional practice. Previously learned vocabulary should appear in future exercises and conversations. The agent should not consider a word mastered merely because I answered it correctly once. GRAMMAR LEARNING The agent should teach English grammar progressively, starting with the fundamentals and increasing difficulty based on my demonstrated understanding. Potential topics include: - Basic sentence structure. - Subject and object. - Verb "to be". - Simple Present. - Present Continuous. - Simple Past. - Future forms. - Questions and negatives. - Articles. - Prepositions. - Modal verbs. - Present Perfect. - Conditional sentences. - More advanced sentence structures. Every grammar lesson should contain: 1. A simple explanation. 2. Practical examples. 3. Indonesian explanations when necessary. 4. Common mistakes. 5. Interactive exercises. 6. Sentence creation. 7. Personalized feedback. When I make a mistake, the AI should explain what is wrong, why it is wrong, and how to correct it. It should distinguish between: - Grammatically incorrect sentences. - Grammatically correct but unnatural sentences. - Informal and formal expressions. - Acceptable variations in English. The teaching style should be patient and encouraging. CONVERSATION PRACTICE The AI should help me practice English through interactive conversations. It should ask questions, wait for my responses, and continue the conversation naturally. Conversation difficulty must adapt to my current ability. Potential conversation topics include: - Daily routines. - Hobbies. - Gaming. - Technology. - Work. - Shopping. - Travel. - Social situations. - Opinions. - Storytelling. - Real-world roleplay. Include different practice modes: - Casual English conversation. - Beginner conversation practice. - Grammar-focused conversation. - Vocabulary-focused conversation. - Roleplay scenarios. - Speaking confidence practice. - Job interview practice. The AI should encourage me to respond in English. It should correct important mistakes without interrupting every sentence unnecessarily. After a conversation, it should provide a brief summary of my performance, recurring mistakes, and recommended practice areas. LISTENING AND SPEAKING If Telegram voice messages and the selected AI services support these capabilities, allow me to send voice messages and receive voice-based English learning exercises. Potential features: - Speech transcription. - Conversation through voice messages. - Listening comprehension exercises. - Audio-based vocabulary practice. - Feedback on understandable pronunciation patterns, where supported by the available technology. The system must clearly distinguish between speech transcription and reliable pronunciation assessment. It should not claim to provide accurate pronunciation scoring if the technology cannot support it. PROGRESS TRACKING The agent should maintain a persistent learning profile and track my progress over time. Track: - Learning days. - Learning streak. - Completed lessons. - Vocabulary introduced. - Vocabulary reviewed. - Vocabulary retention. - Grammar exercise accuracy. - Reading performance. - Listening performance when supported. - Conversation practice frequency. - Repeated mistakes. - Areas that need improvement. The agent should provide weekly progress summaries and explain what I should focus on next. I want to see measurable improvement rather than simply receiving motivational messages. The system should use periodic assessments to evaluate changes in my English skills. It must distinguish between learning activity, exercise performance, and demonstrated proficiency. PERSONALIZED LEARNING The agent should personalize lessons based on: - My current English level. - My learning goals. - My available daily study time. - My interests. - My previous mistakes. - My performance. - My learning consistency. The AI should remember my learning context across sessions. For example, if I repeatedly make mistakes with Simple Past, the agent should provide additional explanations and exercises instead of continuously introducing unrelated topics. The learning plan should evolve as I improve. PROACTIVE DAILY NOTIFICATIONS The Telegram agent should proactively send daily learning notifications at my preferred time. I should be able to: - Set my preferred learning time. - Change the daily study duration. - Pause reminders. - Resume reminders. - View today's lesson. - Review previous lessons. - Request additional practice. The system should avoid sending excessive or unwanted notifications and should respect my notification preferences. TECHNOLOGY PREFERENCES I prefer the following technology stack for the product: - Telegram Bot API as the initial messaging platform. - WhatsApp Business Cloud API as a future integration. - Claude API as the primary AI model. - Next.js and TypeScript for the backend and optional web dashboard. - Supabase PostgreSQL for persistent user data, learning progress, vocabulary, and review schedules. - A reliable background job and scheduling system for daily reminders. - Structured AI outputs and schema validation where practical. The architecture should separate the learning engine from the messaging platform so WhatsApp can be added later without rewriting the core application. TECHNICAL EXPECTATIONS Design the product as a reliable, maintainable, and cost-conscious AI learning application. The system should support: - Persistent user profiles. - Conversation context. - Learning progress storage. - Vocabulary review scheduling. - Daily lesson generation. - Error handling. - Scheduled notifications. - AI usage and cost monitoring. - Secure storage of user data. Do not assume that all integrations are already configured. Identify required external services, API credentials, platform limitations, and implementation dependencies. MVP PRIORITIES Prioritize a functional Telegram MVP before advanced features. The initial MVP should focus on: 1. Telegram bot integration. 2. User onboarding. 3. English level assessment. 4. Personalized daily learning plans. 5. Vocabulary lessons. 6. Grammar exercises. 7. Interactive conversation. 8. Basic spaced repetition. 9. Progress tracking. 10. Scheduled reminders. Future features may include: - WhatsApp integration. - Voice-based learning. - Pronunciation feedback. - Web dashboard. - Gamification. - Advanced analytics. - More sophisticated adaptive learning. SUCCESS CRITERIA The product should help me build a consistent daily English learning habit and demonstrate measurable improvement in my language skills. Focus on: - Daily and weekly learning consistency. - Lesson completion. - Vocabulary retention. - Grammar accuracy. - Conversation practice. - Improvement in periodic assessments. - User satisfaction. - AI response quality. - Operating cost per active learner. Avoid vague claims such as "become fluent quickly." Define measurable learning outcomes and realistic assessment methods. PRD REQUIREMENTS Generate a comprehensive, practical, and implementation-ready PRD for this product. Include: - Product overview. - Problem statement. - Target user. - Product goals. - MVP scope. - User stories. - Functional requirements. - User journeys. - Telegram interaction flows. - AI agent architecture. - Database requirements. - Technical architecture. - Scheduling requirements. - Edge cases. - Security considerations. - Success metrics. - Development milestones. - Future expansion opportunities. Identify important assumptions and unresolved decisions. Prioritize a realistic MVP that can be developed and tested before expanding into a complex AI tutoring platform. The final PRD should be specific enough for an AI coding agent or developer to use as a foundation for implementation.

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