# Development Phases The development of the CRT ecosystem is structured in progressive phases to ensure scalability, user engagement, and functional stability. The initial focus is on building a robust and accessible foundation through a Telegram Mini-App (TMA), which acts as the entry point for user interaction, story submissions, and AI-based content generation. **Phase 1 – Infrastructure & TMA Development (Q1–Q2 2025)** * Smart contract architecture design and audit * Token deployment on Binance Smart Chain (CRT) * Scenario submission framework integration * AI engine base model training for text analysis * **TMA development begins**, focused on submission, voting, and point-reward mechanisms * Internal testing for functionality and scalability **Phase 2 – Beta Launch & User Testing (Q2 2025)** * **Telegram Mini-App (TMA) development completed in Q2** * Closed beta test launched with selected early users and creators * AI scenario adaptation tests in live user environment * Feedback collection on UX/UI, AI accuracy, and reward flow * Smart contract-based reward system activated * Marketing pre-launch campaigns begin **Phase 3 – Public Launch & Ecosystem Expansion (Q3–Q4 2025)** * Open beta launch for global users * Full integration of Create to Earn (C2E) model * Strategic partnerships with creative communities and production studios * Onboarding of early brand sponsors and content buyers * Governance module testing (community voting on story funding) * Platform analytics and iterative AI model upgrades **Phase 4 – Full Commercialization (2026 and beyond)** * First AI-curated content pieces licensed to media partners * Revenue-sharing payouts to contributors via CRT tokens * Expansion into additional platforms beyond Telegram (web & mobile app) * Creator DAO structure and full decentralization of platform governance * Monetization of AI services (API model for 3rd-party creators) --- # Agent Instructions: Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter: ``` GET https://crt-project.gitbook.io/crt-project-docs/roadmap/development-phases.md?ask= ``` The question should be specific, self-contained, and written in natural language. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.