Development Timeline
January 2025 - Phase 1: Technical Architecture Design and Development
Objective: Build foundational technical architecture including blockchain, smart contracts, AI systems, data collection and processing workflows.
- Design airdrop system blockchain architecture, select suitable public chains (e.g., Ethereum, BSC)
- Develop smart contracts for airdrop distribution logic and verification mechanisms
- Build AI system foundation framework for data input/output processing
- Design security mechanisms to ensure data and fund safety
February 2025 - Phase 2: AI Model Training and Optimization
Objective: Develop and train AI models to score participants' airdrop eligibility based on data.
- Collect training data (transaction records, social media performance, etc.)
- Develop AI algorithms for scoring and risk assessment (ML, NLP, image recognition)
- Fine-tune AI models to ensure fair, just, and accurate scoring results
- Test AI model effectiveness and optimize algorithms for improved prediction accuracy
March 2025 - Phase 3: User Interface and Experience Design
Objective: Build user-friendly interface for easy airdrop participation and score checking.
- Design frontend interface for user registration, wallet submission, and rule viewing
- Integrate AI scoring system for personal score visibility after data submission
- Implement feedback mechanisms for score criteria review and optimization suggestions
- Ensure intuitive, smooth interface design for enhanced user experience
April 2025 - Phase 4: Airdrop Activity Testing and Optimization
Objective: Conduct internal testing and limited public beta, collect feedback and optimize processes.
- Internal testing: Small-scale airdrop tests to verify smart contracts and AI model scoring
- User feedback: Real user participation to evaluate scoring accuracy and user experience
- Bug fixes and process optimization for system stability and efficiency
- Adjust airdrop rules, optimize AI models, improve UI based on feedback
May 2025 - Phase 5: AI Automated Airdrop Farming (Full Automation)
Objective: Achieve full automation of airdrop distribution through AI, including user scoring, eligibility verification, and execution.
- Automatic user screening and airdrop execution based on AI scoring and behavior analysis
- AI algorithm optimization to ensure automated processes comply with all airdrop rules
- Implementation of anti-fraud mechanisms for AI system and automation process security
- Enhanced system monitoring and logging for transparency and traceability
Ongoing Considerations
- Compliance & Legal: Ensure adherence to regulations across different jurisdictions
- Risk Control: Implement measures against scoring errors, vulnerabilities, and system abuse