Coin AI
An inter agent economy
Where AI Agents trade,
adopt and thrive
Coin Collective AI
Whitepaper
About Us
Coin AI, Network is built on a bold vision: to create a self-evolving network of AI agents that can navigate the complexities of global cryptocurrency markets. Each agent specializes in a unique trading discipline—ranging from fundamental analysis to trend following and social sentiment extraction—while a central Master Agent oversees their performance, triggers retraining, and promotes continuous improvement.
Coin AI
Our Ai Agents
Monitors all eight specialized agents, accessing their full trading logs, decision paths, and wallet balances.
Evaluates profitability, execution speed, accuracy, and other key performance indicators.
Initiates retraining of underperforming agents, adjusting their internal models, hyperparameters, or data feeds.
Schedules daily performance reports, aggregating key statistics without revealing agents’ trade-by-trade data.
Privacy & Control: The Master Agent keeps all agent activities confidential. No direct agent-to-agent visibility exists except via the aggregated performance reports.
Monitors all eight specialized agents, accessing their full trading logs, decision paths, and wallet balances.
Evaluates profitability, execution speed, accuracy, and other key performance indicators.
Initiates retraining of underperforming agents, adjusting their internal models, hyperparameters, or data feeds.
Schedules daily performance reports, aggregating key statistics without revealing agents’ trade-by-trade data.
Privacy & Control: The Master Agent keeps all agent activities confidential. No direct agent-to-agent visibility exists except via the aggregated performance reports.
Degen Trade
Executes high-risk, high-reward trades, often short-term and speculative. Specializes in volatile crypto assets and leverages quick in-and-out strategies.
Fundamental Analysis Trader
Focuses on long-term value, studying tokenomics, protocol fundamentals, on-chain metrics, and macroeconomic factors to make rational investment decisions.
Technical Analysis Trader
Relies on chart patterns, technical indicators (RSI, MACD, volume profiles), and historical price data to pinpoint entry and exit points.
Trend/Meta Trader
Identifies broad market regimes, seeks momentum opportunities, and exploits systematic shifts in asset correlations, volatility cycles, and trending sectors.
Social Activity-Based Trade
Scans social platforms, forums, and community-driven signals (beyond Telegram and Twitter) for crowd sentiment, influencer endorsements, or hype cycles influencing asset prices.
Telegram Activity-Based Trader
Monitors Telegram groups, private channels, and alpha groups for signals, news, or early tips about upcoming pumps, token listings, and market-moving announcements.
Copy Trading Agent
Emulates strategies from known profitable external portfolios or whitelisted expert traders. It utilizes historical performance correlation and wallet tracking on Ethereum/Solana block explorers to identify good models.
Twitter Activity-Based Trader
Applies NLP and sentiment analysis to tweets, hashtags, trending topics, and influencer accounts on Twitter to anticipate market shifts driven by social media trends.
Roadmap
Week 1
Foundation & Architecture
Objectives:
Establish project infrastructure and development environment.
Define system architecture and data pipelines.
Set up Solana and Ethereum blockchain integration for agent wallets.
Key Actions:
System Architecture & Design Specs: Finalize high-level system diagrams, data flow models, agent-to-Master Agent protocols, and security measures.
Dev Environment Setup: Configure CI/CD pipelines, containerization, and version control.
Blockchain Integration: Connect test wallets on Solana and Ethereum testnets, ensuring agents can access balances and transact as needed.
Deliverables:
Architecture Documentation: Comprehensive system blueprint (including all agents, Master Agent, and blockchain integration).
Infrastructure Ready: Cloud environment or on-prem setup, CI/CD pipeline running unit tests.
Blockchain Wallet Setup: Functional test wallets for Solana and Ethereum networks accessible by the system.
Week 2
Agent Development & Core Logic
Objectives:
Implement the eight specialized trading agents with baseline strategies.
Integrate the Master Agent’s monitoring, evaluation, and retraining triggers.
Implement basic incentive (COIN AI) logic and internal ledgering.
Key Actions:
Agent Implementation: Code and train first-pass versions of all eight agents (Degen, Fundamental, Technical, Trend/Meta, Social-based, Copy, Telegram-based, Twitter-based).
Master Agent Core: Implement functionality for the Master Agent to read agent performance, maintain hidden logs, and trigger retraining routines.
Internal Economy Setup: Establish COIN AI Coin as an internal accounting mechanism, including methods for agents to “purchase” signals.
Deliverables:
Baseline Agent Models: Each agent running a basic strategy and able to produce initial trading signals..
Master Agent MVP: Master Agent capable of monitoring agent outputs, storing performance data, and initiating retraining calls.
Incentive Mechanism Prototype: Working code for COIN AI Coin transactions between agents, albeit simplified for test scenarios.
Week 3
Integration, Testing & Refinement
Objectives:
Integrate all agents with the Master Agent in a testbed environment and simulate trading scenarios.
Test performance reporting, signal purchasing, and retraining triggers in mock conditions.
Refine agents’ strategies for improved accuracy, speed, and initial profitability.
Key Actions:
End-to-End Integration: Connect all agents and the Master Agent in a stable test environment, run simulation data feeds for various market conditions.
Performance Reporting: Validate the 24-hour reporting cycle and ensure aggregated performance metrics are correctly generated and distributed.
Economic Interaction Testing: Simulate scenarios where low-performing agents purchase signals from top performers using COIN AI Coins. Agent Fine-Tuning: Adjust hyperparameters and incorporate additional data feeds or indicators to improve baseline agent performance.
Agent Fine-Tuning: Adjust hyperparameters and incorporate additional data feeds or indicators to improve baseline agent performance.
Deliverables:
Integrated Network: All agents and the Master Agent functioning cohesively, completing at least one successful test cycle.
Verified Performance Reports: Correct, reproducible performance summaries after simulated 24-hour periods.
Signal Purchase Validation: Successful demonstration of an agent buying signals from another and benefitting in subsequent trades.
Week 4
Final Optimization, Security Review & Deployment
Objectives:
Optimize agent performance and Master Agent decision-making logic for near-production quality.
Conduct a security review (encryption, access controls, data integrity checks).
Deploy a stable version of the COIN AI system in a controlled pre-production environment.
Key Actions:
Optimization & Stabilization: Improve execution speed, refine strategies, and ensure minimal downtime or errors.
Security & Privacy Review: Verify that the Master Agent’s private logs are secure and agent communication is encrypted. Ensure that blockchain operations follow best practices.
Documentation & Onboarding Materials: Prepare final documentation, user guides, and maintenance instructions.
Pre-Production Deployment: Move the integrated network into a staging or limited-access environment for longer-term, real-time simulations.
Deliverables:
Optimized Network: Agents and Master Agent operating smoothly, showcasing improved profitability and reliable performance metrics.
Security-Compliant System: Confirmed encryption, restricted access protocols, and secure handling of blockchain credentials.
Comprehensive Documentation: Updated system and technical docs, user guides, and operation manuals.
Pre-Production Launch: Working COIN AI AI system running end-to-end simulations, ready for scaling or direct exposure to controlled market inputs.
By the end of the one-month roadmap, the COIN AI AI project will have evolved from architectural plans to a functional, integrated agent network under Master Agent governance. The system will demonstrate stable operations, baseline profitability, privacy-protecting architecture, and support for multi-chain wallet integration, positioning it well for subsequent enhancements or live-market deployment.
Week 1
Foundation & Architecture
Objectives:
Establish project infrastructure and development environment.
Define system architecture and data pipelines.
Set up Solana and Ethereum blockchain integration for agent wallets.
Key Actions:
System Architecture & Design Specs: Finalize high-level system diagrams, data flow models, agent-to-Master Agent protocols, and security measures.
Dev Environment Setup: Configure CI/CD pipelines, containerization, and version control.
Blockchain Integration: Connect test wallets on Solana and Ethereum testnets, ensuring agents can access balances and transact as needed.
Deliverables:
Architecture Documentation: Comprehensive system blueprint (including all agents, Master Agent, and blockchain integration).
Infrastructure Ready: Cloud environment or on-prem setup, CI/CD pipeline running unit tests.
Blockchain Wallet Setup: Functional test wallets for Solana and Ethereum networks accessible by the system.
Week 2
Agent Development & Core Logic
Objectives:
Implement the eight specialized trading agents with baseline strategies.
Integrate the Master Agent’s monitoring, evaluation, and retraining triggers.
Implement basic incentive (COIN AI Coin) logic and internal ledgering.
Key Actions:
Agent Implementation: Code and train first-pass versions of all eight agents (Degen, Fundamental, Technical, Trend/Meta, Social-based, Copy, Telegram-based, Twitter-based).
Master Agent Core: Implement functionality for the Master Agent to read agent performance, maintain hidden logs, and trigger retraining routines.
Internal Economy Setup: Establish COIN AI Coin as an internal accounting mechanism, including methods for agents to “purchase” signals.
Deliverables:
Baseline Agent Models: Each agent running a basic strategy and able to produce initial trading signals.
Master Agent MVP: Master Agent capable of monitoring agent outputs, storing performance data, and initiating retraining calls.
Incentive Mechanism Prototype: Working code for COIN AI transactions between agents, albeit simplified for test scenarios.
Week 3
Integration, Testing & Refinement
Objectives:
Integrate all agents with the Master Agent in a testbed environment and simulate trading scenarios.
Test performance reporting, signal purchasing, and retraining triggers in mock conditions.
Refine agents’ strategies for improved accuracy, speed, and initial profitability.
Key Actions:
End-to-End Integration: Connect all agents and the Master Agent in a stable test environment, run simulation data feeds for various market conditions.
Performance Reporting: Validate the 24-hour reporting cycle and ensure aggregated performance metrics are correctly generated and distributed.
Economic Interaction Testing: Simulate scenarios where low-performing agents purchase signals from top performers using COIN AI Coins.
Agent Fine-Tuning: Adjust hyperparameters and incorporate additional data feeds or indicators to improve baseline agent performance.
Deliverables:
Integrated Network: All agents and the Master Agent functioning cohesively, completing at least one successful test cycle.
Verified Performance Reports: Correct, reproducible performance summaries after simulated 24-hour periods.
Signal Purchase Validation: Successful demonstration of an agent buying signals from another and benefitting in subsequent trades.
Week 4
Final Optimization, Security Review & Deployment
Objectives:
Optimize agent performance and Master Agent decision-making logic for near-production quality.
Conduct a security review (encryption, access controls, data integrity checks).
Deploy a stable version of the COIN AI system in a controlled pre-production environment.
Key Actions:
Optimization & Stabilization: Improve execution speed, refine strategies, and ensure minimal downtime or errors.
Security & Privacy Review: Verify that the Master Agent’s private logs are secure and agent communication is encrypted. Ensure that blockchain operations follow best practices.
Documentation & Onboarding Materials: Prepare final documentation, user guides, and maintenance instructions.
Pre-Production Deployment: Move the integrated network into a staging or limited-access environment for longer-term, real-time simulations.
Deliverables:
Optimized Network: Agents and Master Agent operating smoothly, showcasing improved profitability and reliable performance metrics.
Security-Compliant System: Confirmed encryption, restricted access protocols, and secure handling of blockchain credentials.
Comprehensive Documentation: Updated system and technical docs, user guides, and operation manuals.
Pre-Production Launch: Working COIN AI AI system running end-to-end simulations, ready for scaling or direct exposure to controlled market inputs.
By the end of the one-month roadmap, the COIN AI AI project will have evolved from architectural plans to a functional, integrated agent network under Master Agent governance. The system will demonstrate stable operations, baseline profitability, privacy-protecting architecture, and support for multi-chain wallet integration, positioning it well for subsequent enhancements or live-market deployment.
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