Automated Trading Workflows
Explore the sophisticated multi-agent workflows that power discovery, analysis, and execution automatically.
Agentical's power lies not in a single AI agent, but in a sophisticated ecosystem of specialized agents working together through carefully orchestrated workflows. Understanding these workflows reveals how the platform transforms raw market data into profitable trading decisions while maintaining strict risk controls.
Understanding the Workflow Architecture
What is a Trading Workflow?
A trading workflow is a structured sequence of automated processes where specialized AI agents collaborate to accomplish complex trading objectives. Think of it as an assembly line where each station performs a specific task, and the output from one feeds seamlessly into the next.
In traditional trading, a human trader must manually handle every step: scan markets, research tokens, evaluate risks, time entries, execute orders, monitor positions, and decide exits. This sequential process is exhausting and prone to human error, emotional bias, and physical limitations.
Agentical's workflow architecture distributes these responsibilities across multiple specialized agents that operate simultaneously. While one agent scans for new opportunities, another monitors your open positions, a third analyzes a promising token's social metrics, and a fourth prepares an exit order for a position approaching its profit target.
Traditional vs. Workflow Trading:
The Multi-Agent System
Agentical employs different types of specialized agents, each designed to excel at specific tasks within the trading workflow.
Agent Categories:
Discovery Agents continuously monitor the Solana blockchain and pump.fun platform for new token launches, migration events, and significant market movements. These agents maintain constant connections to data streams, ensuring no opportunity is missed regardless of when it occurs.
Analysis Agents perform deep evaluations of potential trading candidates. Each analysis agent specializes in a particular domain—one examines social media presence, another studies on-chain holder distribution, a third analyzes price charts and technical patterns. This specialization allows for expert-level evaluation across multiple dimensions simultaneously.
Risk Assessment Agents serve as the workflow's gatekeepers. They aggregate data from all analysis agents, calculate comprehensive risk scores, and maintain veto power over trades that exceed acceptable risk thresholds. No trade executes without passing risk validation, regardless of potential profit.
Execution Agents handle the precise timing and technical implementation of trade orders. They optimize transaction parameters for speed and cost-efficiency, manage slippage tolerances, and ensure reliable order submission even during network congestion.
Monitoring Agents track open positions continuously, watching for exit triggers, changing market conditions, or emerging risks. They update profit/loss calculations in real-time and prepare exit orders when criteria are met.
Portfolio Management Agents maintain the big picture, ensuring overall position sizing remains appropriate, budget limits are respected, and capital allocation follows your strategic guidelines.
Core Workflow Processes
The Primary Trading Workflow
The primary workflow guides tokens from initial discovery through trade execution and eventual exit. This is the main process your agent executes continuously.
Complete Workflow Visualization:
This workflow executes continuously, with multiple tokens potentially at different stages simultaneously. While monitoring one position approaching its profit target, the workflow might simultaneously be analyzing three new tokens and waiting for optimal entry on a fourth.
Workflow Stages in Detail
Stage 1: Discovery & Initial Filtering
Discovery agents maintain persistent connections to pump.fun's infrastructure, receiving real-time notifications of every token launch and significant event.
Discovery Agent Operations:
The scanning process operates on millisecond timescales. The moment a token launches or migrates to DEX, discovery agents capture the event and perform immediate basic validation.
Tokens failing these basic checks are discarded immediately, allowing the workflow to focus computational resources on legitimate opportunities. The 60% rejection rate at this stage demonstrates how much noise exists in the market—most launches are low-quality or outright scams.
Stage 2: Parallel Multi-Factor Analysis
Tokens passing initial filtering enter comprehensive analysis where multiple specialized agents work simultaneously.
Analysis Agent Coordination:
Each analysis agent operates independently but within coordinated timeframes. The orchestration layer ensures all agents complete their work before the workflow proceeds, while preventing any single slow agent from bottlenecking the entire process.
Social Media Agent Deep Dive:
This agent doesn't just count followers—it evaluates account authenticity and community quality. A token with 50,000 Twitter followers might seem impressive until the agent discovers 80% are bot accounts created within the past week, engagement rates are 0.01%, and the account itself was established three days ago.
Analysis Metrics:
Account creation date vs. token launch date
Follower growth pattern (gradual vs. sudden spike)
Engagement rate (likes/comments per follower)
Account verification status
Post frequency and consistency
Community response quality
Holder Distribution Agent Deep Dive:
This agent maps the entire holder landscape, identifying concentration risks and suspicious patterns.
Holder Analysis Example:
Connected wallet detection reveals when multiple addresses are controlled by the same entity—a common manipulation tactic where developers spread tokens across "different" wallets to appear decentralized while maintaining control.
Stage 3: Risk Assessment & Decision Making
After all analysis agents complete their evaluations, data flows into the risk assessment engine.
Risk Scoring Algorithm:
The risk assessment process combines quantitative metrics with pattern recognition, weighing different factors based on their historical correlation with successful trades.
A token must achieve both a minimum risk score AND match all specified criteria in your strategy configuration. Even a 95/100 risk score won't trigger a trade if the token doesn't meet your holder count requirement, for example.
Criteria Matching Process:
This example demonstrates the workflow's discipline—even though the token scored well and passed 7 of 8 criteria, the single failure prevents execution. This strict adherence protects capital by maintaining consistent standards.
Stage 4: Entry Point Optimization
When a token passes all criteria, the workflow doesn't immediately execute—it waits for optimal entry conditions.
Entry Timing Strategies:
The execution planning agent employs multiple timing strategies based on token lifecycle stage and current price action.
Strategy 1 - Pullback Entry:
Rather than buying at the peak of a rally, the agent waits for a healthy pullback or consolidation. This patience often results in 10-15% better entry prices.
Strategy 2 - Breakout Entry:
For tokens consolidating in a tight range, the agent waits for a breakout above resistance with volume confirmation before entering.
Position Sizing Logic:
Position size adjusts dynamically based on multiple factors:
This dynamic sizing ensures larger positions in higher-quality opportunities while maintaining appropriate diversification and risk management.
Stage 5: Trade Execution
When optimal entry conditions align, the execution agent prepares and submits the trade order with precision.
Execution Process Flow:
The multi-node submission strategy ensures reliable execution even if one RPC node experiences issues. Priority fees are calibrated to ensure timely block inclusion without overpaying—typically 0.0001-0.0005 SOL per transaction.
Slippage Management:
Slippage tolerance adjusts based on liquidity conditions:
High liquidity (>100 SOL): 1-2% slippage tolerance
Medium liquidity (50-100 SOL): 2-3% slippage tolerance
Lower liquidity (20-50 SOL): 3-5% slippage tolerance
If actual slippage exceeds tolerance, the transaction fails and the agent retries with adjusted parameters or abandons if conditions have deteriorated.
Stage 6: Position Monitoring
The moment a trade confirms, monitoring agents activate to track the position continuously.
Monitoring Agent Responsibilities:
This multi-layered monitoring ensures positions are protected while allowing profits to develop. The workflow doesn't simply wait passively for profit targets—it actively watches for problems that might warrant early exit.
Dynamic Exit Adjustments:
Monitoring agents can adjust exit parameters based on evolving conditions:
This dynamic management protects capital while allowing winners to run, balancing risk management with profit maximization.
Stage 7: Trade Closure & Learning
Exit execution mirrors entry execution—fast, reliable, and optimized.
Exit Process:
Once an exit trigger activates, the execution agent prepares a sell order using the same efficient process as entry, typically completing within 2-3 seconds.
Post-Trade Analysis:
Every closed trade generates valuable learning data that feeds back into the workflow's continuous improvement system.
This data feeds into the workflow's refinement algorithms, gradually improving decision quality over time.
Specialized Workflow Variations
Conservative Workflow
The conservative workflow emphasizes capital preservation and consistent returns over aggressive profit seeking.
Conservative Workflow Characteristics:
This workflow sacrifices potential for higher returns in exchange for improved win rate and reduced downside risk.
Aggressive Workflow
The aggressive workflow targets high-growth opportunities with larger position sizes and higher risk tolerance.
Aggressive Workflow Characteristics:
Higher risk tolerance allows capturing explosive early-stage growth but exposes capital to greater potential losses.
Custom Workflow Building
Advanced users can construct custom workflows by defining specific criteria combinations and exit strategies.
Custom Workflow Example:
The platform's AI validates custom workflows for logical consistency and feasibility before allowing activation.
Workflow Orchestration & Coordination
The Orchestration Layer
Behind the scenes, an orchestration layer coordinates all workflow activities, ensuring smooth operation even with dozens of concurrent processes.
Orchestrator Responsibilities:
The orchestration layer functions as the workflow's central nervous system. It receives signals from all agents, prioritizes tasks, allocates resources, and ensures critical processes never get blocked by less urgent activities.
Task Priority Hierarchy:
This prioritization ensures critical operations like position protection always execute immediately, while background tasks run when computational resources are available.
Resource Allocation
The orchestrator intelligently manages computational resources based on current workload and priorities.
Dynamic Resource Management:
This adaptive resource allocation ensures the workflow remains responsive and reliable regardless of current activity levels.
Workflow Performance & Optimization
Continuous Improvement Mechanisms
Agentical's workflows don't remain static—they evolve based on performance data and market changes.
Learning Feedback Loop:
This continuous learning happens automatically in the background, gradually refining workflow effectiveness without requiring manual intervention.
Performance Metrics Tracking:
The workflow tracks numerous performance indicators to guide optimization:
Win rate per criteria configuration
Average profit per winning trade
Average loss per losing trade
Risk-adjusted returns (Sharpe ratio)
Entry point timing accuracy
Exit point timing efficiency
Hold duration optimization
Criteria combination effectiveness
Understanding Workflow Transparency
Activity Logging
Every workflow action is logged with complete details, providing unprecedented transparency into agent decision-making.
Comprehensive Activity Logs:
These detailed logs allow you to understand exactly why trades were executed, why opportunities were rejected, and how positions were managed.
Workflow Visualization
The dashboard provides real-time visualization of workflow states and agent activities.
Live Workflow Dashboard:
This real-time view helps you understand what your agent is doing at any moment, building confidence in the automated system.
Workflow Integration with User Control
Manual Override Capabilities
While workflows operate automatically, you maintain override authority at every stage.
Intervention Points:
Users can intervene in the workflow at multiple stages, redirecting or halting processes as needed.
Available Overrides:
Discovery Stage - Add specific tokens to priority analysis queue, manually excluding certain tokens or projects from consideration.
Analysis Stage - Request detailed analysis reports for specific tokens, override risk scores with manual assessment if desired.
Execution Stage - Approve or reject pending entries before execution, modify position sizes for upcoming trades, cancel prepared orders before submission.
Monitoring Stage - Manually close any open position immediately, adjust profit targets or stop-losses on active positions, pause monitoring to review situations manually.
System Level - Pause entire workflow while maintaining open positions, stop all activity and close all positions, adjust strategy parameters mid-operation, switch between different workflow templates.
Workflow Customization Interface
The platform provides intuitive interfaces for customizing workflow behavior without technical knowledge.
Customization Options:
These high-level controls adjust multiple underlying parameters simultaneously, simplifying workflow customization while maintaining logical consistency.
Advanced Workflow Features
Multi-Strategy Parallel Workflows
Users with sufficient AGNT holdings can run multiple independent workflows simultaneously, each with different strategies.
Parallel Workflow Architecture:
Each workflow operates independently with its own budget, criteria, and position management, allowing sophisticated portfolio diversification strategies.
Conditional Workflow Logic
Advanced users can implement conditional logic where workflow behavior adapts to changing market conditions.
Conditional Logic Example:
These conditional rules allow workflows to automatically adjust to market volatility, improving adaptability without constant manual intervention.
Emergency Workflow Protocols
Built-in emergency protocols activate automatically when certain conditions are detected.
Emergency Response System:
These safety protocols protect capital during exceptional market disruptions without requiring immediate user intervention.
Workflow Best Practices
Optimizing Workflow Performance
To maximize workflow effectiveness, consider these optimization strategies.
Performance Optimization Tips:
Strategy Alignment - Ensure your chosen workflow matches your actual risk tolerance and time horizon. Aggressive workflows demand more active monitoring and higher risk acceptance.
Budget Appropriateness - Size your per-trade and daily limits to allow sufficient diversification. If your daily limit only permits one or two trades, consider increasing it or reducing per-trade size.
Criteria Calibration - Start with conservative criteria, then gradually relax specific requirements based on performance data. It's easier to loosen restrictions than tighten them after losses.
Regular Review - Check workflow performance weekly, examining which criteria consistently contribute to winning trades and which frequently reject profitable opportunities.
Market Condition Awareness - Understand that workflow performance varies with overall market conditions. Bull markets produce different results than ranging or bear markets.
Common Workflow Mistakes
Avoiding common configuration errors improves workflow reliability and performance.
Frequent Configuration Errors:
Over-Optimization - Setting criteria so strict that no tokens qualify, resulting in zero trades despite active markets. If your workflow rejects 100+ consecutive tokens, criteria are likely too restrictive.
Conflicting Requirements - Requesting both "ultra-early entries" and "established projects with 5,000+ holders" creates logical impossibility. The workflow will struggle to find matches.
Insufficient Budget - Setting daily limits too low relative to per-trade sizes, preventing adequate position diversification.
Ignoring Learning Data - Not reviewing performance reports and trade logs means missing valuable insights that could improve configuration.
Emotional Overrides - Frequently manually closing positions before targets, undermining the workflow's systematic approach and preventing strategy validation.
The Power of Systematic Workflows
Agentical's workflow architecture represents a fundamental advancement in automated trading. Rather than a single "smart" algorithm attempting to handle every trading aspect, the platform employs specialized agents working in coordinated workflows—each excelling at specific tasks, all contributing to comprehensive trading execution.
This distributed intelligence approach delivers consistency, speed, and discipline that single-agent systems and human traders cannot match. Discovery agents never sleep, analysis agents never rush decisions due to impatience, risk agents never lower standards to make a trade happen, and execution agents never hesitate from fear.
The workflows operate with mechanical precision, executing your strategy exactly as configured, 24 hours a day, 7 days a week. They don't get tired, emotional, or distracted. They don't deviate from the plan chasing FOMO, and they don't freeze when decisive action is needed.
Understanding these workflows transforms Agentical from a black box into a transparent, logical system you can trust to execute your trading strategy with unwavering discipline while you focus on the strategic decisions that only you can make.
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