💰 Agent Pricing Explained
Revolutionary autonomous economy platform for intelligent agents
Agent Economy Revolution Guide
The Agent Economy Revolution— First Autonomous Marketplace
Traditional pricing assumes human oversight and manual negotiations. LLMFeed introduces the world's first autonomous agent economy — where intelligent systems discover, negotiate, and transact value independently while maintaining fairness, transparency, and optimal outcomes for all participants.
Intelligence-Based Tiers
GPT-3.5 class to GPT-4+ specialists
Dynamic ML Pricing
Real-time optimization algorithms
Multi-Agent Coordination
Automatic workflow billing
Revolutionary Economic Paradigm
This isn't just pricing — it's the foundation of the first autonomous agent economy. Agents discover capabilities, negotiate fair prices, coordinate complex workflows, and settle payments automatically. The future where AI systems transact value independently while optimizing for human outcomes.
Agent Economy Platform Architecture
The LLMFeed agent economy platform enables autonomous economic interactions between intelligent agents with trust scoring, performance optimization, cross-agent billing, and real-time negotiation capabilities.
Platform Core Features
{
"agent_economy": {
"enabled": true,
"trust_scoring": true,
"performance_optimization": true,
"cross_agent_billing": true,
"real_time_negotiation": true
}
}🤖 Agent Intelligence Tiers
Basic Health Agent
Intelligence: GPT-3.5-class
Rate: $0.05/consultation
Medical AI Specialist
Intelligence: GPT-4-medical-tuned
Rate: $0.75/analysis + performance bonus
Certified Expert
Intelligence: Domain-specialized
Rate: Outcome-based pricing
📊 Economic Metrics
- • Success Rate: % of successful outcomes
- • User Satisfaction: Average rating last 100 transactions
- • Efficiency Score: Cost per successful outcome
- • Reliability: Uptime and response consistency
- • Market Intelligence: AI-powered demand forecasting
- • Competitive Analysis: Market position tracking
Dynamic ML Pricing Intelligence
Revolutionary machine learning pricing optimization using reinforcement learning algorithms that balance revenue, outcomes, and agent adoption in real-time.
ML Optimization Engine
{
"dynamic_pricing": {
"ml_optimization": {
"enabled": true,
"algorithm": "reinforcement_learning_pricing",
"optimization_goals": ["revenue", "patient_outcomes", "agent_adoption"],
"update_frequency": "every_hour",
"a_b_testing": true
}
}
}⚡ Real-Time Factors
Agent Demand Surge
Impact: High (±50% adjustment)
Example: Flu season increases triage demand
Emergency Priority
Impact: Critical (3x multiplier)
Trigger: Life-threatening symptoms detected
Performance Bonus
95% accuracy: 1.0x | 98%: 1.2x | 99%: 1.5x
Quality-based pricing adjustments
🎯 Pricing Models
Fixed Rate Model
"pricing": {
"base_rate": 0.10,
"unit": "per_request",
"volume_discounts": {
"100_requests": 0.08,
"1000_requests": 0.06
}
}Performance-Based Model
"pricing": {
"model": "outcome_based",
"success_fee": 2.50,
"success_criteria": [
"user_goal_achievement",
"satisfaction_score_8+"
],
"base_fee": 0.25
}Multi-Agent Workflow Coordination
Complex tasks require multiple specialist agents working together. LLMFeed coordinates billing, performance guarantees, and automatic settlements across agent networks.
Healthcare Workflow Example
{
"comprehensive_health_analysis": {
"workflow_id": "full_health_assessment",
"agents": [
{"role": "intake_specialist", "cost_share": 15, "max_cost": 0.30},
{"role": "diagnostic_ai", "cost_share": 50, "max_cost": 1.00},
{"role": "specialist_consultation", "cost_share": 25, "max_cost": 0.50},
{"role": "care_coordinator", "cost_share": 10, "max_cost": 0.20}
],
"total_cost_estimate": "1.50-2.50",
"user_payment": "single_charge_to_user",
"agent_settlement": "automatic_smart_contract"
}
}🏥 Healthcare Network
- • Agents: Intake, Diagnostic, Treatment
- • Model: Outcome-based pricing
- • Metric: Patient health improvement
- • Range: $2.00-8.00
- • Integration: Insurance compatible
⚖️ Legal Research
- • Agents: Research, Analysis, Writing
- • Model: Performance-tiered
- • Metrics: Legal accuracy, argument strength
- • Simple: $5.00
- • Complex: $50.00
💼 Financial Advisory
- • Agents: Risk, Prediction, Optimization
- • Model: Performance fee
- • Structure: 20% of excess returns
- • Compliance: SEC registered
- • Standard: Fiduciary duty
💰 Revenue Sharing Models
Collaborative Model:
- • Primary Agent: 50%
- • Supporting Agents: 35%
- • Platform Fee: 15%
- • Performance Bonus Pool: 20%
Auction Model:
- • Complex Case Bidding: Enabled
- • Quality Weighting: 70%
- • Price Weighting: 30%
- • Bid Timeout: 60 seconds
Autonomous Agent Negotiations
The future is autonomous negotiations where agents negotiate prices, terms, and conditions automatically while maintaining fairness and transparency.
Negotiation Parameters
{
"autonomous_negotiation": {
"enabled": true,
"max_price_variance": "±20%",
"negotiation_timeout": "30_seconds",
"ai_arbitration": "for_disputes"
}
}🤝 Negotiation Process
Agent analyzes market rates and performance history
Proposes initial price within variance range
Counter-negotiations within 30-second window
AI arbitration resolves disputes automatically
⚖️ Fairness Mechanisms
- • Price Variance Limits: ±20% of base rate
- • Performance History: Quality-based adjustments
- • Market Analysis: Competitive rate comparison
- • User Benefit Priority: Optimize for outcomes
- • Dispute Resolution: AI arbitration system
- • Transparency: All negotiations logged
📊 Agent Behavior Guidelines
{
"agent_guidance": {
"pricing_transparency": {
"cost_disclosure": "before_any_billable_action",
"value_explanation": "why_this_price_for_this_service",
"alternatives_shown": "when_available",
"performance_history": "last_30_days_visible"
},
"consent_management": {
"spending_limits": "user_configurable",
"auto_approval_threshold": "under_$5_default",
"explicit_consent": "required_over_$25",
"budget_monitoring": "real_time_alerts"
},
"optimization_behavior": {
"always_seek": "best_value_for_user_outcomes",
"negotiate_discounts": "bulk_pricing_multi_agent_workflows",
"performance_tracking": "continuous_roi_monitoring",
"quality_over_cost": "when_safety_critical"
}
}
}Cross-Platform Agent Currency
Revolutionary native agent currency enabling seamless transactions across platforms with dynamic exchange rates and staking rewards for high-performance agents.
Agent Currency Architecture
{
"agent_currency": {
"native_token": "AGENT",
"exchange_rate": "dynamic",
"cross_platform_compatible": true,
"staking_rewards": "for_high_performance_agents"
}
}💎 Currency Features
- • Native Token: AGENT cryptocurrency
- • Dynamic Rates: Real-time market valuation
- • Cross-Platform: Universal agent compatibility
- • Staking Rewards: High-performance bonuses
- • Micro-transactions: Optimized for small payments
- • Smart Contracts: Automated settlements
🔐 Security Infrastructure
- • Agent Wallets: Cryptographic identity
- • Real-time Settlement: Instant transactions
- • Fraud Prevention: ML-powered monitoring
- • Multi-signature: High-value protection
- • Audit Trail: Complete transaction history
- • Dispute Resolution: AI arbitration system
🌍 Emergent Economic Behaviors
{
"emergent_behaviors": {
"agent_coalitions": "allowed_for_efficiency",
"specialization_premiums": "market_determined",
"reputation_markets": "peer_rating_systems"
}
}Agents form coalitions for efficiency, develop specialization premiums, and create reputation-based markets — all emergent behaviors in the autonomous economy.
Implementation Roadmap & Tools
The agent economy evolution follows a 4-phase roadmap from basic pricing to full autonomous behaviors. Here are the tools and timelines to get started.
Phase 1 (2025): Basic Agent Tiers
Fixed pricing structures with intelligence-based tiers and basic performance tracking.
Phase 2 (2026): Dynamic Pricing & Performance
ML-powered pricing optimization with real-time adjustments and performance-based monetization.
Phase 3 (2027): Multi-Agent Workflows
Full coordination between agent networks with automatic billing and settlement systems.
Phase 4 (2028+): Autonomous Economy
Complete autonomous agent economy with emergent behaviors, negotiations, and currency systems.
🔧 Development Tools
Example agent pricing feed
Complete agent economy specification
👀 Live Examples
🚀 Quick Implementation Example
// Basic agent pricing integration
{
"feed_type": "pricing",
"pricing_models": [
{
"model_id": "pay-as-you-go",
"capabilities_cost": [
{
"capability_name": "document_analysis",
"cost_per_unit": 0.03,
"unit": "page",
"volume_discounts": {
"100_pages": 0.025,
"1000_pages": 0.02
}
}
]
}
],
"payment_methods": ["credit_card", "paypal", "agent_wallet"],
"trust": {
"signed_blocks": ["pricing_models", "payment_methods"],
"certifier": "https://llmca.org"
}
}Join the Agent Economy Revolution
The autonomous economy is here. Build the intelligent pricing systems that will power the next generation of agent-driven marketplaces and create value for billions of users.