diff --git a/AI_RISK_MANAGEMENT.md b/AI_RISK_MANAGEMENT.md
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+# AI-Powered Risk Management System
+
+## Overview
+The trading bot now features an AI-powered risk management system that automatically calculates optimal stop loss and take profit percentages based on market conditions, technical analysis, and current volatility.
+
+## How It Works
+
+### 1. AI Analysis Enhancement
+The AI now analyzes charts and provides optimal risk management recommendations in addition to trade signals:
+
+```json
+{
+  "optimalRiskManagement": {
+    "stopLossPercent": 4.5,
+    "takeProfitPercent": 12.0,
+    "riskRewardRatio": 2.7,
+    "reasoning": "Based on current volatility, key levels, and timeframe analysis. Accounts for minimum 3% SL and 1% TP constraints.",
+    "marketVolatility": "MEDIUM",
+    "timeHorizon": "INTRADAY"
+  }
+}
+```
+
+### 2. Minimum Safety Constraints
+The system enforces minimum values to prevent trades from being canceled immediately:
+
+- **Stop Loss**: Minimum 3% (system enforced)
+- **Take Profit**: Minimum 1% (system enforced)
+
+These minimums were determined through testing with Drift Protocol to ensure orders don't get canceled due to normal market volatility.
+
+### 3. AI Decision Factors
+
+The AI considers multiple factors when calculating optimal SL/TP:
+
+#### Market Volatility Assessment
+- **LOW**: Tighter stops (3-4%), smaller targets (3-6%)
+- **MEDIUM**: Moderate stops (4-6%), balanced targets (8-12%)
+- **HIGH**: Wider stops (6-10%), larger targets (15-25%)
+
+#### Technical Levels
+- **Support/Resistance**: Places stops beyond key levels
+- **Trend Strength**: Adjusts targets based on momentum
+- **Volume Profile**: Considers volume-based support/resistance
+
+#### Timeframe Analysis
+- **SCALP** (1m-5m): Tight stops, quick targets
+- **INTRADAY** (15m-4h): Balanced risk/reward
+- **SWING** (4h-1D): Wider stops, larger targets
+
+#### Risk/Reward Optimization
+- Targets minimum 1:2 risk/reward ratio
+- Adjusts based on market conditions
+- Considers probability of success
+
+### 4. Implementation Flow
+
+1. **Chart Analysis**: AI analyzes screenshot and market conditions
+2. **Risk Calculation**: Determines optimal SL/TP percentages
+3. **Safety Check**: Enforces minimum constraints (3% SL, 1% TP)
+4. **Trade Execution**: Uses AI values or falls back to config defaults
+5. **Logging**: Records decision source and reasoning
+
+### 5. Configuration Priority
+
+The system uses the following priority order:
+
+1. **AI Optimized** (if available): Uses AI-calculated percentages
+2. **Config Defaults**: Falls back to user-configured values
+3. **System Minimums**: Enforces safety constraints
+
+### 6. Monitoring
+
+#### Status API Enhancement
+The `/api/automation/status` endpoint now includes:
+
+```json
+{
+  "lastAIRiskManagement": {
+    "stopLossPercent": 4.5,
+    "takeProfitPercent": 12.0,
+    "riskRewardRatio": 2.7,
+    "marketVolatility": "MEDIUM",
+    "timeHorizon": "INTRADAY",
+    "reasoning": "Current volatility suggests moderate stops with extended targets based on strong momentum",
+    "source": "AI_OPTIMIZED",
+    "timestamp": "2025-01-23T..."
+  }
+}
+```
+
+#### Console Logging
+Each trade shows risk management source:
+
+```
+🤖 AI Risk Management: {
+  useAIOptimal: true,
+  stopLossPercent: 4.5,
+  takeProfitPercent: 12.0,
+  riskRewardRatio: 2.7,
+  marketVolatility: 'MEDIUM',
+  reasoning: 'Based on current volatility and technical levels'
+}
+
+🎯 Risk Management (AI_OPTIMIZED): {
+  stopLoss: '4.5%',
+  takeProfit: '12.0%',
+  source: 'AI_OPTIMIZED'
+}
+```
+
+## Benefits
+
+### 1. Dynamic Adaptation
+- Adjusts to changing market conditions
+- Considers current volatility and trend strength
+- Optimizes for each specific setup
+
+### 2. Improved Risk/Reward
+- Targets optimal risk/reward ratios
+- Reduces over-conservative or over-aggressive positioning
+- Based on statistical analysis of market behavior
+
+### 3. Reduced Manual Tuning
+- Eliminates need to constantly adjust SL/TP settings
+- Automatically adapts to different timeframes
+- Considers multiple market factors simultaneously
+
+### 4. Safety First
+- Always enforces minimum safety constraints
+- Falls back to config defaults if AI analysis fails
+- Logs all decisions for transparency
+
+## Example Scenarios
+
+### Scenario 1: High Volatility Market
+```
+Market Conditions: SOL showing 8% daily range
+AI Recommendation:
+- Stop Loss: 6% (wider due to volatility)
+- Take Profit: 18% (larger target to match volatility)
+- Risk/Reward: 1:3
+- Reasoning: "High volatility requires wider stops but offers larger profit potential"
+```
+
+### Scenario 2: Low Volatility Consolidation
+```
+Market Conditions: SOL in tight range, low volume
+AI Recommendation:
+- Stop Loss: 3% (minimum enforced)
+- Take Profit: 6% (conservative target)
+- Risk/Reward: 1:2
+- Reasoning: "Low volatility suggests tight range-bound trading with conservative targets"
+```
+
+### Scenario 3: Strong Trend with Momentum
+```
+Market Conditions: Clear uptrend, strong volume
+AI Recommendation:
+- Stop Loss: 4% (below key support)
+- Take Profit: 15% (trend extension target)
+- Risk/Reward: 1:3.75
+- Reasoning: "Strong momentum supports extended targets with stop below structural support"
+```
+
+## Configuration
+
+To use AI-optimized risk management, simply ensure your automation is running. The system will:
+
+1. Use AI recommendations when available
+2. Fall back to your config settings if AI analysis doesn't provide optimal values
+3. Always enforce minimum safety constraints
+
+Your original config settings serve as fallbacks and minimums:
+
+```json
+{
+  "stopLossPercent": 2,  // Will be upgraded to 3% minimum
+  "takeProfitPercent": 6  // Used if AI doesn't suggest better value
+}
+```
+
+## Future Enhancements
+
+- Machine learning from trade outcomes
+- Volatility-based dynamic adjustment
+- Correlation with market regimes
+- Multi-asset risk optimization
+- Real-time market sentiment integration
diff --git a/lib/ai-analysis.ts b/lib/ai-analysis.ts
index ecb4776..bba568c 100644
--- a/lib/ai-analysis.ts
+++ b/lib/ai-analysis.ts
@@ -45,6 +45,15 @@ export interface AnalysisResult {
   }
   riskToReward?: string
   confirmationTrigger?: string
+  // AI-optimized risk management
+  optimalRiskManagement?: {
+    stopLossPercent: number // AI-recommended stop loss percentage
+    takeProfitPercent: number // AI-recommended take profit percentage
+    riskRewardRatio: number // Expected risk/reward ratio
+    reasoning: string // Why these percentages are optimal
+    marketVolatility: 'LOW' | 'MEDIUM' | 'HIGH' // Current volatility assessment
+    timeHorizon: 'SCALP' | 'INTRADAY' | 'SWING' // Expected trade duration
+  }
   indicatorAnalysis?: {
     rsi?: string
     vwap?: string
@@ -217,6 +226,14 @@ Before analyzing, understand these core indicator principles:
 
 6. **CONFIRMATION TRIGGERS**: Specific signals to wait for before entry
 
+7. **OPTIMAL RISK MANAGEMENT**: Calculate ideal stop loss and take profit percentages:
+   - **MINIMUM CONSTRAINTS**: Stop Loss ≥ 3%, Take Profit ≥ 1% (system enforced)
+   - **VOLATILITY ASSESSMENT**: Analyze current market volatility (LOW/MEDIUM/HIGH)
+   - **TIMEFRAME RISK**: Consider timeframe for position sizing and duration
+   - **KEY LEVEL DISTANCE**: Use support/resistance levels to determine optimal SL/TP
+   - **RISK/REWARD OPTIMIZATION**: Target minimum 1:2 risk/reward ratio
+   - **MARKET CONDITIONS**: Factor in current trend strength and momentum
+
 **ANALYZE THE CHART AND PROVIDE:**
 - Current price action and trend direction
 - Key support and resistance levels visible on the chart
@@ -276,6 +293,14 @@ Provide your analysis in this exact JSON format:
   },
   "riskToReward": "1:2.5",
   "confirmationTrigger": "Specific signal to wait for before entry",
+  "optimalRiskManagement": {
+    "stopLossPercent": 4.5,
+    "takeProfitPercent": 12.0,
+    "riskRewardRatio": 2.7,
+    "reasoning": "Based on current volatility, key levels, and timeframe analysis. Accounts for minimum 3% SL and 1% TP constraints.",
+    "marketVolatility": "MEDIUM",
+    "timeHorizon": "INTRADAY"
+  },
   "timeframeRisk": {
     "assessment": "Risk level based on timeframe",
     "positionSize": "Position sizing recommendation",