# AI Context Management & Automation System Implementation Plan
## 🎯 Objective
Transform Gorev into an AI-optimized task management system that solves critical issues: 77.5% tasks stuck in "beklemede", 0% active tasks, and context loss in AI interactions.
## 🔍 Current Problem Analysis
### Critical Issues
- **77.5% tasks in "beklemede"** - No automatic state transitions
- **0% tasks in "devam_ediyor"** - AI forgets to update task states
- **Context loss** - Long conversations lose track of active work
- **Manual everything** - No automation or smart suggestions
- **Session discontinuity** - No persistent task context between interactions
### Root Causes
1. **AI behavioral patterns**: AIs naturally create tasks but forget to manage states
2. **Lack of context persistence**: Each conversation starts fresh
3. **No automation hooks**: Everything requires explicit commands
4. **Poor state transition UX**: Too many manual steps to update status
## 📋 Implementation Plan
### Phase 1: Context Management Foundation (Week 1) ✅ COMPLETED
**Goal**: Build core context system and automatic state management
#### Task 1.1: Database Schema Updates
- [x] Create `ai_context` table:
```sql
CREATE TABLE ai_context (
id INTEGER PRIMARY KEY,
active_task_id INTEGER REFERENCES gorevler(id),
session_id TEXT NOT NULL,
context_data JSON,
created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
updated_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP
);
```
- [x] Create `ai_interactions` table:
```sql
CREATE TABLE ai_interactions (
id INTEGER PRIMARY KEY,
task_id INTEGER REFERENCES gorevler(id),
interaction_type TEXT NOT NULL, -- 'view', 'update', 'create', 'complete'
interaction_data JSON,
ai_session_id TEXT,
created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP
);
```
- [x] Add columns to `gorevler` table:
```sql
ALTER TABLE gorevler ADD COLUMN last_ai_interaction TIMESTAMP;
ALTER TABLE gorevler ADD COLUMN estimated_hours REAL;
ALTER TABLE gorevler ADD COLUMN actual_hours REAL;
ALTER TABLE gorevler ADD COLUMN auto_status_enabled BOOLEAN DEFAULT TRUE;
```
#### Task 1.2: Core Context Manager (Go)
- [x] Create `internal/gorev/ai_context_manager.go`:
- `SetActiveTask(sessionID, taskID)` - Set active task for session
- `GetActiveTask(sessionID)` - Get current active task
- `GetRecentTasks(sessionID, limit)` - Get recent interactions
- `RecordInteraction(taskID, type, data)` - Log AI interaction
- `GetContextSummary(sessionID)` - Generate AI-optimized summary
#### Task 1.3: Auto-State Management System
- [x] Create `internal/gorev/auto_state_manager.go`:
- `AutoTransitionToInProgress(taskID)` - Auto-start when accessed
- `AutoTransitionToPending(taskID)` - Auto-pause after inactivity
- `CheckParentCompletion(taskID)` - Check if parent can be completed
- `ScheduleInactivityCheck(taskID)` - 30-minute inactivity timer
#### Task 1.4: New MCP Tools
- [x] `gorev_set_active` - Set active task context
- [x] `gorev_get_active` - Get current active task
- [x] `gorev_recent` - Get recent task interactions
- [x] `gorev_context_summary` - AI-optimized session summary
### Phase 2: Natural Language & Batch Operations (Week 2) ✅ COMPLETED
**Goal**: Enable natural language queries and efficient batch operations
#### Task 2.1: NLP Query System
- [x] Create `internal/gorev/nlp_processor.go`:
- Parse relative references: "son oluşturduğum görev", "bugün"
- Handle date expressions: "yarın yapalım" → tomorrow date
- Tag-based queries: "etiket:bug", "frontend görevleri"
- Status queries: "tamamlanmamış görevler", "devam edenler"
- [x] Implement `gorev_nlp_query` MCP tool:
- Smart query interpretation
- Context-aware results
- Relative date/time processing
- Fuzzy matching for task titles
#### Task 2.2: Batch Operations System
- [x] Create `internal/gorev/batch_processor.go`:
- `ProcessBatchUpdate(updates)` - Multiple task updates
- `BulkStatusTransition(taskIDs, newStatus)` - Mass status change
- `BulkTagOperation(taskIDs, tags, operation)` - Mass tag management
- `BulkDelete(taskIDs, confirmation)` - Mass deletion with safety
- [x] Implement batch MCP tools:
- `gorev_batch_update` - Update multiple tasks at once
- `gorev_bulk_transition` - Change status for multiple tasks ✅ COMPLETED
- `gorev_bulk_tag` - Add/remove tags from multiple tasks ✅ COMPLETED
#### Task 2.3: Smart Suggestions System ✅ COMPLETED
- [x] Create `internal/gorev/suggestion_engine.go`:
- Suggest next actions based on priorities
- Detect similar tasks and recommend templates
- Time estimation based on historical data
- Deadline risk analysis
### Phase 3: Automation & Intelligence (Week 3) ⏳ READY TO START
**Goal**: Add intelligent automation and predictive features
#### Task 3.1: Intelligent Task Creation ✅ COMPLETED
- [x] Auto-subtask splitting based on description analysis
- [x] ML-based time estimation using historical data
- [x] Similar task detection and template recommendation
- [x] Smart priority assignment based on keywords
#### Task 3.2: Integration Hooks [~] IN PROGRESS
- [x] File system watcher for project files
- [ ] Git commit hook integration
- [ ] VS Code workspace integration
- [ ] Automatic task updates based on code changes
#### Task 3.3: Predictive Analytics
- [ ] Task completion probability calculation
- [ ] Deadline miss risk assessment
- [ ] Bottleneck detection in task dependencies
- [ ] Performance trend analysis
## 🧪 Testing Strategy
### Unit Tests
- [ ] Context manager operations (95% coverage)
- [ ] Auto-state transitions (100% coverage)
- [ ] NLP query processing (90% coverage)
- [ ] Batch operations (95% coverage)
### Integration Tests
- [ ] MCP tool integration tests
- [ ] Database transaction consistency
- [ ] Cross-session context persistence
- [ ] Performance tests with 10K+ tasks
### E2E Tests
- [ ] Complete AI workflow scenarios
- [ ] Multi-session context preservation
- [ ] Batch operation performance
- [ ] Auto-state management accuracy
## 📊 Success Metrics
### Immediate Impact (After Phase 1)
- **Active task ratio**: >20% (from current 0%)
- **Context switches per session**: <5 (target: 2-3)
- **Auto-state accuracy**: >80%
- **User satisfaction**: Measurable through usage patterns
### Long-term Impact (After Phase 3)
- **Task completion rate**: >40% (from current 22.5%)
- **Average task lifecycle**: <7 days
- **Bulk operation usage**: >30% of all updates
- **AI interaction efficiency**: 50% fewer manual commands
## 🛠️ Technical Implementation Details
### Database Migrations
```sql
-- Migration 001: AI Context Tables
CREATE TABLE ai_context (...);
CREATE TABLE ai_interactions (...);
CREATE INDEX idx_ai_context_session ON ai_context(session_id);
CREATE INDEX idx_ai_interactions_task ON ai_interactions(task_id);
-- Migration 002: Enhanced Task Table
ALTER TABLE gorevler ADD COLUMN last_ai_interaction TIMESTAMP;
ALTER TABLE gorevler ADD COLUMN estimated_hours REAL;
ALTER TABLE gorevler ADD COLUMN actual_hours REAL;
```
### New MCP Tools Interface
```go
type AIContextTools struct {
contextManager *AIContextManager
stateManager *AutoStateManager
nlpProcessor *NLPProcessor
batchProcessor *BatchProcessor
}
// Core context tools
func (t *AIContextTools) SetActive(sessionID string, taskID int) error
func (t *AIContextTools) GetActive(sessionID string) (*Task, error)
func (t *AIContextTools) GetRecent(sessionID string, limit int) ([]Task, error)
func (t *AIContextTools) GetSummary(sessionID string) (*ContextSummary, error)
// NLP and batch tools
func (t *AIContextTools) NLPQuery(sessionID, query string) ([]Task, error)
func (t *AIContextTools) BatchUpdate(updates []TaskUpdate) error
func (t *AIContextTools) BulkTransition(taskIDs []int, status string) error
```
### Auto-State Logic
```go
type AutoStateManager struct {
inactivityTimer time.Duration // 30 minutes
db *Database
}
func (m *AutoStateManager) OnTaskAccess(taskID int, sessionID string) {
// Auto-transition to "devam_ediyor" if "beklemede"
// Reset inactivity timer
// Record interaction
}
func (m *AutoStateManager) OnInactivity(taskID int) {
// Auto-transition back to "beklemede"
// Preserve context for resume
}
```
## 🚀 Deployment Strategy
### Phase 1 Rollout (Week 1)
1. **Database migration** with backward compatibility
2. **Gradual MCP tool introduction** (feature flag controlled)
3. **User education** through documentation updates
4. **Monitoring** auto-state transition accuracy
### Phase 2 Rollout (Week 2)
1. **NLP query beta** with limited users
2. **Batch operations** with safety limits
3. **Performance monitoring** for large datasets
4. **Feedback collection** from power users
### Phase 3 Rollout (Week 3)
1. **Full feature activation** for all users
2. **Advanced analytics** dashboard
3. **Integration documentation** for developers
4. **Performance optimization** based on real usage
## 🔄 Rollback Plan
### Immediate Rollback Triggers
- Auto-state accuracy below 70%
- Performance degradation >20%
- Critical bugs in context management
- User productivity decrease
### Rollback Procedure
1. **Feature flags** to disable new tools
2. **Database rollback** scripts prepared
3. **Fallback to v0.11.0** behavior
4. **Data preservation** during rollback
## 📈 Monitoring & Analytics
### Key Metrics to Track
- Task state distribution (beklemede/devam_ediyor/tamamlandi)
- Average session context switches
- Auto-state transition accuracy
- Batch operation usage patterns
- NLP query success rate
- User engagement metrics
### Alerting Thresholds
- Auto-state accuracy drops below 75%
- Context retrieval latency >500ms
- Batch operation failure rate >5%
- Database query performance degradation
## 🎓 Learning & Adaptation
### Continuous Improvement
- **Weekly performance reviews** during first month
- **User feedback integration** into feature refinements
- **ML model training** for better predictions
- **Pattern analysis** for workflow optimization
### Success Celebration
When we achieve **>20% active tasks** and **<5 context switches per session**, we'll have fundamentally transformed Gorev from a static task tracker into an intelligent AI companion! 🎉
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*This comprehensive plan addresses the core inefficiencies in current AI-task management workflows and positions Gorev as a leader in AI-optimized productivity tools.*
