title: Parallel Worktree Execution Strategy

insight: Using Ralph Wiggum TRUE method with 3 git worktrees enables conflict-free parallel execution of 50 atomic stories across separate branches

reasoning_chain: Assessed Genesis system state - identified done (git worktrees, parallel scripts, AIVA on Elestio, memory stack) vs remaining (TRUE executor, syntax errors, placeholders)

reasoning_chain: Created 50 atomic stories split across 3 workers with non-overlapping file paths

reasoning_chain: Launched parallel Task agents in rwl-1, rwl-2, rwl-3 worktrees

reasoning_chain: Each worker executes independently without file conflicts

source_context: User requested: 'make sure all stories agents are able to paralellise without conflicts by use correct Ralphy method and git trees'


title: Token Usage MCP Server Creation

insight: Created dedicated MCP server for real-time token usage tracking with 6 tools for budget monitoring and cost metrics

reasoning_chain: Workers processing 2.4M+ tokens required real-time usage visibility

reasoning_chain: Existing cost_tracker needed MCP exposure for cross-session monitoring

reasoning_chain: Created server.py with get_usage_summary, get_budget_status, get_agent_breakdown, get_model_breakdown, log_usage, get_realtime_cost tools

source_context: Genesis created Token Usage MCP at /mnt/e/genesis-system/mcp-servers/token-usage/server.py


title: 50 Story PRD Execution Flow

insight: Multi-phase execution: assess → plan → split → parallelize → monitor → complete

reasoning_chain: Phase 1: Read AIVA folder docs, Ralph Wiggum TRUE method, genesis-aiva-activation document

reasoning_chain: Phase 2: Assess current state - what done vs remaining

reasoning_chain: Phase 3: Design PRD with 50 atomic stories (PM-001 to PM-050)

reasoning_chain: Phase 4: Split across 3 workers (RWL-1: PM-001-017 Core, RWL-2: PM-018-034 AIVA, RWL-3: PM-035-050 Revenue)

reasoning_chain: Phase 6: Monitor progress - Workers 1,2,3 all completed

source_context: Worker 1 completed PM-001-010, Worker 2 completed PM-018-026, Worker 3 completed PM-035-041


title: Ralph Wiggum TRUE Method Implementation

insight: Fresh session per task with tiered model escalation (Gemini → Sonnet → Opus) prevents context rot and optimizes cost

reasoning_chain: TRUE Method = Tiered model usage, Real-time tracking, Unified learning, Escalation rules

reasoning_chain: Tier 1: Gemini Flash ($0.01, 20 attempts) for simple tasks

reasoning_chain: Tier 2: Claude Sonnet ($0.15, 10 attempts) for medium complexity

reasoning_chain: Tier 3: Claude Opus ($0.75, 10 attempts) for complex reasoning

reasoning_chain: Estimated budget: ~$7.50 for 50 stories (well within $30 Claude + $300 Gemini)

source_context: Budget breakdown: Gemini Flash 90%, Claude Sonnet 8%, Claude Opus 2% - estimated total ~$7.50


title: AIVA Authority Framework Charter

insight: Created AIVA_CHARTER.md defining 4 authority levels from Autonomous to Human Override with permissions matrix and escalation protocols

reasoning_chain: PM-020 required creating authority framework for AIVA

reasoning_chain: Defined 4 levels: Autonomous, Semi-Autonomous, Supervised, Human Override

reasoning_chain: Created permissions matrix, operational/safety/ethical constraints

reasoning_chain: Established escalation protocols and accountability framework

source_context: Worker 2 completed PM-020: Created AIVA_CHARTER.md with full authority framework


title: Context Window Exhaustion

insight: Long-running parallel execution with 3 workers consuming massive context caused 'Prompt is too long' errors and session compaction failure

reasoning_chain: 3 parallel Task agents processing 2.4M+ tokens

reasoning_chain: System reminders and agent notifications accumulating

reasoning_chain: Compaction failed - session needs to be closed and reopened

source_context: Error: 'Conversation too long. Press esc twice to go up a few messages and try again'