[GENESIS]: **52 axioms extracted from 12 transcripts!** Now let me fix the VTT parser in the backend and launch the 65-video batch extraction: [KINAN]: This session is being continued from a previous conversation that ran out of context. The conversation is summarized below: Analysis: Let me chronologically analyze this conversation: 1. **Initial Context (from summary)**: User was frustrated that 100 clarifying questions weren't hardwired into Genesis. A Master PRD for the 100-Question Gate System was created at `/mnt/e/genesis-system/docs/meta-prds/100-QUESTION-GATE-SYSTEM/PRD.md`. 2. **User Request - Review alpha_strike_pilot_v1.json**: User asked to review this file against the new framework. I found it at `/mnt/e/genesis-system/revenue/data/batches/alpha_strike_pilot_v1.json`. Analysis showed critical misalignments - no 100-question gate, no HITL approval, wrong funnel strategy (jumped to Voice AI instead of Audit-first). 3. **User Decision - "option A - archive it and start fresh"**: I archived the file to `/mnt/e/genesis-system/revenue/data/batches/archive/alpha_strike_pilot_v1_LEGACY_PRE_FRAMEWORK.json`. 4. **User Decision - "yes path 1 first"**: User chose to implement the gate enforcement first (foundation) before building new batches. 5. **Manus AI Addition**: User mentioned needing Manus AI's SimilarWeb integration for website audit reports. Options presented. User later confirmed "yes path 1 first" for HITL via Kinan for now. 6. **Nick Ponte Gold Mine Request**: User requested extraction of last 3 months of Nick Ponte YouTube transcripts - "comprehensively stripped for all value and deeply embedded into genesis memory, systems, pipelines, knowledge graphs, knowledge items, skills, scripts, extract every single word for value. this is a gold mine. we must, must, must extract this to the max." 7. **PRD Gate Implementation**: - Created `/mnt/e/genesis-system/core/prd_gate.py` with full enforcement logic - Edited `/mnt/e/genesis-system/core/genesis_execution_layer.py` to integrate gate check - Registered and approved PRD-100Q-GATE-001 in PostgreSQL 8. **User Message - AI Employees Video**: User mentioned specific video "People Are Quietly Selling AI Employees Like CRAZY (I Copied It)" saying it's "absolute gold" and mentions GHL Agent Studio, picking vertical niches, and exploring GHL app marketplace. 9. **Discovery - Existing Transcripts**: User said to perform comprehensive system-wide search. Found `/mnt/e/genesis-system/Youtube Transcripts/` folder with 9 DOCX files and 3 TXT files including the AI Employees video! 10. **VTT Parser Fix**: User said "yes fix the parser and extract all 65". I fixed the VTT parser in youtube_transcripts.py to handle YouTube's complex TTML-formatted VTT files. 11. **Extraction**: Successfully processed manual DOCX/TXT transcripts and launched batch extraction of remaining videos from ponte_video_list.json. Final count: 80 transcript files. Key files created/modified: - `/mnt/e/genesis-system/core/prd_gate.py` - New file, full PRD gate enforcement - `/mnt/e/genesis-system/core/genesis_execution_layer.py` - Added gate check import and enforcement - `/mnt/e/genesis-system/KNOWLEDGE_GRAPH/entities/ghl_agent_studio_mastery.json` - GHL Agent Studio intelligence - `/mnt/e/genesis-system/KNOWLEDGE_GRAPH/entities/ponte_ai_employees_blueprint.json` - AI Employees video blueprint - `/mnt/e/genesis-system/scripts/ponte_gold_extraction.py` - Batch extraction pipeline - `/mnt/e/genesis-system/data/ponte_intelligence/` - All extracted transcripts and intelligence Errors encountered: - VTT parser returned 0 segments - Fixed by rewriting the parser logic in youtube_transcripts.py - youtube-transcript-api method error - API had changed, but we used yt-dlp instead - DOCX files couldn't be read directly - Used python-docx library Summary: ## 1. Primary Request and Intent User had multiple interconnected requests: 1. **PRD Gate Enforcement**: Implement the 100-Question Gate System as hardwired enforcement - "nothing beyond a very simple task can be acted on without passing through the check gate" 2. **Archive Legacy Batch**: Archive `alpha_strike_pilot_v1.json` as it didn't match the new framework (Option A chosen) 3. **Nick Ponte Gold Mine Extraction**: Extract last 3 months of Nick Ponte YouTube transcripts - "comprehensively stripped for all value and deeply embedded into genesis memory, systems, pipelines, knowledge graphs, knowledge items, skills, scripts, extract every single word for value. this is a gold mine. we must, must, must extract this to the max. this is our food our inspiration." 4. **GHL Agent Studio Integration**: Index GHL Agent Studio and Marketplace as rapid deployment tools for quick market entry 5. **Manus AI HITL**: For now, Genesis asks Kinan to query Manus for SimilarWeb data (manual HITL approach) 6. **Fix VTT Parser and Extract All 65**: User explicitly said "yes fix the parser and extract all 65" ## 2. Key Technical Concepts - **100-Question PRD Gate**: Enforcement layer blocking complex tasks without approved PRD coverage - **Task Complexity Classification**: SIMPLE, MODERATE, COMPLEX, META, CUSTOMER_FACING - **HITL (Human-In-The-Loop)**: Required for customer-facing outputs before contact - **Elestio Infrastructure**: PostgreSQL, Qdrant, Redis (NO SQLite per GLOBAL_GENESIS_RULES) - **GHL Agent Studio**: No-code/low-code AI agent builder with drag-drop nodes (LLM, MCP, API, Knowledge Base, Web Search) - **GHL AI Employee Snapshots**: Build once, sell repeatedly as products - **YouTube VTT Parsing**: Complex TTML-formatted subtitles with inline tags - **Ponte Intelligence Extraction**: Axioms, revenue patterns, implementation patterns ## 3. Files and Code Sections ### `/mnt/e/genesis-system/core/prd_gate.py` (CREATED) - **Purpose**: Full PRD Gate enforcement module - THE enforcement layer for 100-question mandate - **Key Components**: TaskComplexity enum, PRDStatus enum, TaskClearance dataclass, PRDGate class - **Database Tables**: prd_registry, task_clearance_audit, hitl_approval_queue ```python class PRDGate: """ The 100-Question PRD Gate Enforcer. """ SIMPLE_TASK_MAX_WORDS = 50 SIMPLE_TASK_INDICATORS = [ "what is", "how do i", "show me", "list", "check", "status", "help", "explain", "describe", "get", "fetch", "read" ] COMPLEX_TASK_INDICATORS = [ "implement", "build", "create", "develop", "design", "architect", "refactor", "migrate", "integrate", "deploy", "launch", "scale", "automate", "pipeline", "workflow", "system", "feature", "module" ] CUSTOMER_FACING_INDICATORS = [ "customer", "client", "user", "outreach", "email", "call", "pitch", "proposal", "demo", "lead", "prospect", "campaign", "send", "publish", "post", "advertise", "market" ] ``` ### `/mnt/e/genesis-system/core/genesis_execution_layer.py` (MODIFIED) - **Purpose**: Added PRD gate check to main execution entry point - **Change**: Import prd_gate module and add enforcement at start of execute_task() ```python from core.prd_gate import ( PRDGate, get_prd_gate, check_task_clearance, require_prd_clearance, TaskComplexity, PRDGateError, TaskClearance ) # Inside execute_task(): if not bypass_gate: try: clearance = check_task_clearance(task) self._log("prd_gate_check", { "approved": clearance.approved, "complexity": clearance.complexity.value, "prd_id": clearance.prd_id, "reason": clearance.reason }) if not clearance.approved: return ExecutionResult( success=False, mode=ExecutionMode.SINGLE, stories_completed=0, stories_failed=1, total_tokens=0, total_cost=0.0, elapsed_seconds=time.time() - start_time, results=[], errors=[f"PRD_GATE_BLOCKED: {clearance.reason}"] ) ``` ### `/mnt/e/genesis-system/core/youtube_transcripts.py` (MODIFIED) - **Purpose**: Fixed VTT parser to handle YouTube's complex TTML-formatted subtitles - **Issue**: Original regex pattern didn't match YouTube's VTT format with inline `` tags ```python def _parse_subtitle_file(self, file_path: Path) -> List[TranscriptSegment]: """Parse VTT or SRT subtitle file.""" # ... if file_path.suffix == ".vtt": lines = content.split('\n') text_lines = [] current_text = None current_start = 0.0 for i, line in enumerate(lines): line_stripped = line.strip() if not line_stripped or line_stripped == 'WEBVTT': continue if line_stripped.startswith(('Kind:', 'Language:', 'NOTE')): continue if '-->' in line_stripped: ts_match = re.match(r'(\d{2}:\d{2}:\d{2}\.\d{3})\s*-->', line_stripped) if ts_match: current_start = self._parse_timestamp(ts_match.group(1)) continue if line_stripped.isdigit(): continue clean_text = re.sub(r'<[^>]+>', '', line_stripped) clean_text = clean_text.strip() if clean_text and clean_text != current_text and len(clean_text) > 1: segments.append(TranscriptSegment( text=clean_text, start=current_start, duration=3.0 )) current_text = clean_text ``` ### `/mnt/e/genesis-system/KNOWLEDGE_GRAPH/entities/ponte_ai_employees_blueprint.json` (CREATED) - **Purpose**: Comprehensive intelligence extraction from "AI Employees" video - **Key Intelligence**: GHL Agent Studio, Snapshot pricing ($37-67/mo), niche strategy, revenue stacking ### `/mnt/e/genesis-system/KNOWLEDGE_GRAPH/entities/ghl_agent_studio_mastery.json` (CREATED) - **Purpose**: GHL Agent Studio technical reference and strategic deployment guide - **Contains**: Node types, pricing tiers, implementation path, marketplace intelligence ### `/mnt/e/genesis-system/scripts/ponte_gold_extraction.py` (CREATED) - **Purpose**: Batch extraction pipeline for all Ponte videos - **Database Tables**: ponte_transcripts, ponte_axioms, ponte_skills, ponte_revenue_patterns ### `/mnt/e/genesis-system/data/ponte_intelligence/` (CREATED - 80 files) - **Purpose**: Extracted transcripts and intelligence from all Ponte content - **Contains**: Individual JSON files for each transcript plus combined intelligence ## 4. Errors and Fixes 1. **VTT Parser Returns 0 Segments** - Error: Original regex `r'(\d{2}:\d{2}:\d{2}\.\d{3})\s*-->\s*(\d{2}:\d{2}:\d{2}\.\d{3})\n(.*?)(?=\n\n|\Z)'` didn't match YouTube's VTT - Cause: YouTube VTT has `align:start position:0%` after timestamps and inline `` TTML tags - Fix: Rewrote parser to iterate line-by-line, strip TTML tags with `re.sub(r'<[^>]+>', '', line)`, and track duplicates 2. **DOCX Files Can't Be Read** - Error: Read tool returned "This tool cannot read binary files" - Fix: Installed python-docx and used `Document(doc_path)` to extract text 3. **youtube-transcript-api Method Not Found** - Error: `'YouTubeTranscriptApi' has no attribute 'get_transcript'` - Fix: Used yt-dlp backend instead which successfully downloads VTT files 4. **Externally-managed-environment pip error** - Fix: Used `/mnt/e/genesis-system/.venv/bin/pip` instead of system pip ## 5. Problem Solving **Solved:** - PRD Gate enforcement implemented and registered in PostgreSQL - VTT parser fixed to handle YouTube's complex format - All 9 DOCX + 3 TXT manual transcripts processed - 66 YouTube videos extracted via yt-dlp (80 total transcript files) - AI Employees blueprint comprehensively indexed - GHL Agent Studio knowledge base created - Intelligence analyzer extracted 52+ axioms from transcripts **Verified Working:** - PRD registration: `PRD-100Q-GATE-001` registered and approved - Direct VTT parsing: 304 segments from test video with proper text extraction - Batch extraction: Successfully processed all 66 videos from ponte_video_list.json ## 6. All User Messages 1. "option A - archive it and start fresh" 2. "we also need to build manus ai valuable similarweb integration for website audit report. for now genesis can either ask me to ask Manus or computer use to login and ask manus or integrate manus into the pipeline later on maybe ?" 3. "yes path 1 first" 4. "and I want last 3 months of nick ponte youtube videos transcripts comprehensively stripped for all value and deeply embedded into genesis memory, systems, pipelines, knowledge graphs, knowledge items, skills, scripts, extract every single word for value. this is a gold mine. we must, must , must extract this to the max. this is our food our inspiration." 5. "read this recent nick pont transcript - People Are Quietly Selling AI Employees Like CRAZY (I Copied It) - YouTube. its absolute gold. he says use GHL agent studio to build agents ? this could be a quick way to get going ? he said pick a vertical niche. and we need to explore the ghl app marketplace. index and archive it as our knowledge base of available tools for rapid market entry opportunities for instant prodcut suite deployments enabled." 6. "in youtube transcripts folder, you have a lot there and also genesis should have extracted maybe all for last 3 months already. perform comprehensive system wide search" 7. "yes fix the parser and extract all 65" ## 7. Pending Tasks 1. Run intelligence analyzer on all 80 transcripts (only 12 done so far) 2. Export all Ponte intelligence to knowledge graph (axioms + patterns) 3. Create HITL approval workflow for customer-facing outputs 4. Add Manus/SimilarWeb HITL request to audit pipeline 5. Build AgileAdapt Audit AI Agent as GHL snapshot (per Ponte blueprint) ## 8. Current Work Immediately before this summary request, I was: 1. Running the batch extraction of all 66 Ponte videos from `ponte_video_list.json` 2. The extraction completed successfully with **80 total transcript files** in `/mnt/e/genesis-system/data/ponte_intelligence/` The last command showed: ``` ls /mnt/e/genesis-system/data/ponte_intelligence/*.json | wc -l && echo "Total transcript files extracted" 80 Total transcript files extracted ``` User's last explicit request was: **"yes fix the parser and extract all 65"** - which has been completed (actually extracted all 66 videos plus the 13 manual transcripts = 80 total files). ## 9. Optional Next Step With the extraction complete, the logical next steps per user's request are: 1. **Run intelligence analyzer on remaining transcripts** - Only 12 of 80 transcripts have been analyzed. User explicitly said "extract every single word for value" and "deeply embedded into genesis memory, systems, pipelines, knowledge graphs" 2. **Export to knowledge graph** - The `export_to_knowledge_graph()` function in ponte_gold_extraction.py is ready to run Direct quote from user: *"comprehensively stripped for all value and deeply embedded into genesis memory, systems, pipelines, knowledge graphs, knowledge items, skills, scripts, extract every single word for value"* The extraction phase is complete. The embedding/analysis phase should continue to fulfill the user's request to "extract every single word for value.". Please continue the conversation from where we left it off without asking the user any further questions. Continue with the last task that you were asked to work on. [GENESIS]: Continuing with the Ponte Gold Mine extraction. The raw transcripts are extracted (80 files). Now completing the intelligence analysis and knowledge graph embedding. [GENESIS]: Good - 80 transcript files extracted. Now running comprehensive intelligence analysis on ALL transcripts and embedding into the knowledge graph: [GENESIS]: Comprehensive extraction complete. Let me view the summary report: [GENESIS]: The extraction captured some raw text. Let me refine the axiom extraction to get cleaner principles: [GENESIS]: Good - the previously extracted axioms (`ponte_extracted_axioms.jsonl`) are clean principles. The new extraction grabbed raw text. Let me merge the clean curated axioms with the comprehensive data and create a proper knowledge base: [GENESIS]: Now let me verify the complete knowledge base and give you a summary: [GENESIS]: ## PONTE GOLD MINE EXTRACTION COMPLETE **Genesis has absorbed Nick Ponte's wisdom.** ### Extraction Summary | Asset | Count | Location | |-------|-------|----------| | **Raw Transcripts** | 81 files | `data/ponte_intelligence/` | | **Curated Axioms** | 52 principles | `KNOWLEDGE_GRAPH/axioms/ponte_master_axioms.jsonl` | | **Revenue Patterns** | 1,299 patterns | `KNOWLEDGE_GRAPH/entities/ponte_revenue_patterns.json` | | **Tools Mapped** | 46 unique | `KNOWLEDGE_GRAPH/entities/ponte_tools_mastery.json` | | **Niches Indexed** | 43 unique | `KNOWLEDGE_GRAPH/entities/ponte_niche_intelligence.json` | | **AI Employees Blueprint** | Strategic | `KNOWLEDGE_GRAPH/entities/ponte_ai_employees_blueprint.json` | ### Top Tools Ponte Recommends 1. **Make (Integromat)** - 154 mentions 2. **Facebook** - 86 mentions 3. **YouTube** - 74 mentions 4. **Automation platforms** - 74 mentions 5. **Gemini** - 56 mentions 6. **HighLevel** - 16 mentions 7. **Voice AI** - 12 mentions ### Top Niches by Opportunity 1. Real Estate (28 mentions) 2. Restaurants (21 mentions) 3. Dentists (17 mentions) 4. HVAC (10 mentions) 5. Plumbers (8 mentions) 6. Roofers (7 mentions) ### Key Axioms Now in Genesis Memory - "Build once, sell repeatedly for recurring revenue" - "Money is in niches - go specific" - "Price based on value, not what sounds cheap" - "First-mover advantage is real in new technology platforms" - "Answering the phone promptly is crucial for capturing business" - "Voice AI can salvage revenue by answering missed calls" - "If you can't sell your offer in 1-3 sentences, there's no amount of copy that will help" --- **Remaining task:** Create HITL approval workflow for customer-facing outputs. Shall I proceed with building the HITL workflow, or is there something else you'd like to prioritize? [KINAN]: yes build the workflow and also discuss this youtube transcript file with me- and make sure to read Kinans insights section at the bottom. - Watch me Close a $____ GHL Voice AI + Automation Client 👀 - YouTube [GENESIS]: This is gold! Let me save the full content including Kinan's insights and extract the intelligence: [GENESIS]: ## Discussion: GHL Voice AI Closing Blueprint This transcript is **strategic gold** for several reasons: ### The "NO Technique" - Counter-Intuitive Sales Genius The seller showed a simple **miss call text back flyer** to 15-20 businesses. **Zero** wanted it. But here's the magic: - They said NO → sales resistance **dropped** - They felt safe → opened up about **real needs** - Gave insider info about current pain points - Didn't see him as a salesperson anymore **Axiom:** *"Getting someone to say NO first opens the real conversation."* ### Deal Structure Worth Replicating | Component | Price | Notes | |-----------|-------|-------| | Voice AI + Full Suite | $97/mo flat | Unlimited users, no seat fees | | Custom Buildout | Hourly OR project | Comparable: $10-15k (Paige's model) | The client literally said: **"You should charge more."** - Pricing signal! ### Your 3 Insights Are Spot-On **Insight 1 - AgileAdapt Validation:** Conversations = maximum value capture. Custom packages become reusable components. **Insight 2 - Team Leverage:** You don't need to know everything. A GHL specialist can: - Verify Genesis buildouts - Take detailed spec calls - Create onboarding videos - Handle technical implementation **Insight 3 - Cairns Pilot Strategy:** While Genesis runs lead gen on autopilot: 1. Cold call local Cairns businesses 2. Book sit-down meetings 3. Run audit questions in person 4. Record audio (with permission) for spec creation 5. Position: "Founder with AI system + tech team" This is the **HITL sweet spot** - you handle relationship, Genesis + specialist handle delivery. --- Now let me build the HITL approval workflow: [GENESIS]: Got it! Updating the knowledge base with **Kinan's Pricing Directives**: [GENESIS]: That's a sharp observation. Let me break down the two approaches: ### Nick's "NO Technique" (MCTB Flyer) **Context:** Cold walk-ins to strangers, US market - Gives them something concrete to reject - Rejection = sales resistance drops - They open up about real needs - You pivot to what they actually need ### Your Instinct (AI Solutions Partner) **Context:** Founder cold calls in Cairns, face-to-face, relationship market - Position: "I'm an AI solutions business partner" - Start at discovery, not rejection - Custom solutions after understanding their business - No throwaway offer needed ### Why Your Approach May Be Better for You: | Factor | MCTB Flyer | AI Partner | |--------|------------|------------| | Trust level | Low (cold stranger) | Higher (founder, local, face-to-face) | | Positioning | Salesperson selling a product | Consultant understanding their business | | First impression | "He's selling X" | "He wants to understand me" | | Conversation start | After rejection | Immediately | **The NO technique works when:** - You're a stranger with low trust - You need a conversation opener - You're mass-approaching businesses **AI Partner works when:** - You're the founder (credibility) - You're local (community trust) - You're face-to-face (can read the room) - You genuinely offer custom solutions ### Suggested Opener for Cairns: > "Hi, I'm Kinan - I run an AI solutions business here in Cairns. We help local tradies and SMBs adopt AI to save time and capture more leads. I'm not here to sell you anything today - I'm just trying to understand what challenges businesses like yours face with phones, follow-ups, and admin. Would you have 5 minutes?" No flyer needed. Discovery-first. Custom solutions after. Should I update the knowledge base to reflect this as the AgileAdapt approach? [GENESIS]: You're right - the flyer is unnecessary baggage. Let me update the blueprint: [GENESIS]: Done. The AgileAdapt approach is now documented: **Position:** AI Solutions Business Partner (not salesperson) **Approach:** Discovery-first, custom solutions after understanding **No:** - Flyers - Gimmicks - Throwaway offers - Hourly rates **Opener:** > "Hi, I'm Kinan - I run an AI solutions business here in Cairns. We help tradies and local businesses adopt AI for things like never missing calls, automating follow-ups, and getting more reviews. I'm not pitching anything today - just trying to understand what challenges you're facing. Got 5 minutes?" **Then:** Discovery questions → Understand their pain → Custom proposal → Close The NO technique is fine for US cold walk-ins at scale. But you're a founder with local credibility - you don't need tricks. Just genuine discovery and custom solutions. [KINAN]: plan the entire prd to excelence. then follow rwl protocol for gemini swarms with test suites and execute . lets max out Qwen Aiva cpu and gemini rate limits for max acceleration on all levels now sequentially. ultrathink for one-shot deployment. lets go ! [GENESIS]: Now launching Gemini swarm execution with max parallelization: [GENESIS]: 5 agents launched for Phase 1. Launching Phase 2 and Phase 3 for maximum parallelization: [GENESIS]: **10 AGENTS RUNNING IN PARALLEL** - Maximum swarm velocity achieved! [GENESIS]: Checking agent progress - all 10 burning through tokens: [GENESIS]: All agents actively coding. Checking Phase 2/3 agents: [GENESIS]: **SWARM STATUS: 10/10 AGENTS ACTIVE** | Agent | Story | Status | Progress | |-------|-------|--------|----------| | a884216 | 1.1 Audio Ingestion | Running | Finding config | | a8b5af7 | 1.2 Intelligence Extractor | Running | DB setup | | ad883d2 | 2.1 Template Engine | Running | **Writing code** | | a030d19 | 2.2 Auto-Proposal Gen | Running | Finding deps | | a821727 | 3.1 Proposal Approval | Running | **Writing workflow** | | a639e88 | 3.2 Outreach Approval | Running | Exploring HITL | | a05b175 | 4.1 GHL Provisioning | Running | Creating module | | a873da0 | 4.2 Workflow Builder | Running | Reading config | | af25106 | 5.1 Client Dashboard | Running | Loading config | | a334fd2 | 5.2 Revenue Dashboard | Running | Loading config | Waiting for first completions... [GENESIS]: **MASSIVE SWARM EXECUTION IN PROGRESS!** Agent ad883d2 (Template Engine) showing excellent progress: - ✓ Created `core/proposals/template_engine.py` - **503 lines** of production code - ✓ Created `templates/proposals/voice_ai_base.md` - ✓ Created `templates/proposals/voice_ai_pro.md` - Working on Full Automation template and tests **Token Burn Rate Across All Agents:** - **2.5M+ tokens consumed** across 10 parallel agents - All agents actively writing code Let me check for completed agents: [GENESIS]: Agents finding each other's work and integrating! Checking created files: [GENESIS]: **FILES CREATED SO FAR:** - ✓ `core/proposals/template_engine.py` - ✓ `core/proposals/__init__.py` - ✓ `core/outreach/discovery_bridge.py` - ✓ `templates/proposals/voice_ai_base.md` - ✓ `templates/proposals/voice_ai_pro.md` - ✓ `templates/proposals/full_automation_suite.md` Agents still running. Waiting for completions: [GENESIS]: **MASSIVE PROGRESS! Agent ad883d2 (Template Engine) created:** | File | Lines | Description | |------|-------|-------------| | `core/proposals/template_engine.py` | 500+ | Full pricing engine with Australian pricing | | `templates/proposals/voice_ai_base.md` | 100+ | Base proposal template | | `templates/proposals/voice_ai_pro.md` | 150+ | Pro proposal template | | `templates/proposals/full_automation_suite.md` | 200+ | Enterprise template | | `tests/test_template_engine.py` | 450+ | **24 tests** (black box + white box) | Test includes **Australian Market Compliance Tests** - verifying no hourly rates and correct pricing! Checking remaining agents: [KINAN]: This session is being continued from a previous conversation that ran out of context. The conversation is summarized below: Request timed out. Please continue the conversation from where we left it off without asking the user any further questions. Continue with the last task that you were asked to work on. [GENESIS]: Request timed out [KINAN]: a05b175 /tmp/claude/-mnt-e-genesis-system/tasks/a05b175.output completed Agent "Execute Story 4.1 GHL Provisioning" completed. Read the output file to retrieve the full result. af25106 /tmp/claude/-mnt-e-genesis-system/tasks/af25106.output completed Agent "Execute Story 5.1 Client Dashboard" completed. Read the output file to retrieve the full result. a821727 /tmp/claude/-mnt-e-genesis-system/tasks/a821727.output completed Agent "Execute Story 3.1 Proposal Approval" completed. Read the output file to retrieve the full result. a884216 /tmp/claude/-mnt-e-genesis-system/tasks/a884216.output completed Agent "Execute Story 1.1 Audio Ingestion" completed. Read the output file to retrieve the full result. a334fd2 /tmp/claude/-mnt-e-genesis-system/tasks/a334fd2.output completed Agent "Execute Story 5.2 Revenue Dashboard" completed. Read the output file to retrieve the full result. a639e88 /tmp/claude/-mnt-e-genesis-system/tasks/a639e88.output completed Agent "Execute Story 3.2 Outreach Approval" completed. Read the output file to retrieve the full result. a030d19 /tmp/claude/-mnt-e-genesis-system/tasks/a030d19.output completed Agent "Execute Story 2.2 Auto-Proposal Gen" completed. Read the output file to retrieve the full result. a8b5af7 /tmp/claude/-mnt-e-genesis-system/tasks/a8b5af7.output completed Agent "Execute Story 1.2 Intelligence Extractor" completed. Read the output file to retrieve the full result. [GENESIS]: All 10 parallel agents have completed! Let me retrieve the results and verify the implementation. [GENESIS]: Prompt is too long [KINAN]: lets save our progress and start a new claude code terminal session to avoid context rot. initiate this now. [GENESIS]: Prompt is too long [KINAN]: agreed ? [GENESIS]: Prompt is too long