Progress Pathway - Vision Crystallized
What Happened Today
Started with: 'Can we train LARS with identity?' Ended with: A complete vision for a trainer-that-trains-trainers.
The Journey
- Morning: Checked LARS server, downloaded 7B abliterated model
- Unsloth Failure: Bugs in 2025.12.9, abandoned for plain Transformers+PEFT
- 2D Training: Worked but model still said 'Qwen'
- Research: Found DeepSeek R1 approach, AM-DeepSeek dataset
- 3D Format Design: Created
/ structure - EXP-003 Breakthrough: LARS identifies as LARS, shows thinking
- EXP-004 Success: Task reasoning works on novel scenarios
- Vision Discussion: LARS as trainer, security watchdog, client system
Key Realizations
- 3D format is the foundation - Works for identity AND operations
- Recipe matters more than model size - 7B with right training beats larger untrained
- Workflow → Training pipeline - Everything we build should train LARS
- Hardware scales the vision - 3rd 3090 unlocks 30B, 6000 Pros unlock production
- LARS trains others - The meta-level that makes this a business
Chris's Vision (Captured)
'We need to create LARS to where LARS knows everything. LARS is not stupid. LARS is smart. LARS is capable. LARS is always willing to work and always willing to do what it needs to do and reason and think things through.'
'If I can have an AI system that trains all my clients' AIs the way that they need to be trained... not only textbook the way that they need to be trained for Nexus... but train them in the way that the company needs them to be trained for themselves... then LARS can do that training.'
Foundation Laid
- Training methodology: ✓
- Experiment tracking: ✓
- 4 successful experiments: ✓
- Hardware scaling path: ✓
- Vision documented: ✓
This is Day 1 of something significant.