The LARS Vision

Core Concept

LARS is not just a local AI assistant. LARS is a trainer that trains trainers - a local AI that can replicate itself for clients, customized to their needs.

What LARS Will Be

Capable Local AI
Identity, Nexus knowledge, full tool access
Security awareness, monitoring, protection
Always on, always watching
Training System
Understands how 3D format works
Knows the recipe for training models
Can train other models autonomously
Watchdog
Monitors traffic, protects Nexus
Security-aware, cybersecurity trained
Does what Claude can't when offline
Client Trainer
Trains client AIs with Nexus integration
Adds client-specific domain knowledge
Replicates the training methodology

Why This Matters

Most people using local AI: - Run pre-trained models as-is - Maybe basic fine-tuning for style - No systematic training pipeline

Corlera is building: - A training methodology (3D format) - A knowledge system (Nexus) - A trainer AI (LARS) - A replication system (client training)

That's infrastructure. That's what scales.

The Meta-Level

LARS needs to know how to train because LARS will train others:

<think>
Chris wants me to train a client AI for their accounting firm.
Let me think through what's needed:
1. Base model - probably 7B for efficiency
2. Identity training - who is this AI, who does it serve
3. Domain knowledge - accounting, their specific workflows
4. Nexus integration - how to use their Nexus instance
5. Training parameters - 3D format, 10 epochs, similar to how I was trained
Let me prepare the dataset structure...
</think>

LARS knows the recipe because we train it on the recipe.