The Exocortex Architecture
Hobbes is a Context Composition Engine, not a Chatbot. Standard AI interactions are stateless and fleeting. Hobbes treats context as a tangible asset, maintaining a living "Memory Object" that allows you to break linear thought, switch tasks, and operate at the speed of thought. By pairing a local-first, privacy-centric architecture with advanced reasoning models, it extends your cognitive range without exposing your data. It is an exocortex designed for high-value execution, not just conversation.
The Exocortex leverages a local-first SQLite and JSON Store architecture, ensuring your data never leaves your machine.
Instead of a simple chat log, Hobbes maintains a "Memory Object". This object is a living, composed context updated by a background Summary Model (Gemini 3 Flash Preview). This allows for infinite context retention on relevant topics without blowing up the token window or losing the thread.
AI is delivering on the original dream of computing: the ability to speak to a machine in our own language and have it understand. While programmers have always given computers complex instructions, AI makes this power accessible to everyone. Hobbes makes it safe to connect this new capability to the tools and apps you use every day.
We found context to be something to be orchestrated. The system's Memory Object Architecture enables it to understand not just what you've discussed, but when, why, and how it connects to your broader goals.
This creates a living memory that evolves with each interaction, building a cumulative understanding that traditional RAG systems simply cannot achieve. When combined with dedicated long-term MCP memory storage for the agent, each session can quickly gain the context it needs to get you back on track. Starting fresh or with the memory of a previous session.
Every time we've onboarded a new partner to early testing, we've gotten to enjoy them light up with the joy and surprise of using an AI that's properly and securely grounded in facts. We'll keep working on making Hobbes better. We hope you enjoy being more productive.
Cognitive Translation
The Semantic Bridge
The challenge of building a trustworthy AI assistant begins with a fundamental translation problem: enabling nuanced, multi-domain communication between user intent and context-sensitive model behavior.
- Type-Safe Schema Conversion
- History-Grounded Error Correction
- Turn Re-Inversion
Context Orchestration
The Memory Engine
Building an AI assistant that remembers across sessions requires more than simple state management. It demands a sophisticated orchestration system that preserves the right information while discarding the noise.
- Reactive Session State
- Background Summarization
- Tool Call Snapshotting
HITL by Design
The Trust Architecture
The Human-In-The-Loop philosophy is not an afterthought in Hobbes; it is the foundational architecture that makes everything else possible. You need to trust your agent, and trust requires your ability to control it.
- Unified Permission Lifecycle
- Explicit Tool Approval
- Transparent Tool History