Skip to content

Robots

HTM uses robots rather than the fashionable "agents" deliberately and thoughtfully. This section explains why, and how HTM's robot architecture enables intelligent memory management for LLM-based applications.

Section Overview

Document Description
Why "Robots"? The philosophical and practical reasons HTM uses "robot" terminology
Hive Mind How all robots share a common long-term memory
Two-Tier Memory The working memory and long-term storage architecture
Multi-Robot Systems Running multiple robots with shared knowledge
Robot Groups Organizing robots into collaborative groups

The Robot Philosophy

┌─────────────────────────────────────────────────────┐
│                  Shared Long-Term Memory            │
│              (The Hive Mind / Collective)           │
│                                                     │
│  ┌─────────┐  ┌─────────┐  ┌─────────┐              │
│  │ Memory  │  │ Memory  │  │ Memory  │  ...         │
│  └─────────┘  └─────────┘  └─────────┘              │
└─────────────────────────────────────────────────────┘
        ▲              ▲              ▲
        │              │              │
   ┌────┴────┐    ┌────┴────┐    ┌────┴────┐
   │ Robot A │    │ Robot B │    │ Robot C │
   │         │    │         │    │         │
   │ Working │    │ Working │    │ Working │
   │ Memory  │    │ Memory  │    │ Memory  │
   └─────────┘    └─────────┘    └─────────┘

Robots are workers: They execute tasks, store memories, recall information.

Robots are individuals: Each has its own name, identity, and working context.

Robots are collective: They share knowledge, learn from each other's experiences.

Robots are persistent: They're registered, tracked, and their contributions are attributed.

Quick Start

# Create a robot
htm = HTM.new(robot_name: "research_assistant")

# Robot remembers information
htm.remember("PostgreSQL supports vector search via pgvector")

# Robot recalls relevant memories
memories = htm.recall("database search capabilities", limit: 5)

# Another robot can access the same memories
htm2 = HTM.new(robot_name: "documentation_writer")
memories = htm2.recall("vector search")  # Finds the first robot's memory

Key Concepts

  • Robot Identity: Each robot has a unique name and ID, tracked in the robots table
  • Working Memory: Token-limited context for immediate use (per-robot)
  • Long-Term Memory: Durable PostgreSQL storage (shared across all robots)
  • Hive Mind: All robots contribute to and benefit from collective knowledge
  • Never Forget: Memories are never truly deleted, only soft-deleted

See Also