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Philosophy

Rewrite this - The problem Colony is designed to solve.

To extract or synthesize novel insights from a large established body of knowledge, the current breed of research agents may need to ingest large amounts of context perhaps in multiple passes revisiting the same information repeatedly. The order in which they ingest this context is important because it both determines data locality in LLM KV caches (inference cost) and affects the agent's likelihood to stumble upon novel connections. Moreover, in many cases, insights often emerge from unexpected connections between distant pieces of information which requires keeping the entire context live and accessible, not filtering it through retrieval.

Core Convictions

Three philosophical pillars support Colony's architecture:

  1. The NoRAG Paradigm -- Colony keeps the full context live and accessible, not filtering it through retrieval. RAG activates sparse subsets and misses the dense, cross-cutting connections where breakthroughs happen.

  2. Cache-Aware Patterns -- When context spans billions of tokens distributed across a GPU cluster, cache management is not an optimization -- it is the dominant factor in whether reasoning succeeds or fails.

  3. Agents All the Way Down -- General intelligence is not a property of any single model. It emerges from the right composition of LLM-based reasoning agents that communicate, coordinate, and collaborate across unbounded context.

  4. Parallelized, Distributed Reasoning -- Parallelized, distributed reasoning over partitioned context is the key to unbounded depth and breadth of reasoning.

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