Stateful systems for stateless models.
The current trajectory of AI — scaling context windows indefinitely — is a structural dead end. Attention dilution, computational waste, behavioral drift. These aren't bugs. They're the architecture.
The next generation of AI systems will not scale context. They will scale memory.
Our agents operate with zero short-term memory. Context is flushed after every turn. Continuity comes from a tiered retrieval backend that handles consolidation, decay, and recall — the hippocampus — so the model can function purely as cortex. This allows agents to operate continuously for months without behavioral drift.
Research
- Tiered memory consolidation with adaptive decay
- Procedural extraction from unstructured behavioral history
- Entity resolution across noisy, high-cardinality datasets
- Graph-augmented retrieval with hybrid ranking
Open Source
Gollem
The execution layer. Production-grade Go framework for LLM agents. Durable execution, streaming, strict structured output. Native Temporal integration. Fugue provides the memory. Gollem provides the runtime.
Infinite context is a crutch for poor retrieval. True intelligence requires the ability to forget.