Research on Cognitive Architectures
Open research on general intelligence architectures, alignment techniques, and scalable learning systems.
Research Focus Areas
Practical approaches to building more capable and reliable AI systems.
Cognitive Architectures
Layered system designs separating planning, reasoning, execution, and oversight into composable components.
Multi-Agent Coordination
Patterns for multiple AI models working together: orchestration, specialization, debate, and consensus.
Tool-Using Agents
Architectures for agents that effectively use external tools, APIs, and execution environments.
Alignment & Interpretability
Self-monitoring systems, uncertainty quantification, and techniques for understanding model behavior.
Multi-Model Debate
Structured disagreement for error detection: adversarial verification, iterative refinement, and consensus.
Uncertainty Quantification
Calibration, knowing what you don't know, and appropriate abstention in AI systems.
Recent Research Notes
View all →Tool-Using Agent Architectures
Patterns for agents that use external tools: ReAct, plan-then-execute, tool selection, sandboxing, and error handling.
CoordinationMulti-Agent Coordination
Patterns for multiple AI agents working together: orchestrator-worker, pipelines, debate, and hierarchical structures.
Follow the Research
This is an open research project. All notes and explorations are shared publicly. Follow along on GitHub or check back for updates.
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