Agentic Intelligence Lab

SYS: AGENT_ALIGNMENT X:--- Y:---

FIG. 1A Route selection under shifting task, model, latency, and cost pressure.

SYS: MEMORY_DISPERSION X:--- Y:---

FIG. 1B Memory as evolving system state, not static chat history.

Working Thesis

Persistent AI

The next frontier is not larger chat. It is AI systems that compound experience: keeping useful memory, acquiring context before acting, routing across models, executing with discipline, and turning outcomes into the next version.

Agentic Intelligence Lab builds underneath that frontier: agent products that create real episodes, harnesses that shape context and boundaries, routers that choose the best model at the best time, and inference and learning systems that make improvement auditable.

Persistent AI must remember, choose, act, learn, and safely improve.

SYS: CONTEXT_STRATA X:--- Y:---

FIG. 2 Context boundaries, model routing, and inference load as one system surface.

Focus 01

Research

Papers from systems we build: recursive learning, routing, inference, context, and kernels.

Open research

Focus 02

Ecosystem

Open infrastructure for agents, harnesses, models, and runtime learning loops.

Open ecosystem

Focus 03

People

Industry leaders and frontier researchers building the persistent AI loop.

Meet people