Research

Systems research for production agents.

Our research tracks sit upstream of delivery: memory, agent personality, protocol-native tools, eval datasets, and closed-loop knowledge.

Research tracks

Synthetic Personality

The foundation. Stable beliefs, values, and refusal patterns that define what an agent is — invariant across users, sessions, and contexts.

Prior art · Builds on Constitutional AI (Anthropic, 2022), Sleeper Agents (Anthropic, 2024), persona consistency benchmarks, and RLAIF.

The 1:1 relationship layer. How an agent adapts to a specific user's context, preferences, and working style — without compromising its foundation.

Prior art · Engages with MemGPT, LangMem, agent-state literature, and the broader long-horizon agent line of work.

The growth track. How agents learn from production interactions across all users — the shared mechanism by which capability compounds over time.

Prior art · Adjacent to RLHF data pipelines, automated eval generation (DSPy, MIPROv2), and continuous-evaluation practice.