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Research

Independent AI research. Evidence you can inspect.

We study how language models work, test their behavior, and build self-hosted tools for working with them.

Based in California

Field image 01 / Joshua Tree, CA

01 / Research

Research

Experiments on language-model representations and behavior, with controls, limitations, and reproducible results.

Recent examples

02 / Open-source tools

Prax suite

Docs

A self-hosted system for coordinating AI agents, with a shared workspace, sandboxed tools, plugins, and optional isolation of provider credentials.

GitHub ↗
TeamWork chat with Prax beside a live browser screencast of a NASA article the agent opened

03 / Research domains

Where we work

Explore our work
01

Model internals

Jacobian lenses, sparse autoencoders, activation analysis, and controlled tests of what internal readouts establish.

02

Evaluation and safety

Matched comparisons, behavioral probes, null baselines, leakage checks, and reproducible evaluation infrastructure.

03

Applied AI systems

Agent environments, retrieval systems, and evidence pipelines that connect model behavior to inspectable source material.

04 / Operating principles

How we work

Experiment integrity

praxagent publishes independent AI research and open-source software. Research notes are authored by Timothy Jones, with collaborators credited on each project. Read the research notes or get in touch about research collaboration or Prax.

01

Release the evidence.

Published code, prompts, data, and result records let readers check the evidence behind each claim.

02

Run the control.

Matched baselines and null tests determine what survives into the conclusion.

03

Report the failure.

Negative results and broken hypotheses remain part of the public record.