Evaluation and interpretability
Tests that show what a model can actually do, why it fails, and whether an apparent improvement is real.
bougia Labs
Work on the open questions in AI.
bougia Labs is the research arm of bougia AI. We study reasoning, learning, evaluation, and efficient models through focused experiments, and publish what we learn.
Research priorities
What the Lab is working on.
Current focus
Reasoning and learning in language models
How models plan, revise, use tools, and improve from feedback, and how those abilities can be measured beyond polished final answers.
Related questions
Efficient training and adaptation
How better data, post-training, and smaller models can produce stronger systems with less compute.
Agents and long-horizon tasks
How models maintain context, choose actions, recover from mistakes, and complete work over many steps.
Values
How the Lab works.
Curiosity with evidence.
Interesting claims need experiments that can prove them wrong.
Fast, careful experimentation.
Move quickly, keep the work reproducible, and change course when the evidence does.
Responsibility grows with capability.
Study limits and risks alongside progress, not after it.
Research
Research notes.
Notes and results from Lab experiments. Short, concrete, and written to be checked.
20 July 2026 · bougia Labs
Why the Lab publishes
The Lab exists to test what our deployment work keeps running into. This note explains what we will publish here, and the standard each note has to meet.
Read moreWe share work when it is clear enough to be useful, and welcome thoughtful questions along the way.