AI safety research institutes
An independent strategic perspective for research, evaluation design, and adversarial exploration.
AI safety · Strategic red teaming
Grandmaster Labs brings elite strategic thinkers into AI safety research to challenge assumptions, pressure-test evaluations, and uncover failure modes that conventional approaches may miss.
Chess masters spend their lives asking one question:
What is the other side going to do that I haven’t considered?
We bring that mindset to AI.
Grandmaster Labs is designed to supplement existing evaluations, red teams, and research programs — not replace them.
An independent strategic perspective for research, evaluation design, and adversarial exploration.
An additional adversarial layer for testing models, evaluations, and safety assumptions.
Strategic thinkers who can pressure-test the red team itself — and challenge evaluation frameworks from another angle.
AI safety teams already have researchers, engineers, evaluators, and traditional red teams.
Grandmaster Labs adds another perspective.
Elite chess players are trained to model an opponent. They search for hidden resources, unexpected moves, and weaknesses in a position that initially appears sound. They think several moves ahead while actively trying to defeat the strategy in front of them.
We work with research organizations and frontier labs to test whether that capability can contribute something useful to AI safety — as an additional layer inside existing methodology.
Can elite strategic thinkers identify important AI failure modes that conventional evaluation misses?
That is the question at the center of our work.
Red-team the red team.
AI safety teams already use evaluations, red teams, interpretability, adversarial testing, and other approaches. Grandmaster Labs is designed to complement those efforts.
The purpose isn’t to replace existing methods. It’s to add another way of looking for what they might miss.
What would I do if I wanted to defeat this system?
What assumption would I attack first?
What possibility are we not considering?
What might a strategically capable model see that we don’t?
We work with research teams and frontier labs on red-team exercises, evaluations, scenario analysis, and pressure-testing assumptions — as an additional layer inside existing methodology.
Independent pressure on plans, evaluations, and governance designs from people practiced at finding the move others miss.
Structured premortems and multi-path scenario work designed to surface high-stakes trajectories while they are still tractable.
Sessions and briefs built to sit beside existing safety programs — clear enough for a safety lead or research director to use without translation.
A short conversation to define the question, the constraints, and who owns the decision. We agree on the failure modes worth pressure-testing and what “done” looks like. If the problem, timing, or standard of rigor is not a fit, we say so.
Define the question. Agree what “done” looks like.
We put the plan, assumption, or governance design under adversarial review. That can be a live working session with your team, structured premortem work, or both. The point is not to win the argument. It is to find the line your own process is likely to miss.
Adversarial review — find the line the process will miss.
You leave with a short written product: the failure trajectories we see, where the reasoning is thin, and what we would test next. Clear enough for a safety lead or research director to use without translation.
A brief your team can use without translation.
Short pieces on method, risk, and why this work exists. Not a blog — working notes for people already taking the problem seriously.
Give your safety process another perspective.
Grandmaster Labs works with researchers, safety teams, and frontier labs to explore what elite strategic reasoning can add to the search for failure modes. As AI systems become more capable, independent perspectives from external evaluators grow more valuable — not less.
