We're a Cambridge, UK-based AI safety organisation that's asking: how can we build the most robust alignment initialisations for capable LLMs?

We’re one of the few non-profit organisations positioned to answer this question empirically. We have the engineering experience, and now the compute, to conduct data intensive interventions across the model training pipeline. This post lays out our research agenda and theory of change, and what we are looking for in technical hires. Applications are open here.

Research agenda

TLDR: Long-horizon capabilities RL may be the most critical source of misalignment. Misalignment instilled during capabilities RL may be difficult to remove afterwards. Geodesic Research's mission is to develop the science of providing robustly-aligned initialisations for RL, where alignment priors persist through the remainder of training.

Our seminal work on alignment pretraining showed that you can bake alignment priors into base models. Frontier labs are now using these techniques in production: for example, Anthropic's recent work heavily leans on improving alignment priors. But it's clear that, in the face of production post-training, alignment pretraining is not a one-size-fits-all solution. So now, we are framing pre- and midtraining interventions within the rest of the model training stack.

The evidence points towards [...]

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Outline:

(00:44) Research agenda

(03:56) Theory of Change

(05:10) The team

(06:35) FAQs

(08:56) Acknowledgements

The original text contained 5 footnotes which were omitted from this narration.

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First published:
May 27th, 2026

Source:
https://www.lesswrong.com/posts/xBbYGer8w45kxkaWr/announcing-geodesic-research

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Narrated by TYPE III AUDIO.

“Announcing Geodesic Research” by Puria, Cam, Alexandra Narin, Edward James Young, Kyle O’Brien

LessWrong (30+ Karma)

“Announcing Geodesic Research” by Puria, Cam, Alexandra Narin, Edward James Young, Kyle O’Brien