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Researcher Profile

Robert Lasenby

Alignment via AI feedback (Constitutional AI)

Co-author, Constitutional AI

Co-authored Constitutional AI: Harmlessness from AI Feedback.

Labs

Anthropic

Topics

Post-Training & Alignment Reinforcement Learning

About This Page

This profile is meant to help you get oriented quickly: why this researcher matters, what to read first, and where to explore next.

Last updated

March 20, 2026

Best First Clicks

Constitutional AI: Harmlessness from AI Feedbackpaper Training a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedbackpaper

Known For

The ideas, systems, and research directions that make this person worth knowing.

Alignment via AI feedback (Constitutional AI)

Constitutional AI: Harmlessness from AI Feedback

Training a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedback

Anthropic

Constitutional AI

Alignment

Start Here

Canonical papers, project pages, or repositories that anchor this profile.

Constitutional AI: Harmlessness from AI Feedbackpaper Training a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedbackpaper

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Start HereTraining a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedback

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Worth following for the evaluation side of Anthropic’s alignment program, especially where model-written tests and public-input methods become practical tooling rather than just ideas.

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Start HereTraining a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedback

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One of the clearest people to follow if you care about scaling laws, training efficiency, and the systems choices that quietly shape frontier-model progress.

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Start HereRahul Patil joins Anthropic as Chief Technology Officer

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Important for understanding how Anthropic’s assistant-training stack evolved from early RLHF into Constitutional AI and later robustness work around jailbreaks and behavior control.

Anthropic Post-Training & Alignment Reinforcement Learning

Start HereTraining a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedback

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Saurav Kadavath

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A good person to follow for the part of alignment work that becomes concrete measurement: model-written tests, chain-of-thought faithfulness, and behavior-shaping methods that can actually be audited.

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Start HereDiscovering Language Model Behaviors with Model-Written Evaluations

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Sandipan Kundu

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Useful for the attack-and-evaluation side of alignment work, especially long-context jailbreak research and the measurement work that turns safety concerns into concrete tests.

Anthropic Post-Training & Alignment Evaluation & Benchmarks

Start HereMany-shot Jailbreaking