







This paper is a perspective from Lightcone Research, an open-source initiative building tooling for scientific research in the age of agentic AI.
Lightcone Research
An open ecosystem for inspectable, composable, and referenceable scientific research in the age of agentic AI.


AI for science needs reasoning, not just data
AI agents that can model the human process of research will accelerate discoveries in science.

AI Scientists as Engines of Discovery: A Case for Development within Reformed Institutions
Agentic artificial intelligence (AI) systems are beginning to assist, accelerate, and partially automate scientific discovery, performing tasks that span literature synthesis, code generation, data analysis, hypothesis proposal, and model criticism. We argue that this transition is qualitative rather than incremental, and that suitably designed multi-agent systems may evolve from passive computational tools into ``AI scientists'' that can expand the hypothesis-generating and verification capacity of science. Such systems must be developed and deployed within a scientific ecosystem fit for purpose: institutions must be redesigned for verification, accountability, interpretability, and dual-use safety. We sketch how multi-agent architectures, illustrated by the prototype framework \textit{Denario}, accelerate the discovery cycle and traverse model spaces beyond human reach; examine what this implies for authorship, peer review, and the enduring role of human scientists; and close with recommendations for governing AI as an epistemic actor rather than a mere instrument.

OpenScience.ai — Autonomous AI Research Agents
AI agents conducting reproducible scientific inquiry. Full provenance, executable notebooks, peer validation.

Human scientists trounce the best AI agents on complex tasks
State-of-the-industry report finds that, despite the limitations of artificial-intelligence systems, researchers have embraced them.

Agent4Science
A social network for AI scientists — where agents share, debate, and discuss research papers.

How to build an AI scientist: first peer-reviewed paper spills the secrets
AI Scientist, an autonomous research tool, first released in 2024, has now undergone peer review, highlighting its strengths and limitations.

Deep Research, information vs. insight, and the nature of science
What AI will accelerate in the scientific process, what it cannot do, and how we can prepare for new manners of scientific investigation.

I don’t think we are close to “AI scientists”
Today's AI agents are not designed to extract deep insights from new observations.

OpenScience | Open-source AI co-scientist for research
OpenScience is the open-source AI co-scientist. Free models included or connect any model from any provider, including Claude, GPT, Gemini and more.

AI Research Agents Narrow Scientific Exploration
AI research agents now support large-scale AI-assisted scientific discovery. We examine whether AI-generated ideas broaden scientific exploration or primarily reinforce existing work. Using five agent frameworks and five large language models, we generate 219,655 ideas for different scientific fields. Across experiments, four consistent patterns emerge. First, AI-generated ideas are more concentrated than human-authored papers within the same research area. Second, they remain much closer to starting literature than later human follow-on work does. Third, AI-generated ideas align less with future human research. Last, AI-generated ideas are located in lower-impact regions of the historical scientific landscape. Overall, current AI research agents appear better suited to local elaboration than to broadening scientific exploration.

Which ‘AI scientist’ suits your lab? A guide for the perplexed
General-purpose AI tools for science, such as Claude Science, promise to accelerate research. But which is right for you?

AI agents team up in Agent Laboratory to speed scientific research
Johns Hopkins University and AMD have developed Agent Laboratory, a new open-source framework that pairs human creativity with AI-powered workflows.

AI Research Evaluation: Negative Findings and Failure Modes | Arvind Narayanan posted on the topic | LinkedIn
📢 New paper: Forecasts of explosive AI progress hinge on AI agents automating AI research. But most evaluations of agents conducting AI research focus on narrow, verifiable tasks. Can AI agents… | Sayash Kapoor
My claude is constantly wanting to 'A/B test' things instead of actually just doing the thing I told her to do, and constantly wants to fall…
A snapshot of research into answering if frontier AI agents can run R&D into AI (which not surprisingly failed apart from "minor findings…
This is definitely my feeling working with them on recommendation algorithm.
"This paper prompted Jack Clark, one of the co-founders of Anthropic to post this to their news letter: 'the singularity could be delayed'".

Agency and Agents
ГАЛЬВАНИЗАЦИЯ АВТОРА, ИЛИ ЭКСПЕРИМЕНТ С НЕЙРОННОЙ ПОЭЗИЕЙ. Борис Орехов. «Новый мир» №6, 2018

Personal Online RL | 🌱 | Offprint
Approaching an unknown communication system by latent space exploration and causal inference | Royal Society Open Science | The Royal Society

Surya Narreddi

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