AI agent use cases for researchers
How researchers put AI agents to work: real deployments with the results they reported, and recipes you can try. Every example links to its source.
Run LangChain's Open Deep Research multi-agent pipeline locally
LangChain's open-source deep research agent, built on LangGraph, runs research sub-agents in parallel, compresses what they find and writes a final report. It works with many mode…
On Deep Research Bench, the default GPT-4.1 configuration scored 0.4309 and the GPT-5 configuration 0.4943.
Cursor's planner-worker agents built a web browser from scratch in about a week
Cursor tested long-running autonomous coding with a hierarchy of planner agents that create tasks and worker agents that just complete them. The headline project was a browser eng…
The agents ran for close to a week, writing over 1 million lines of code across 1,000 files.
16 parallel Claude agents wrote a C compiler that builds the Linux kernel
An Anthropic researcher ran a team of Claude agents in a loop on a shared repository to write a Rust-based C compiler from scratch. The write-up and the code are both public.
Over nearly 2,000 Claude Code sessions and $20,000 in API costs, the agents produced a 100,000-line compiler.
How Oxford PharmaGenesis ran a 500-paper literature review in a week with Elicit
Health-science communications consultancy Oxford PharmaGenesis used Elicit for screening, data extraction and reporting in literature reviews, with experts checking the results. E…
Elicit reports answering 40 research questions across 500 papers in under a week.
How NBIM rolled out Claude to investment and compliance staff
NBIM, which manages Norway's sovereign wealth fund, deployed Claude across investment research, ESG analysis, compliance and data operations. Anthropic reports weekly time savings…
According to Anthropic, employees save 20% of their week on the analytical and operational work they now do with Claude.
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Where these examples come from
Every example links to its source: a company's own engineering blog, a vendor's customer story, official documentation or a public write-up. AgentGid writes the summary; the figures under “Results” are quoted from the source as it reports them, and most customer stories are published by the vendor of the tool, so read them as the vendor's claims. Recipes follow the official docs at the time we checked them; tools change quickly, so the linked docs are the reference.
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