Research automation
Agents and pipelines that run parts of the research workflow, from data pull to replication.
Topics
The beats we track. Each one has its own page and is checked on every sweep.
LLM methods
Text as data, embeddings, prompting and fine-tuning in empirical work, and the validity problems that come with them.
Stack
Which services to use and what they cost: model access, rented GPUs, coding agents and the pipeline around them.
Models and tools
Model and tool releases that change what a researcher can do.
Data and vendors
Datasets, research platforms and the AI features vendors are shipping.
International data
Markets outside the US, cross-country datasets and multilingual text.
Global research
Research, policy and adoption outside the US.
Accreditation and credentials
AACSB and other accreditors, curriculum changes, and the credentials students are being asked for.
Journals and peer review
Journal AI policies, disclosure rules, refereeing and replication.
Industry
What asset managers, banks and vendors are doing with AI in research roles.