AI-native workflow

Adrasteia supports economic paper writing through structured assumption search.

The workflow is based on a preliminary, under-review manuscript about human-in-the-loop agentic research for theory-oriented economics. It is presented here as a project overview rather than as a public manuscript release.

Its purpose is not to automate paper writing end to end. Instead, it helps researchers turn early ideas into inspectable models, branch across alternative assumptions, revise arguments under internal checks, and prepare drafts for referee-style scrutiny.

How it helps economic paper writing

  • Sharper research questions
  • More defensible assumptions
  • Traceable assumption-to-conclusion chains
  • Drafts that better survive reviewer-style criticism
01

Problem framing

Translate a phenomenon, mechanism intuition, or target claim into a research object with clear scope.

02

Assumption proposal

Generate candidate assumption packages and model branches that can support a disciplined economic argument.

03

Internal verification

Check logic, derivations, literature fit, boundary conditions, and whether conclusions outrun assumptions.

04

Revision and branching

Weaken claims, substitute mechanisms, refine assumptions, and preserve promising alternatives for comparison.

05

Human adjudication

Let the researcher select, prune, or retain branches based on originality, taste, and scholarly accountability.

06

Simulated reviewer validation

Expose draft research objects to referee-style critique, then convert feedback into structured revision targets.

Active

Adrasteia: AI Agent Workflow for Economic Paper Writing

Accepted at the ICML 2026 Workshop on Human-AI Co-Creativity. A human-in-the-loop agentic workflow for moving economic research from an initial question to defensible assumptions, model structure, argument revision, and referee-style critique.

Team: Heikichi Hayashi

ICML 2026 WorkshopHuman-AI co-creativityAI for economic researchAgentic workflow

Design

The Elite School Custodianship Effect

A work-in-progress project on the impact of super high school group-based schooling on students' human capital, developed in collaboration with Beijing National Day School.

Team: Heikichi Hayashi

EducationHuman capitalWork in progress