ToolExperiment

Research Workflow Automation

An experimental AI-assisted workflow for turning papers, notes, and experiments into structured research logs and technical outputs.

LLM WorkflowsResearch OpsToolingKnowledge Systems

Problem

Research creates scattered artifacts: papers, notes, equations, code, plots, meeting comments, and experiment logs. The hard part is turning fragmented information into structured understanding and reusable output.

Approach

This project explores a workflow that helps convert research inputs into structured, reusable outputs:

Paper summaries
Concept maps
Experiment logs
Next-action lists
Draft technical notes
Research questions

Output

Obsidian-style templates
LLM-assisted summarisation workflow
Research log structure
Paper-to-experiment pipeline
Technical writing prompts

Commercial angle

A refined version could become useful for PhD students, research teams, technical consultants, R&D groups, and deeptech founders.

Next steps

Build personal MVP
Test on 10 papers
Compare manual vs assisted workflow
Share template publicly

Proof artifacts

Paper-to-experiment template

Next to publish

A reusable note structure for converting a paper into claims, assumptions, implementation hooks, and concrete experiment candidates.

Ten-paper workflow test

Planned

A small evaluation of the workflow across ten papers, comparing manual notes against assisted extraction and follow-up quality.

Research log schema

Drafting

A structured log format for preserving experiment context, decisions, plots, and next actions without scattering them across tools.

This is an in-progress research project. Status, methods, and results are exploratory and will be updated as the work develops.