---
canonical: "https://yuanhaochen.dev/notes/ai-native-research-workflows"
path: "/notes/ai-native-research-workflows"
section: "Notes"
title: "AI-native research workflows: from a question to an evidence-linked memo"
language: "en"
agentUse: "summary, retrieval, citation, hiring evaluation"
---

# AI-native research workflows: from a question to an evidence-linked memo

How a research memo should preserve source state, uncertainty, and judgment shifts instead of collapsing evidence into a polished answer too early.

The pressure

The interesting question is no longer whether AI can summarize a pile of sources. The harder question is whether a serious reader can see which source changed the answer, which uncertainty survived, and which part of the memo is still a claim instead of evidence.

Most AI research workflows still collapse the work into a polished paragraph too early. That makes the output easier to forward, but weaker to challenge.

The shape I trust

A useful memo should keep the question, source trail, judgment shifts, and objection path close together. The reader should not have to guess whether a sentence came from a source, a model synthesis, or my own interpretation.

The workflow I want to test is simple: start with one decision pressure, attach the sources that actually moved the reasoning, write the memo around the changed judgment, and leave the next challenge visible.

What I would inspect next

I would inspect tools that make source state and uncertainty visible without turning the whole workflow into compliance theater. The important test is whether a reader can disagree with the memo faster because the evidence is still attached.