How I Fixed My Messy Technical Research Workflow

Description and use

The author created a structured research process that starts with a specific question, captures evidence, separates facts from interpretation, and ends with actionable outputs, speeding up decision‑making and making information easier to retrieve.

Problem

Research notes were cluttered with many open tabs and a document full of copied links, making it hard to recall why a page mattered or which video explained a specific trade‑off.

Outcome

The workflow reduced the time spent on research by preventing loss of reasoning between reading and deciding, and produced clearer, actionable outputs.

Workflow

• 1. Start with a specific question
• 2. Capture evidence only: Source, Useful finding, Why it matters, Confidence or limitation
• 3. Separate extraction from judgment: record source statement then add interpretation
• 4. End with an output such as a decision table, recommendation, or list of open questions

Evidence

The workflow becomes harder when information is spread across API docs, PDFs, screenshots, and conference videos. Manual notes still work, but switching formats adds friction.

Source

I tested an AI workspace for documents and videos called iWeaver for this part of the process.

Source