AI & Code

Claude Code, Codex, and similar agentic coding tools are most useful when thesis work becomes file-based: sources in folders, metadata in spreadsheets, scripts that need to run, outputs that need checking, and methods that need documentation. Use them to make the workflow more explicit and reproducible. Do not use them to outsource judgment, interpretation, or final claims.

Choose a Workflow

Starter Prompts

Use these as starting points. Replace bracketed text with your actual project details.

I am writing a thesis on [topic]. Help me set up a transparent research folder for sources, metadata, notes, scripts, outputs, and documentation. Suggest a folder structure, file naming convention, and metadata columns. Do not analyze the sources yet. Focus on organization and reproducibility.

I have [number/type] source files about [topic] from [source/database] covering [date range]. Help me design a corpus-building workflow. I need inclusion/exclusion rules, metadata fields, file organization, quality checks, and a short methods note explaining the workflow. Ask clarifying questions before proposing scripts.

Inspect this script as a research workflow, not just as code. Explain what each step does, identify assumptions, list possible failure points, and suggest validation checks. Do not change the analytical logic unless you explain why.

Help me draft a transparent methods note describing how AI/code tools supported my workflow. Include what the tool helped with, what I checked manually, what I did not delegate, and where scripts or prompts are stored. Keep the wording factual and concise.

Responsible Use Checklist

Before you rely on an AI/code-assisted workflow, make sure you can answer all of the following:

• Can you explain what the tool did and why that step was appropriate?
• Are prompts, scripts, outputs, and manual corrections stored somewhere you can revisit?
• Did you verify a sample of outputs against the original sources?
• Are corpus boundaries, exclusions, and transformations documented?
• Is the final interpretation yours, grounded in evidence you checked?
• Have you discussed the planned use with your supervisor and followed the relevant Ethics & AI policy for permission, disclosure, and academic integrity?

Good Division of Labor

The standard is simple: if the work shapes the argument, you must understand and defend it. If the work is repetitive, procedural, or technical, the tool can help, but you still verify the result.

Where To Go Next