Use AI to map a thesis literature review
They used ChatGPT to summarize papers and sketch the review, then switched to a source-first tool to cut citation risk.
- What they did
- A writer working on an early thesis literature review asked ChatGPT to turn papers into short summaries and to help organize the section. After seeing that it could produce citations that looked real but were wrong or made up, they began testing Literfy AI, which starts with actual academic papers and then writes from those sources.
- How it went
- The main benefit was less strain and more confidence that the references were real. They did not report any hard time savings and said the process was still early, so they did not fully trust the AI.
- Tips
- For this kind of task, treat any generated reference as something to verify yourself. A source-first workflow is safer when citation accuracy matters.
Try it yourself with ChatGPT Agent
I’m drafting a thesis literature review on [topic]. Find real academic papers about [subtopic 1], [subtopic 2], and [subtopic 3]. For each paper, give a brief summary, explain how it relates to the topic, and group the findings into a clear review outline. Include a link, DOI, or other checkable source detail for every citation. Before you move on to anything that would change my draft or submit work, stop and ask for my approval.
Fill in the [brackets]. Agents can make mistakes, so review anything before it is sent, paid or deleted.
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