Lesson 272 of 2116
Running a Literature Review With AI
AI turns weeks of literature review into days — if you know how to use it. Here is a workflow that actually works.
Lesson map
What this lesson covers
Learning path
The main moves in order
- 1From Weeks to Days
- 2literature review
- 3research workflow
- 4Perplexity
Concept cluster
Terms to connect while reading
Section 1
From Weeks to Days
A traditional literature review on a narrow AI topic takes weeks of reading abstracts, taking notes, and chasing citations. With AI tools, the same scope can happen in days — if you use the tools critically and never let them do your thinking for you.
A four-stage workflow
- 1Frame: write one sentence defining what you want to learn
- 2Harvest: use Semantic Scholar, Elicit, or Perplexity to surface 30-80 candidate papers
- 3Filter: skim abstracts manually — AI cannot judge relevance to your specific question yet
- 4Read and synthesize: batch-read with Claude or NotebookLM, then write your own summary
Tools and what each is good at
Compare the options
| Tool | Strength | Limit |
|---|---|---|
| Semantic Scholar | Citation graph, authoritative metadata | Raw — requires filtering |
| Elicit | Structured Q&A over papers | Narrow subset, paid tier for scale |
| Perplexity | Live web synthesis with citations | Mixes papers, blogs, news indiscriminately |
| NotebookLM | Grounded Q&A over your uploaded PDFs | Cannot pull from the open web |
| Claude / GPT | Deep reading of individual papers | Slow one-at-a-time, hallucination risk |
The note-taking layer
- One file per paper (slug-case-title.md)
- Top of file: one-sentence summary and main claim
- List of surprising findings
- Limitations you noticed
- Questions for further investigation
- Links to related papers in your pile
“Reading is like coding — you can have a friend pair with you, but you still have to understand what runs.”
Key terms in this lesson
The big idea: AI accelerates literature review but does not replace the thinking. Use it as a pair, not a proxy.
End-of-lesson quiz
Check what stuck
15 questions · Score saves to your progress.
Tutor
Curious about “Running a Literature Review With AI”?
Ask anything about this lesson. I’ll answer using just what you’re reading — short, friendly, grounded.
Progress saved locally in this browser. Sign in to sync across devices.
Related lessons
Keep going
Creators · 45 min
Open vs. Closed Models: Philosophy and Strategy
Open-source AI is both a technical movement and a political one. Understand the arguments so you can pick a stack and defend it.
Creators · 38 min
Elicit: The AI Research Assistant For Systematic Reviews
Elicit automates slow parts of academic research: finding papers, extracting data, building literature matrices. Look at what it saves PhDs 20 hours a week.
Creators · 38 min
Building a Personal AI Stack for School and Career
Assemble the four or five AI tools that actually belong in your daily life. A tested template for the stack that earns its keep.