The AI Literature Review Workflow
Research Topic β You start with your research question, however broad or narrow.
AI Super Prompt β ChatGPT transforms your topic into an optimised prompt that guides the AI agent toward comprehensive results.
Structured Literature Synthesis β Edison Scientific's Falcon returns a full literature review draft with ranked references and search queries, typically within 20β30 minutes.
Seed Paper Extraction β You pull the highest-quality papers, Boolean search strings, keywords, and theoretical frameworks from the AI output.
Citation Mapping β Research Rabbit runs forward, backward, and lateral searches from your seed papers β surfacing work that keyword searches alone miss.
Research Database β Every paper is processed through NotebookLM and entered into the pre-built Notion template β a living, searchable database of your entire landscape.
Comparative Analysis β Notion AI compares findings across 30β50 papers, maps contradictions, and surfaces genuine research gaps.
Structured First Draft β Your database generates the first draft of each section β grounded in your own notes, your critical judgments, and proper citations.
You already know the problem.
If you are here, you have probably experienced some version of this:
Random keyword searches that go nowhere.
PDFs piling up without a system.
Re-reading papers you have already processed.
A quiet worry that you might have missed something important.
The traditional approach works.
Eventually.
But it is slow, scattered, and stressful.
Which means you spend weeks building a literature base you cannot fully trust.
Which means the research gap you identified might not hold up β and you would not know until it is too late.
This is a systems problem.
And this course gives you the system.
Before vs. After
What the course covers
Everything inside the course.
| Component | What It Includes | Why It Matters |
|---|---|---|
| 5 Modules | Full literature review process β fundamentals through final writing | Complete end-to-end system, not disconnected tips |
| 35+ Video Lessons | ~3 hours of focused instruction, no filler | Learn the full workflow in a single focused day |
| AI Prompt Library | Every prompt used in the course, copy-paste ready | Skip the trial and error β use tested, optimised prompts |
| Notion Template | Pre-built literature tracker with automated fields, reading timelines, keyword filtering | Your database builds itself as you work β organise 100+ sources clearly |
| Workflow Guides | Step-by-step sequences across ChatGPT, Edison Scientific, Research Rabbit, NotebookLM, Notion AI | Know exactly which tool to use, when, and how they connect |
| Pre-Submission Checklist | Structure, citations, academic tone, plagiarism checks | Submit with confidence, not anxiety |
| Lifetime Access | All current and future updates | Use the system for every literature review in your career |
Here is what you can realistically expect.
No inflated claims. These are conservative estimates based on the workflow design:
Reduce initial search and organisation time by 40β70% β by starting with an AI-generated synthesis instead of blank keyword searches.
Process 2β3x more papers per week β using NotebookLM's structured extraction instead of manual reading and annotation.
Compare 30β50 papers in a single analysis session β using Notion AI comparative prompts across your full database.
Organise 100+ sources without losing track β using the pre-built Notion template with automated filtering, timelines, and fields.
The exact results depend on your discipline, your existing skills, and how thoroughly you implement the system. But the workflow is designed to eliminate the biggest bottlenecks in the traditional approach.
Why I built this
AYNUR ATALAY
Chemical Engineering PhD Candidate
Who this is NOT for.
Students who want AI to write their thesis. This teaches AI as a research assistant, not a ghostwriter. You still read, evaluate, and synthesise.
Researchers unwilling to engage with papers. The system makes reading faster and more targeted. It does not eliminate reading.
Undergraduates writing short essays. This is built for postgraduate-level reviews requiring systematic coverage across dozens or hundreds of papers.
Researchers who prefer fully manual workflows. If you have a working system and no interest in AI tools, this course is not trying to convince you otherwise.
Common questions
No. AI helps you find, organise, and analyse literature. You provide the critical thinking and synthesis. The course specifically teaches ethical usage and maintains academic integrity.
The course focuses on research assistance β finding papers, reading comprehension, note organisation, pattern recognition β not generating original claims. This distinction is built into every workflow.
Every core tool is free. Edison Scientific's Falcon, Research Rabbit, NotebookLM, Notion (Education plan), ChatGPT (free tier). No student is priced out.
Module 1 can be skipped. Modules 2β5 improve the process even mid-review. Many researchers reorganise existing work with these tools and save considerable time.
The tools are public. The integrated workflow is not β the prompt sequences, the system connecting tools, the Notion template, the prompt library, the structured progression from search to submission. System, not playlist.
The AI Literature
Review Workflow
You already know the problem
If you are here, you have probably experienced some version of this:
Random keyword searches that go nowhere.
PDFs piling up without a system.
Re-reading papers you have already processed.
A quiet worry that you might have missed something important.
The traditional approach works.
Eventually.
But it is slow, scattered, and stressful.
Which means you spend weeks building a literature base you cannot fully trust.
Which means the research gap you identified might not hold up β and you would not know until it is too late.
This is a systems problem.
And this course gives you the system.
Before vs. After
4β8 weeks of scattered searching
Under 1 hour with AI-generated synthesis
Keyword guessing, repeated with different terms
AI-generated starting point followed by targeted expansion
Folders of PDFs, scattered highlights, notes in multiple apps
Centralised Notion research database with automated tracking, filtering, and structured fields
Manual reading and forgotten highlights
AI-assisted extraction via NotebookLM β key contributions, methods, and limitations in minutes
Uncertain research gap
Data-driven: comparative analysis across 30+ papers reveals patterns and contradictions
"I think I covered everything"
"I have a verified, systematic record of my entire research landscape"
Really admire how you break down complex topics without oversimplifying them. This kind of content makes academic learning feel accessible. Would love to see more formats like this.
I thought that I can't do research anymore but after watching your video I realized that it's not difficult β€
I started to use NotebookLM after exploring that in your video. It's amazing for gap detection as you mentioned.
Thank you for taking the time to make this video and help other students! It's not only super informative but very aesthetic! Really appreciate people like you for taking the time to make this information readily available.
Pricing
That is months of your time spent on a problem that a structured system can substantially reduce.
- βLess than a single textbook
- βLess than one month of a reference manager subscription
- βLess than one hour of private academic coaching
What the course covers
Everything inside the course.
| Component | What It Includes | Why It Matters |
|---|---|---|
| 5 Modules | Full literature review process β fundamentals through final writing | Complete end-to-end system, not disconnected tips |
| 35+ Video Lessons | ~3 hours of focused instruction, no filler | Learn the full workflow in a single focused day |
| AI Prompt Library | Every prompt used in the course, copy-paste ready | Skip the trial and error β use tested, optimised prompts |
| Notion Template | Pre-built literature tracker with automated fields, reading timelines, keyword filtering | Your database builds itself as you work β organise 100+ sources clearly |
| Workflow Guides | Step-by-step sequences across ChatGPT, Edison Scientific, Research Rabbit, NotebookLM, Notion AI | Know exactly which tool to use, when, and how they connect |
| Pre-Submission Checklist | Structure, citations, academic tone, plagiarism checks | Submit with confidence, not anxiety |
| Lifetime Access | All current and future updates | Use the system for every literature review in your career |
Here is what you can
realistically expect.
No inflated claims. These are conservative estimates based on the workflow design:
Reduce initial search and organisation time by 40β70% β by starting with an AI-generated synthesis instead of blank keyword searches.
Process 2β3x more papers per week β using NotebookLM's structured extraction instead of manual reading and annotation.
Compare 30β50 papers in a single analysis session β using Notion AI comparative prompts across your full database.
Organise 100+ sources without losing track β using the pre-built Notion template with automated filtering, timelines, and fields.
The exact results depend on your discipline, your existing skills, and how thoroughly you implement the system. But the workflow is designed to eliminate the biggest bottlenecks in the traditional approach.
This really changed how I go about my literature review and I got this tip from you. So thanks :)
Thank you so much! I just started using this tool and your videos are quite helpful. Never hit the subscribe button faster π
Thank you for saving me out of my endless google doc subtabs rabbit hole π
The Guarantee
No forms. No hoops.
Why I built this
AYNUR ATALAY
Chemical Engineering PhD Candidate
Who this is NOT for
Students who want AI to write their thesis. This teaches AI as a research assistant, not a ghostwriter. You still read, evaluate, and synthesise.
Researchers unwilling to engage with papers. The system makes reading faster and more targeted. It does not eliminate reading.
Undergraduates writing short essays. This is built for postgraduate-level reviews requiring systematic coverage across dozens or hundreds of papers.
Researchers who prefer fully manual workflows. If you have a working system and no interest in AI tools, this course is not trying to convince you otherwise.
Common questions
No. AI helps you find, organise, and analyse literature. You provide the critical thinking and synthesis. The course specifically teaches ethical usage and maintains academic integrity.
The course focuses on research assistance β finding papers, reading comprehension, note organisation, pattern recognition β not generating original claims. This distinction is built into every workflow.
Every core tool is free. Edison Scientific's Falcon, Research Rabbit, NotebookLM, Notion (Education plan), ChatGPT (free tier). No student is priced out.
Module 1 can be skipped. Modules 2β5 improve the process even mid-review. Many researchers reorganise existing work with these tools and save considerable time.
The tools are public. The integrated workflow is not β the prompt sequences, the system connecting tools, the Notion template, the prompt library, the structured progression from search to submission. System, not playlist.
Pricing
That is months of your time spent on a problem that a structured system can substantially reduce.
- βLess than a single textbook
- βLess than one month of a reference manager subscription
- βLess than one hour of private academic coaching
The Guarantee
No forms. No hoops.
