Claude can now break down papers like an MIT researcher.
Here are 10 insane Claude prompts that turn dense research papers into simple summaries, diagrams, limitations, experiments, and future research ideas in minutes (Save this)
1. The Feynman Breakdown
"Read this paper and explain it like you're teaching a curious 12-year-old. Use everyday analogies. No jargon. If a term is unavoidable, define it in 5 words or less. End with: what would surprise a non-expert most?"
Turns 40 pages into 4 paragraphs.
2. The 5-Layer Summary
"Give me 5 versions of this paper:
→ One sentence
→ One paragraph
→ One page
→ Technical abstract
→ Tweet thread (10 tweets)
ChatGPT can now build courses like a Stanford professor.
Here are 11 insane ChatGPT prompts that turn any skill into a 30-day curriculum, lesson plans, exercises, projects, and grading rubrics in minutes (Save this)
1/ The 30-Day Curriculum Builder
Prompt:
"I want to learn [SKILL] in 30 days.
Build me a complete 30-day curriculum.
Structure it like a top university course.
For each day, include:
- Main concept
- What I should study
- Practice task
- Output I should create
- Common mistakes
- 20-minute review exercise
Assume I am starting from [BEGINNER / INTERMEDIATE / ADVANCED] level."
This gives you the full roadmap before you even start.
Most people fail because they learn randomly.
This turns the skill into a clear path.
2/ The Skill Deconstruction Prompt
Prompt:
"Break down [SKILL] into its smallest learnable parts.
Separate everything into: 1. Core fundamentals 2. Supporting concepts 3. Tools I need 4. Mental models 5. Practice drills 6. Real-world projects 7. Advanced topics
Then show me the exact order I should learn them in."
This is insane for removing confusion.
Instead of asking “where do I start?” you get the entire skill map in one place.
Claude can now research like a Stanford PhD student.
Here are 9 insane Claude prompts that turn 40+ research papers into structured literature reviews, knowledge maps, and research gaps in minutes (Save this)
PROMPT 1 - The Intake Protocol
Use this when you first upload your papers:
"I'm going to share [X] papers on [topic].
Before I ask anything, do this:
1. List every paper by author + year + core claim in one sentence 2. Group them into clusters of shared assumptions 3. Flag any paper that contradicts another
Don't summarize. Map the landscape."
PROMPT 2 - The Contradiction Finder
Most researchers miss this. This prompt doesn't:
"Across all papers uploaded, identify every point where two
or more authors directly contradict each other.
For each contradiction:
- State both positions
- Name the papers
- Explain WHY they likely disagree (methodology, dataset, era)
Top senior engineers don't read legacy codebases line by line anymore.
They point Claude Code at the repo and run a 6-command workflow that maps the architecture, surfaces hidden dependencies, and identifies the 10 riskiest files in under an hour.
Here are the exact commands they use: 👇
1. The Architecture Map
First command on any unfamiliar repo:
"Read the entire repository. Then produce:
1. One paragraph describing what this application does in plain English 2. The architectural pattern (MVC, hexagonal, event-driven, microservices, monolith, etc) 3. A text-based diagram of the main components and how they talk to each other 4. The tech stack with versions 5. The 3 entry points I should read first to understand the core flow
Don't suggest changes. Just orient me."
This replaces the first 4 hours of onboarding.
2. The Dependency Graph
Once you know the shape of the codebase:
"Map the dependencies in this repo.
1. List every external package and what it's used for 2. Identify internal modules that other modules depend on heavily (the 'core' files) 3. Flag any circular dependencies 4. Identify any dependencies that are outdated, abandoned, or have known security issues 5. Show me the 5 files with the most incoming imports — these are the files I cannot break
Rank by blast radius: if I change this file, how many others break?"
This surfaces the landmines before you step on them.
Top students at Stanford don't read books cover to cover anymore.
They upload the PDF to NotebookLM and run a 6-prompt workflow that extracts the core arguments, counterexamples, and real-world applications in one sitting.
Here are the exact prompts they use:
1. The Core Argument Extractor
Every book has one central argument everything else serves.
Most readers finish the whole thing and can't state it in two sentences.
Paste this first:
"Read this entire book and identify the single central argument the author is making. Not the topic. The argument the specific claim they are trying to convince me is true. State it in two sentences maximum. Then identify the 3 to 5 key sub-arguments that support the central claim. For each sub-argument: what evidence or reasoning does the author use to support it, and how strong is that evidence on a scale of anecdote to empirical proof?"
If you can't state a book's central argument in two sentences after finishing it, you haven't finished it.
You've just been present for it.
This prompt makes sure you actually have it.
2. The Assumption Auditor
Every author has a worldview baked into every book they write.
Most of those assumptions are never stated because the author doesn't realize they're making them.
They feel like facts because they feel obvious to the person writing.
"Identify every significant assumption this author makes that they never explicitly state or defend. What does the author take for granted about human nature, about how organizations work, about what people want, about how change happens? For each unstated assumption: is it well-supported by evidence outside this book, is it contested by credible thinkers in related fields, or is it simply the author's worldview presented as universal truth? Which assumption, if wrong, would most undermine the book's central argument?"
The best books survive this prompt with most of their argument intact.
The overrated ones collapse at assumption two or three.
Running this tells you exactly how much of what you just read was insight versus ideology.