$20 That Saves You Weeks of PhD Work – AI Tools Worth Paying For

Andy StapletonAbout 4 min readAug 26, 2025Watch original
THE SUMMARYAI-generated

Key Concepts:

  • AI tools for PhD students
  • Literature review automation
  • Drafting and editing assistance
  • Large language models (LLMs)
  • AI-powered feedback on writing
  • SciSpace (formerly Typeset.io)
  • ChatGPT/Claude
  • Thesis AI
  • GenSpark
  • Academic writing
  • Research efficiency

1. Introduction: The Value of AI Tools in PhD Research

  • The video addresses the financial constraints of PhD students and highlights AI tools that are worth investing in, even on a limited budget.
  • The speaker emphasizes that the usefulness of AI tools varies depending on the stage of the PhD.
  • Money-Saving Hack: The speaker advises timing subscriptions to coincide with periods of maximum use, leveraging free versions or tools when possible.

2. SciSpace: Automating Literature Review

  • Main Point: SciSpace is presented as a valuable tool for early-stage PhD students to navigate the vast amount of existing literature.
  • Functionality:
    • Explains complex papers.
    • Identifies relevant studies.
    • Reveals connections between papers.
    • Summarizes papers quickly.
    • Allows users to save files and upload their own papers.
  • Example: The speaker demonstrates SciSpace by searching for "the most efficient OPV devices." The tool generates a summary, identifies key breakthroughs, and provides references.
  • Customization: Users can add columns to extract specific information from papers.

3. AI for Drafting and Editing: Leveraging Large Language Models

  • Main Point: The video discusses using AI to accelerate the writing process while maintaining originality and academic integrity.
  • Preferred Tools: The speaker favors general LLMs like ChatGPT and Claude for their flexibility.
  • Three-Step Process:
    1. Provide a Scaffold: Input an example of the desired writing style (e.g., an abstract from a published paper).
    2. Instruct the Model: Ask the LLM to "read" the example and then generate content based on it.
    3. Iterative Editing: Refine the AI-generated text through continuous editing and feedback.
  • Canvas Feature: The speaker highlights the "Canvas" feature in GPT, which allows for easier editing and modification of generated text.
  • Cautionary Note: The speaker acknowledges the existence of more advanced "done-for-you" tools like GenSpark, which can generate full paper drafts from figures. However, they caution against using such tools in academic publishing due to concerns about removing decision-making from the researcher.
  • GenSpark Example: The speaker demonstrates GenSpark's ability to create a paper draft, including an abstract, introduction, materials and methods, figures, and captions, from a set of figures.

4. Thesis AI: Getting Feedback on Your Writing

  • Main Point: Thesis AI is presented as a tool for obtaining feedback on writing, similar to having a supervisor available 24/7.
  • Functionality:
    • Highlights unclear arguments.
    • Identifies logical flaws.
    • Suggests improvements to writing.
  • Example: The speaker inputs their most cited paper into Thesis AI and receives feedback on various aspects, including the thesis statement and the establishment of a protocol.
  • Additional Features: Thesis AI provides a digest, identifies opportunities for further work, suggests relevant publications and conferences, and offers grant matching.

5. Conclusion: Focusing on Creativity and Outsourcing Grunt Work

  • Key Argument: AI will continue to automate academic tasks, freeing up researchers to focus on creativity and critical thinking.
  • Emphasis on Human Input: The speaker stresses that AI is a predictive engine and that true breakthroughs will still require human insight and the challenging of assumptions.
  • Call to Action: Identify the most dreaded tasks and use AI tools to make research easier and more efficient.
  • Final Thought: The video encourages viewers to explore free AI tools as well.

Technical Terms and Concepts:

  • Large Language Models (LLMs): AI models trained on vast amounts of text data, capable of generating human-like text.
  • OPV Devices: Organic photovoltaic devices.
  • Scaffold: A framework or structure used as a basis for writing.
  • Predictive Engine: An AI system that predicts the most likely outcome based on data.
  • Peer-Reviewed Paper: A scholarly article that has been reviewed by experts in the field before publication.
  • Abstract: A brief summary of a research paper.
  • Thesis Statement: A concise statement of the main argument or point of a research paper.

Logical Connections:

  • The video progresses logically from the initial stages of research (literature review) to the later stages (drafting, editing, and publishing).
  • Each section builds upon the previous one, presenting AI tools that address specific challenges faced by PhD students at different stages of their research.
  • The conclusion synthesizes the main points and emphasizes the importance of using AI strategically to enhance research productivity.

AI summaries can miss context or contain errors. Check important details against the original video.

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