The AI-Augmented Doctoral Dissertation13 weeks. Defensible. Yours.
A 13-week asynchronous course for doctoral candidates who refuse to choose between integrity and acceleration. Use AI as a disclosed, defensible collaborator across the full dissertation lifecycle, from topic discovery in Week 2 to a defended dissertation in Week 13.
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The Premise
The bar has not moved. The means have.
A defensible doctoral dissertation is still original, rigorous, contribution-bearing scholarship that a committee of experts will sign off on and that a candidate can defend in a room with five people who know the field better than almost anyone alive. That part is unchanged from 1986, 2006, or 2026.
What has changed is the means. A candidate who knows how to wield Claude, ChatGPT, Gemini, NotebookLM, Elicit, Consensus, Perplexity, Research Rabbit, Zotero, and the Subthesis Research Assistant can move through every phase of the dissertation with a speed and rigor that was not available three years ago. The literature review that used to take eighteen months can be done in six weeks. The framework that used to take a semester of advisor meetings can be drafted, stress-tested, and refined in a fortnight.
This course teaches a single integrated skill: how to use that acceleration without surrendering the originality, the authorship, or the legal ownership that make a dissertation defensibly yours.
The Three Non-Negotiables
Three principles that override everything else
Every week of the course is built on these. When in doubt, return to them.
Tools assist thinking. They never replace it.
A dissertation that was not thought by the candidate is not the candidate's. AI is a research and writing accelerator, not an author. The defense rewards the candidate who is unmistakably the author of their own thinking.
Provenance over invisibility.
Keep a prompt log. Disclose AI use according to your institution's policy. The candidate who can show their work has a moat the candidate who hides AI use does not. Provenance becomes a habit in Week 1, a defended artifact at the Week 13 defense.
Institutional policy supersedes course recommendations.
Your university's policy, your advisor's expectations, and your committee's norms always win over anything taught here. The course teaches navigation, not override. We teach you to recognize the conflict before it costs you.
Four Degree Tracks
One course, taught through the lens of your discipline
Every week ships three generalizable videos plus one track-specific video that re-cuts the same beats through your field’s conventions, tools, exemplars, and tripwires. Pick a track at enrollment.
Math and Pure Sciences
Pure mathematics, theoretical computer science, theoretical physics. Monograph-style traditions. Alphabetical co-author conventions.
Conservative on AI-in-proof, permissive on AI-in-typesetting and literature mapping.
STEM and Engineering
Applied CS, electrical and mechanical engineering, applied physics, computational science. Three-paper-model is now the default. Conference culture often outranks journals.
AI for coding is widely accepted under disclosure. AI in peer review is forbidden.
Biology and Life Sciences
Biology, neuroscience, biomedical research, genetics, ecology. Hybrid dissertation models. Heavy use of AI for protein structure prediction, sequence analysis, image segmentation.
Image integrity is the integrity boundary. Replicate honesty is the rigor boundary.
Public Health
Epidemiology, biostatistics, health policy, MPH and DrPH research tracks. Three-paper-model dominant. Policy implication framing expected.
HIPAA and BAA awareness are non-optional. Much of the data is protected health information.
The 13-Week Journey
Each week produces a concrete artifact
The course follows the actual dissertation lifecycle. Each week’s output is what the next week assumes you hold. By Friday of Week 13, you have defended.
Foundations: The AI-Augmented Doctoral Mindset
Tool stack table, one-page personal AI policy, institutional policy acknowledgment, and originality clause signed.
Topic Discovery and Research Question Formulation
A sharpened, scoped, defensible research question plus a one-paragraph rationale.
Committee and Advisor Relationship
Committee shortlist of three to five members, first-meeting agenda, and an AI-run mock advisor conversation log.
Literature Review, AI-Accelerated
Annotated bibliography of 40+ entries, a citation network map, and a one-page literature gap memo.
Theoretical and Conceptual Framework
A framework diagram and a one-page rationale you can defend to a skeptical committee member.
Methodology Design
A complete methods plan plus instruments, proofs, or pipelines specific to your design.
The Ideation Proposal
A two-to-three-page ideation document plus a recorded advisor reaction you can act on.
Proposal Writing and Pre-Defense
A complete proposal draft, a weaknesses list from the mock defense, and a remediation plan.
IRB, Ethics, Approvals, and Pre-Registration
A complete approval packet (or documented exemption) and a pre-registration record if applicable.
Data Collection, Experimentation, Proof Development
Data, results, or proofs in hand, plus a research journal that becomes the spine of Weeks 11 and 12.
Analysis and Results
A complete results chapter draft.
Discussion, Implications, and Writing It All Up
A complete end-to-end dissertation draft, ready for polishing and defense prep.
Defense, Submission, and Beyond
Defended, submitted, and started executing on a publication and career plan.
The Weekly Rhythm
Four videos per week, every week
The structure is the same regardless of which phase of the dissertation you are in. Predictable rhythm. Compounding skill.
01
Concept
What is this phase, what does "done" look like, what changes in 2026, and what does not.
02
AI Toolkit Applied
Hands-on demonstration with the specific AI tools that accelerate this phase.
03
Synthesis and Stress-Test
How to evaluate AI output, integrate it rigorously, and avoid the failure modes that derail otherwise capable candidates.
04
Track Lens
The same week, recorded once per track, seen through the conventions and tripwires of Math, STEM, Biology, or Public Health.
6 to 8 hours per week. Roughly 85 to 105 hours total across the 13 weeks. Asynchronous, on-demand, self-paced.
Who This Is For
A doctoral candidate in any research-degree program
The goal is to finish the dissertation. Successfully, on time, defensibly, with pride.
- PhD, DrPH, MPH thesis-track, DBA, EdD, MD-PhD candidates.
- Year one through year four. Proposal stage or beyond.
- Assumes at least one topic of interest. Does not assume a defended proposal.
- Basic familiarity with one major chat LLM. Week 1 builds the rest of the tool stack.
- Pain points: overwhelm, advisor friction, time pressure, fear of obsolescence.
- For candidates unsure where ethical AI use ends and academic dishonesty begins.
What Success Looks Like at Week 13
Five artifacts and one habit
The habit matters more than the artifacts. It is the instinct, before every paragraph and every decision, to ask: what part of this is unambiguously mine?
A defensible AI-augmented dissertation
Or, for earlier-stage candidates, a proposal-ready package the rest of the dissertation will be built on.
A prompt provenance log
Something you can show your committee at any moment. The receipts that turn AI from liability into moat.
A personalized tool stack
The set of AI instruments you will continue using across your academic and professional career.
A chapter-to-paper conversion plan
Target journals, target conferences, target timelines. Your dissertation becomes a publication pipeline.
A defense practice record
Something to return to before every high-stakes academic presentation for the rest of your career.
Once that instinct is installed, the rest of your career is protected. You can sustain rigor because of AI, not despite it.
Honest Expectations
What this course is not
- Not a methods course. It assumes you are learning your methodology in your discipline’s coursework or with your advisor. We teach you how to choose, defend, and stress-test a method. We do not teach the method itself.
- Not a writing-from-scratch service. You bring your own ideas, your own data, and your own judgment. AI accelerates production. It does not replace authorship.
- Not a workaround for institutional AI policy. We teach navigation, not evasion. When your institutional policy is more conservative than the course’s recommended workflow, your institutional policy wins, and we teach you to recognize the conflict.
- Not a credential. The dissertation, the defense, and the doctorate are the credential. This course is the operating system that gets you there.
Your Dissertation. Accelerated. Still Unmistakably Yours.
Join doctoral candidates who are using AI as a disclosed, defensible collaborator across the full dissertation lifecycle. Finish on time. Defend with confidence. Own every word.
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