
AI+ Research Workbook
Practice companion to AI+ Academic Research
Practice companion to T3-01.
You understood the warning about hallucinated citations. Then you cited one anyway.
You read AI+ Academic Research and understood the warning about hallucinated citations — then cited one anyway. This workbook makes verification a reflex: 40 exercises on your own project, and three calibration drills that train you to catch a fabricated citation, an overstated synthesis, and a claim its source never made. Built by an AI engineering firm for researchers who want AI's speed without staking their name on a source that doesn't exist.
- 40 exercises on your own research — scoping, finding, evaluating, reviewing, synthesising, drafting, and citing.
- Three calibration drills that train you to catch a fabricated citation, an overstated synthesis, and a claim its source never made.
- The TRUST source-verification workflow, made reflex — existence, metadata, and claim-in-source, before you cite.
- A verified synthesis matrix that holds every claim to a source that genuinely supports it.
- A defensible integrity record — a disclosure statement and an account of what AI did and did not do.
Anyone whose work involves rigorous research and who has read (or is reading) AI+ Academic Research (T3-01): postgraduate and PhD students, academic researchers and lecturers, lawyers and paralegals, clinicians and evidence reviewers, policy analysts, journalists, and research-heavy consultants. Cross-industry by design. They want to convert the parent book's workflow into habit against their own real project.
Also for:Research supervisors, librarians, and research-methods trainers running the workbook as a cohort or CPD programme; postgraduate research-skills modules pairing it with the parent book.
- Has applied the Academic Research Prompt Toolkit and PRISM to a real research project across the full lifecycle — scoping, finding, evaluating, reviewing, synthesising, drafting, and citing
- Has applied TRUST to detect hallucinated and misattributed citations before relying on any AI-surfaced source, and caught seeded failures in calibration drills
- Has produced a real literature synthesis and a correctly cited draft section from their own project
- Has applied the AI Safety Checklist and research-integrity discipline to their own AI use, producing a defensible record of what AI did and did not do
- Week 1
- The AI Research Workflow and Scoping
- Week 2
- Finding and Evaluating Sources
- Week 3
- Reviewing and Synthesising
- Week 4
- Drafting, Citing and Integrity
- Back matter
- Skill Summary · Recommended Next Reads · Glossary · Tool Reference
Built by an AI engineering firm for researchers who want AI's speed without staking their name on a source that doesn't exist.
Often packaged with this title.
T3-01 · Job SkillsAI+ Academic Research
T3-83 · Job SkillsAI+ Systematic Literature Reviews
T3-85 · Job SkillsAI+ Laboratory Research & Experimental Design
T3-29 · Job SkillsAI+ Data Analysis
T3-82 · Job SkillsAI+ Qualitative Research Methods
T3-84 · Job SkillsAI+ Quantitative Research & Statistics
T3-86 · Job SkillsAI+ Fieldwork & Ethnographic Research
T3-87 · Job SkillsAI+ Textual & Discourse Analysis
