AI+ Research Workbook

Name: AI+ Research Workbook
Price: 50 USD
Availability: InStock
ISBN: 9789746525602

Put AI to Work on Your Real Research

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.

Tier

Workbooks

Inside

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.

Who this is for

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.

You’ll be able to

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

What’s inside

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.