Deep Background
Source: Check Please
Author: Mike Caulfield
Original source: https://checkplease.neocities.org/?utm_source=substack&utm_medium=email
Source type: guide
Private backup: the full article text is archived in the private repository at archives/articles/checkplease-neocities-org-checkplease-neocities-org.source.md. It is not published on the public Quartz site.
Summary
This Check Please page introduces “Deep Background,” a reusable prompt meant to make LLMs behave more like research assistants than generic answer machines. The prompt is designed to surface context, conflict, chronology, and source comparisons so student researchers can build background knowledge while still retaining responsibility for their own conclusions. The page frames prompt design as an information-literacy scaffold rather than a replacement for judgment.
Pull quotes
Hallucinate less, compare sources
“With the prompt in place, your LLM will come to better conclusions, hallucinate (much) less, and source conflicting perspectives more systematically.”
Less chatbot, more research assistant
“It also models an approach that is less chatbot, and more research assistant in a way that is appropriate for student researchers, who can use it to aid research while coming to their own conclusions.”
Use the prompt yourself
“To see how the tool works, browse the examples or take the instruction prompt in the right sidebar and use it yourself.”
Big ideas
- Students need to check AI answers against real evidence
- Students need to bring the purpose; AI should not supply it for them
Claims
- Research prompts can support inquiry without taking over student judgment
- AI-assisted inquiry should ground claims in evidence
Key evidence and examples
- The page recommends pasting Deep Background at the beginning of a chat or adding it to project instructions.
- It claims the prompt can reduce hallucinations and improve the sourcing of conflicting perspectives.
- It is framed as appropriate for student researchers because it supports inquiry without writing the final conclusion for them.
- Example research logs include contested claims about warfare, microplastics, asbestos in The Wizard of Oz, Eisenhower and Lumumba, historical bread adulteration, and gravity explanations.
- The page notes that effective use requires a search-enabled LLM and recommends strong models for the task.
Education relevance
This is relevant to research literacy, SIFT-style fact checking, AI-assisted inquiry, and classroom routines that help students gather context, compare evidence, and preserve their own judgment.
Durability note
The exact prompt will age as model search features change, but the underlying move—turning AI use into source-aware background research rather than answer collection—is durable.