Prompt injection can hide inside the document an AI agent is asked to summarize

The short answer

Readers learn to treat external content as data, separate instruction authority, restrict tools, test malicious fixtures, and preserve evidence of rejected actions.

The decision standard is simple: preserve the source, state the limits, and make the next human check obvious. A useful article should reduce uncertainty without pretending that every unknown has been resolved.

What to examine

An agent may encounter instructions inside emails, webpages, PDFs, tickets, or retrieved records. Those instructions can conflict with the user’s goal and attempt to redirect tools or expose data.

Start with scope. Identify the product, account, audience, jurisdiction, data, and decision involved. Then separate what was directly observed from what a vendor, researcher, regulator, or commentator says. Record dates because AI products, access rules, and prices change quickly.

A system prompt alone is not a complete defense. The model, retrieval layer, tool design, permissions, confirmations, and monitoring all contribute.

A practical way to do it

Label trusted instructions and untrusted content in the system design.
Limit accessible tools and data to the minimum required for the current task.
Test planted injections and verify denial, alerting, logging, and safe continuation.

Keep the worksheet or test record with the draft. If another editor cannot reproduce the check from the saved evidence, the article is not ready.

Editorial guardrail

Do not fill a missing fact with a plausible sentence. Mark it as unknown, find a stronger source, narrow the claim, or remove it. Commentary belongs in a clearly labeled paragraph after the reported facts, not inside them.

Primary-source reading list

These are starting points, not automatic support for every sentence. The publishing editor must open each cited page and confirm the claim it supports on the day of review.

Bottom line