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Your learning path: 16 lessons.
Module 03 / Lesson 09 · Read, apply, check
Use AI to explore and structure a story while keeping every substantive claim tied to evidence.
Review the approved evidence pack and ask what a particular audience could learn from it. A useful angle connects a real change, tension or decision with a reader’s concern. Generate several candidates, then score them for evidence strength, relevance, novelty and available access. Reject angles that depend on facts the client has not supplied. A catchy headline is not a reason to expand a narrow pilot into a market-wide claim. Keep a short note explaining why the selected angle deserves the reader’s attention.
Specify audience, purpose, central claim, supporting source IDs, intended format and exclusions. Add a missing-information list and an instruction to flag gaps rather than resolve them imaginatively. Define the role of each section: establish the event, explain the decision, show evidence, address limitations and give the reader a useful implication. Include quote IDs and the approved attribution. A strong brief gives AI enough structure to produce a coherent draft without inviting it to add fictional customers, statistics or statements merely to make the story flow.
Have the tool return the draft together with a claim-to-source table and unresolved questions. Separate proposed editorial framing from verified facts. Ask it to identify where the evidence supports correlation, a firsthand account or an opinion rather than a causal conclusion. Keep internal source annotations in the working draft until review is complete. The editor can then inspect the support efficiently and remove internal notes only when preparing the public version. Fluency is useful, but traceability makes the draft reviewable.
Read the opening and ask whether it answers the promised reader question. Check that every major section advances the story instead of repeating the same benefit. Identify unsupported expansion, stale background and generic claims. Return precise revision instructions: replace an unverified superlative, narrow the outcome to the pilot, or explain the actual operational tradeoff. Preserve useful passages instead of restarting blindly. Record what failed in the brief so the next assignment needs fewer correction rounds and the workflow improves over time.
Fictional manufacturing pilot. Open a highlighted claim’s editorial record.
During a three-site pilot, the manufacturer changed how maintenance exceptions were assigned. The useful lesson was about responsibility before automation, with findings limited to the participating sites.
Source: approved pilot brief, participating-site register.
Check: dates and site definitions agree.
Status: supported within the pilot scope.
Source: operations interview and comparison records.
Check: confirm the comparison period and definition of delay.
Status: hold quantitative wording until the record is complete.
The evidence covers a small pilot. A broader industry claim requires evidence the pack does not contain. Remove the sentence.
The editor’s deliverable is prose plus a claim record and unresolved questions.
Choose a specific reader and useful question.
Select the strongest supported tension or decision.
Define claims, source IDs, structure and exclusions.
Return prose, evidence links and unresolved questions together.
A fictional agency receives evidence about a manufacturer that reduced a recurring maintenance delay during a three-site pilot. The pack includes dates, a process diagram, an operations interview and a limited comparison. AI proposes three angles: industry transformation, a practical exception-handling lesson and a founder profile. The editor selects the operational lesson because the evidence supports it directly. The brief names plant managers as readers and forbids extrapolation to the whole industry. The first draft includes a claim map and two questions about the comparison period. After the client resolves one question, the editor removes the unsupported sentence behind the other. The final story explains a specific decision and its limits rather than turning a modest pilot into a sweeping technological revolution.
Another team starts with the headline “The Future of Manufacturing Has Arrived” and asks AI to build a story around it. The evidence pack becomes decoration for a predetermined narrative. The draft adds market forecasts, anonymous customer enthusiasm and a causal claim that the supplied records cannot establish. Editing now requires removing the article’s central premise. The team would have saved time by selecting an evidence-supported angle before asking for persuasive prose.
More angles do not automatically create more value. Three distinct, supported directions are more useful than twenty variations of the same promotional headline. Treat AI suggestions as editorial hypotheses. The human editor decides what the evidence supports and which reader question matters. If none of the angles is strong, return to reporting rather than stretching a thin pack into a longer article.
A source citation in an AI draft must be checked against the underlying item. A model can attach a real source to a claim it does not support. Do not treat the existence of a source map as proof of accuracy; use it as a navigation aid for the editor’s verification.
Do this today · 30 minutes
Write an AI drafting brief for the maintenance pilot.
A document or spreadsheet and the illustrative case in this lesson. Use synthetic or already approved material for practice; no paid account or real client data is required.
Before: Choose a specific reader and useful question.
After: Return prose, evidence links and unresolved questions together.
Notes stay in this browser. Download a copy to keep them.
Test this worksheet on one bounded assignment. Record the reviewer’s findings, revise the method and assign the next review date.
Before you move on
AI proposes an industry-wide transformation headline from evidence covering three client pilot sites. The draft cites the pilot report and reads persuasively. Which change should the editor make before developing the article further in this agency workflow?
Next lesson →Associated Press: newsroom standards for AI
Lesson edition 1.0 · References reviewed 16 October 2026 · Practical exercise reviewed 16 October 2026. Examples are illustrative teaching scenarios.
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Use the worksheets to turn each lesson into a real decision. Improve the method as you learn from client evidence, editorial checks and delivery results.
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