Sharing an article is easy. Deciding whether it deserves your audience's time is the actual work of curation. An AI summary can make that decision faster, but it can also hide a weak source behind a convincing paragraph.
A useful curation workflow separates discovery, verification, and your own contribution. The goal is a small set of relevant material with a clear reason to read it, rather than an endless stream of automated links.
Define what belongs in the collection
Choose an audience and a question. A collection for independent shop owners might cover inventory management, local events, and customer service. A collection for engineering leaders needs different sources and a different level of detail.
Write a short inclusion rule. For example: “Share material that helps a small team make a practical operating decision, with a clear source and a concrete example.” Also define exclusions: thin sales pages, unsupported forecasts, recycled statistics, or commentary outside your expertise.
The niche industry copilot guide explains why vocabulary and decision context matter when your audience has specialist needs.
Use AI to narrow the reading queue
A research feed can reduce the time spent searching. Feedly's AI Feeds documentation describes topic-based queries, source selection, and exclusions. Test the results against your editorial rule rather than accepting every match.
Start with primary sources where possible: original research, official documentation, public records, and direct statements. Commentary can be useful when it adds analysis, but follow important claims back to the source.
Do not confuse discovery with recommendation. A high match score or a trending topic does not establish that an article is accurate, original, or relevant to your reader.
Read the source behind the summary
Before sharing, check the full article. Confirm the publication date, author, central claim, supporting evidence, and limitations. If the claim concerns a tool feature or platform policy, use current official documentation.
Some assistants cannot retrieve a URL merely because you pasted it. Verify what text the assistant actually received. A generated synopsis based on a title is not a summary of the article.
Keep a simple note with the source link, the useful idea, any uncertainty, and why it belongs in your collection. This makes later review much easier when a policy changes or someone challenges the claim.
Add the interpretation your audience needs
A hypothetical curated post about a new reporting feature could say:
This update may help teams compare support categories without rebuilding their spreadsheet. The part to check is whether your account includes the export you need. I would test one week's data before changing the reporting process.
That is an editorial angle, not an invented result. It explains a possible use and a decision to make. Ask AI for two ways to express your own annotation, then remove any implication that you tested something you have not tested.
For repurposing material you own, use the scaling content creation guide. Curation of someone else's work requires attribution and care with quotation; it is a different task.
Keep the output small and deliberate
Use an editorial gate before anything enters a publishing queue:
- Source: Can the important claim be traced to reliable evidence?
- Relevance: Does it answer a question your audience actually has?
- Context: Have you preserved the scope, date, and limitations?
- Contribution: Have you explained what readers should notice or do?
Link to the original and paraphrase modestly. Do not copy an entire article or let an assistant turn somebody else's distinctive work into an unattributed post. A useful collection helps readers find sources; it does not erase them.
Review what people ask after sharing. If the collection produces confusion, revise the annotations or your inclusion rule. If it produces no useful discussion, it may be too broad.
Start with three sources and one reader question. Publish only the item for which you can explain a concrete benefit. A shorter, trustworthy reading list is easier to maintain and more helpful than a fully automated feed.