Last updated: October 30, 2026
VEYREM starts with curiosity. Sometimes that means opening a tool and trying it ourselves. Other times it means spending an evening buried in documentation because we want to understand how something actually works.
Sometimes one of us can open a tool, run the workflow, compare the results, and show you exactly what happened.
Other times, the interesting question is bigger than what we can realistically test firsthand. In those cases, we dig through official documentation, release notes, product pages, technical explanations, demos, and trustworthy secondary sources until I understand what is actually useful.
We’re fine with both. We just don’t want to blur the line between them.
This page explains how we document tests and check research sources. Our Editorial Policy covers the principles behind choosing and publishing articles.
Two ways VEYREM researches a topic
1. Hands-on testing
When an author tests something personally, that author documents the conditions that matter.
That can include:
- the tool or model used
- the plan or version
- the task the author gave it
- prompts or setup
- the result
- what worked
- what failed
- what needed manual fixing
- how long it took
- whether the author would keep using it
If a comparison matters, we try to give the tools the same job instead of comparing marketing claims.
2. Deep-dive research
Not every useful topic requires firsthand access.
For research-based articles, I prioritize:
- official documentation
- official help centers
- release notes and company announcements
- technical documentation
- primary-source interviews or presentations
- trustworthy secondary reporting when primary sources are not enough
We do not present researched information as personal experience.
If an author has not tested something personally, the article says so when that distinction matters.
How to read the evidence in an article
- Recorded work: an input, reply, calculation, or file check from the work described. Dates and settings are given when recorded.
- Screens: original captures show a visible state. Translated or reconstructed screens are labeled; an illustration does not establish that a task was completed.
- Documentation: linked sources support product conditions. The source-check date is separate from the date of a hands-on run.
- Suggested examples: practice inputs, prompts, and expected answers written for a guide are not recorded model replies.
For example, Som’s study-answer check shows the calculation missing from a reply. Yun’s spreadsheet article separates the earlier workbook records from a later two-row Excel check. Those records support the checks shown, not a result for every task or file.
What we look for
We are usually less interested in the feature list than in questions like:
- What problem does this actually solve?
- Who would benefit from it?
- What still requires human judgment?
- Is the free version enough?
- What changes once you use it in a real workflow?
- Is this useful for work, learning, creating, automating repetitive tasks, or—when relevant—opening up a new opportunity?
- Is there a catch that is easy to miss?
AI-assisted research
VEYREM is a site about AI, so yes, AI is part of the research and writing process.
We may use AI to:
- organize research
- compare sources
- summarize long documentation
- test prompts
- generate questions worth investigating
- explore different workflow ideas
- work through early drafts
But AI output is not treated as a source by itself.
Important factual claims should be checked against current sources, especially when they involve pricing, plans, features, model availability, limits, policies, or anything else that changes quickly.
When information changes
AI moves fast.
If a feature, price, model, or policy has changed since an article was published, we may update the article rather than leave an outdated version in place.
Where useful, VEYREM may show an updated or reviewed date.
The standard
Do the homework. Say what was tested. Say what was researched. Then explain the part that is actually worth knowing.
If a reader can understand the topic faster and leave with something useful to try, the research did its job.