Article writing and research

Writing strong articles, whitepapers, or deep-dive blog posts takes a lot of effort:

• Formulating the idea
• Researching the scientific and industry consensus
• Designing the structure, logic, and narrative

Too often, this work happens alone, and feedback only arrives late, sometimes just before or even after publication. Even when authors do invite reviewers, it’s usually a small circle and already at the finishing stage.

In testing, we know the value of shifting left: catching issues earlier saves time, improves quality, and reduces costly rework. The same is true for research and writing. By collaborating early, you:

• Get feedback on your ideas before they harden into drafts
• Share the workload of gathering and validating sources
• Improve the clarity, accuracy, and impact of the final piece

With Beyond Quality, research becomes a shared process from the very beginning: stronger, faster, and more rewarding for everyone involved.

Examples:

• Vitaly’s article: “How the 5 whys method works in theory — and why it might not work in practice” — imagine if the community could have shared early examples or critiques to sharpen the argument
• Anupam’s article: “Exploratory testing a RAG model” — a week of research and experiments that could have been faster and more visible with collaborative support.

Collaborative work on research turns the lonely, high-effort part of research into a shared, energizing process.

• You save time.
• You get better quality outcomes.
• You don’t have to “recruit co-authors” in advance, the community naturally contributes at different levels.

Process proposal

1. Author pitches an idea of a research or an article they are considering working on:
   • Post a short thesis/question (1–2 sentences) and 2–3 bullets on what you want to explore. For example, “My thesis is that ‘more testing’ doesn’t always mean ‘better quality’, and I want to unpack this with research.”
   • Ask for specific help (critique framing, suggest sources, join outlining, review drafts).
2. Collaborators express help in different roles: sourcer, summarizer, reviewer, shaper, or co-author. Low-barrier contributions (links, quick comments) are always welcome. Categoriges of efforts are:
   • Level 1 (5–15 min): drop resources, quick feedback.
   • Level 2 (1–3 hrs): summarize sources, suggest structure.
   • Level 3 (deep dive): draft sections, review whole paper, act as co-author.
3. Publish & credit. Everyone who contributes is acknowledged. Co-authors and deep reviewers are named on the final piece.

Proposal example

NB: I did this with a few peers when I was writing my “QA Myth busting: more testing means higher quality” article.

Thesis: The common belief that “more testing automatically leads to higher quality” is a myth. In reality, the relationship between testing and quality is not linear, both poorly targeted and excessive testing can even harm product quality.

Main Ideas / Subtopics to Explore:

1. Defining Quality vs. Testing
   • Clarify the meaning of “quality” in a software context, take it from ISO family of standards, show how testing is just one activity that influences quality.
2. The Diminishing Returns of Testing
   • Explore the basic economics of testing: the more you test, the less additional value you get per test.
3. Risks of Over-Testing
   • Opportunity costs (time/resources spent on low-value tests).
   • False sense of safety (“we ran thousands of tests, so quality must be good”).
4. Alternative Approaches
   • Shift focus to test effectiveness and strategy, not volume.
   • Balance testing with prevention (requirements, design, etc).

Ask (How you can help):

• Review this framing: does it capture the real problem?
• Share papers, case studies, or industry reports on testing economics and diminishing returns.
• Help draft or refine the risks of over-testing
• Volunteer to co-review the final draft before publication.