As a part of our partnership with AnswerThis, I’ve recorded a short guide how I use this tool to understand specific area of research better. It’ll go live tomorrow, but I thought I’d give you early access - hope it helps! P.S. what do you think of using AI for research?

Last week we reviewed two papers in real time, and the same “hidden blockers” showed up that often lead to slow reviews, major revisions, or desk rejection. If you’re preparing a manuscript, use this as a checklist before you submit. 1) Abstracts: stop starting with “what we did” A strong abstract reads like a story, not a methods note. Use this sequence: - Big-picture context (why the topic matters). - Specific research gap (what’s missing in the literature). - What you did (1–2 sentences). - Key results (headline numbers only). - Why it matters (one clear implication). Also: avoid abbreviations in the abstract unless truly unavoidable—clarity wins. 2) Literature review ≠ research gap A table summarising prior studies is useful, but it doesn’t automatically create novelty. You still need 2–3 explicit sentences that say: - What others have done. - Where the limitations are. - How your work addresses those limitations. If your novelty requires “reading between the lines,” it’s not clear enough. 3) Results: description is not discussion Many drafts report trends (increase/decrease) but don’t interpret them. What strengthens a paper immediately: - Benchmark your findings against prior studies (agree? contradict? extend?). - Quantify differences (relative errors, percentage differences), not just “higher/lower.” - Make the insight explicit: “This suggests…”, “This implies…” 4) Structure signals quality Common fixes that make papers feel more “journal-ready”: - Avoid lots of one-paragraph subsections—group results by themes (e.g., “design parameters,” “operating parameters”). - Keep figure labels consistent (Fig. 4a/4b rather than “left/right”). - Use equation formatting consistently, and consider a nomenclature/abbreviations table. - Add limitations + future work (show you understand what your study did not cover). What’s next I’ll run these peer-review sessions weekly or bi-weekly, depending on demand, so the whole community benefits from repeated patterns and practical fixes.

“Teams deliver change” this is what my former head of department kept telling us. And I agree. It’s much easier to work with someone rather than trying to make it yourself. Tell us, what’s your research area and if you’re currently looking for collaborators.

It’s been an unusually busy break for me. To the extent I haven’t had time to sit down and plan for 2026. But if I were to list just 2 priorities it would be this: 1. Grow this community into number #1 research community (we need to be ambitious) 2. Develop training materials and deliver at least 2 sessions (one training per quarter; 2 for this community; 2 relevant to my professional capacity) That’s it - beyond my academic responsibilities. How about you? What do you plan this year? P.S. We run paper writing training this Friday. Will you be there?