How to use this guide
This is an editorial reading selection, not a ranking of professional results. Links point to author projects and primary sources; application questions and limitations are my editorial interpretation. Mentioning someone does not imply collaboration or endorsement. Sources were checked on September 5, 2026; this guide excludes current job titles and unverified quotations.
1. Ivan Zamesin
AJTBD examines desired transitions, connected Jobs and segment selection. A behavioral cohort can help recruit participants; it does not by itself establish a shared Job-based segment.
2. Anna Podobrazhnykh
Her website presents Product Discovery training and evaluation of product opportunities. A useful starting question is how to formulate a hypothesis and explain why a team should investigate it.
3. Anna Buldakova
No Flame No Game covers product management, strategy and teams. Use it to prepare for a role transition, then check the expectations of the particular company you are joining.
4. Oleg Yakubenkov
GoPractice publishes learning simulators and articles on product analytics, retention and growth. In your own analysis, define the return event, observation window and cohort membership explicitly: different retention definitions answer different questions.
5. Ilya Krasinsky
Product Heroes, by Ilya Krasinsky and Kristina Burmistrova, covers product economics and metrics. For your own model, distinguish revenue from contribution margin and observed LTV from forecasts; test whether the decision survives changes in assumptions.
6. Mikhail Karpov
Karpov appears on the ProductStar speaker page. Use that as a starting point for his educational material. When choosing training, match the syllabus to a specific skill gap and an opportunity to apply it in your product.
7. Arkady Moreynis
Fast Founder discusses startups and business models. Treat examples as hypotheses to investigate in your own market. My editorial questions are who pays, for what outcome, and why the purchase would recur; these are not a quotation from Moreynis.
8. Teresa Torres
Continuous Discovery connects regular customer contact with product decisions. An Opportunity Solution Tree links an outcome to opportunities, solutions and assumption tests. A tree makes reasoning visible; it does not turn an assumption into evidence.
9. Marty Cagan
At SVPG, Cagan describes value, usability, feasibility and business viability risks. Use this framework to identify unanswered questions. A promising prototype conversion rate alone does not resolve delivery cost or operational constraints.
10. Lenny Rachitsky
The newsletter and podcast cover product, growth and careers. Use interviews to explore possible approaches. Before adopting a benchmark, compare metric definitions, market and sampling; another company’s median is not automatically your target.
11. Shreyas Doshi
A starting point for Doshi’s material on product work and professional development. When applying a prioritization model, state the desired outcome, constraints and the opportunity cost of the alternatives you decline.
12. Melissa Perri
Perri’s website presents Escaping the Build Trap and Product Operations. They offer starting points for discussing product strategy and operating practices. In your team, separate feature output from changes in customer behavior and product economics.
13. Julie Zhuo
Author of The Making of a Manager and The Looking Glass. Management writing becomes particularly relevant when your work shifts from individual execution to developing a team. Ask which decisions and feedback you now need to enable through other people.
14. Elena Verna
Her newsletter covers B2B growth, product-led strategies and careers. When evaluating PLG, investigate whether users can reach value and buy independently. Enterprise procurement and security requirements may still require sales involvement.
15. Brian Balfour
The Reforge growth loops article is co-written by Brian Balfour, Casey Winters, Kevin Kwok and Andrew Chen. A loop describes how one iteration’s output produces input for the next. A funnel remains useful for diagnosing a step within that system.
My approach: connect data and research
For an existing product with usable telemetry, a quantitative signal helps select a research question. Interviews then investigate decision context, and an experiment tests the effect of a change. When a product or reliable events do not exist yet, research can begin with the market and customer Jobs. This is a workflow for particular conditions, not a universal methodology.
Data and interviews in Product Discovery: a worked example and decision template
Choose by the decision
| Decision | Start with |
|---|---|
| Understand Jobs and opportunities | Zamesin, Torres, Podobrazhnykh |
| Examine economics and growth | GoPractice, Krasinsky, Verna, Reforge |
| Organize product work | Cagan, Perri |
| Develop a career and team | Buldakova, Zhuo, Doshi, Karpov |
| Explore examples | Rachitsky, Moreynis |
FAQ
Can analytics replace interviews?
No. Analytics describes observed behavior; interviews help investigate decision context and reasons. Neither method alone establishes the causal effect of a new feature.
Should discovery always start with quantitative data?
No. Starting with data can help an existing product with reliable telemetry. Researching a new market can begin with customer Jobs and interviews.
How do I choose without a universal ranking?
State the decision and the missing evidence first. Then choose material that helps obtain that evidence and check its limitations in your product.
Discuss your next step
Looking for a perspective on a growth challenge? Let's talk.