456. Talya Minsberg, New York Times Sports Editor
"It was so cool, and so weird, and it's still hard to describe."
For many sports journalists — especially the ones who cover running — New York City Marathon week is arguably the busiest of the year. That was certainly true for New York Times sports editor Talya Minsberg, who not only covered the race and many of the stories leading up to it, but also ran the marathon herself (and earned a Boston Marathon qualifying time in the process!). On this episode, Talya reflects on that week, sharing the stories she was most excited to tell (notably, the one about Tommy Rivers Puzey's comeback), and stories from her own race. She talks about what her days look like writing, editing, and managing the NYT Running newsletter. Plus, tales from the Met Gala, the Tokyo Olympics, and the Times comment section.
SPONSOR: AfterShokz — Visit ontherun.aftershokz.com for 15% off wireless headphones.
What you'll get on this episode:
- What's making Talya happy right now? (5:00)
- What Talya's busiest week of the year was like (6:00)
- All about that Tommy Rivers Puzey story (14:30)
- What Talya's reporting process is like (18:45)
- The stories that give Talya butterflies (24:50)
- What it was like running the virtual NYC Marathon in 2020, and how it compared to this year's in-person race (29:00)
- What it was like being at the Tokyo Olympics this summer (31:30)
- Talya shares her career highlight reel (40:00)
- What Talya was like growing up, and how she got the job at the New York Times (45:00)
- On being a comment moderator for the New York Times (53:40)
- How Talya spends her days now (55:50)
- Talya's take on the uneven coverage of women's vs. men's sports in the media (57:15)
- The running stories Talya is excited about right now (1:03:30)
- The New York Times piece Talya thinks everyone should read (1:07:30)
Check out:
Erin Azar in the New York Times
Tommy Rivers Puzey in the New York Times
"Why Are American Women Running Faster Than Ever? We Asked Them — Hundreds of Them"
Follow Talya:
Follow Ali:
- Instagram @aliontherun1
- Join the Facebook group
- Twitter @aliontherun1
- Support on Patreon
- Blog
- Strava
Listen & Subscribe:
SUPPORT the Ali on the Run Show! If you're enjoying the show, please subscribe and leave a rating and review on Apple Podcasts. Spread the run love. And if you liked this episode, share it with your friends!
Available Results
Generated results are saved to your library for reuse and search.
Choose Template
Pick the result you want. You can review provider and model before generating.
A concise first-pass summary for understanding the episode quickly.
A comprehensive, source-grounded extraction of the reusable knowledge in an episode.
Technologies, AI models, technical methods, capabilities, limitations, and adoption implications.
Repeatable methods, frameworks, mental models, processes, and systems.
A dedicated analysis of warnings, limitations, trade-offs, weak evidence, and uncertainty.
A dedicated inventory of concrete resources named in the episode.
A concise first-pass summary for understanding the episode quickly.
A detailed readable summary organized by chapter or topic.
A navigable map of subjects, topic flow, and suggested chapters.
A comprehensive, source-grounded extraction of the reusable knowledge in an episode.
Reusable atomic knowledge units extracted from the episode.
A comprehensive extraction focused on health practices, protocols, claims, and safety caveats.
A comprehensive extraction focused on opportunities, strategy, markets, and company building.
Explicit actions, next steps, habits, recommendations, and things to avoid.
A dedicated inventory of concrete resources named in the episode.
A dedicated analysis of warnings, limitations, trade-offs, weak evidence, and uncertainty.
A concise first-pass summary for understanding the episode quickly.
A detailed readable summary organized by chapter or topic.
A navigable map of subjects, topic flow, and suggested chapters.
A comprehensive, source-grounded extraction of the reusable knowledge in an episode.
Reusable atomic knowledge units extracted from the episode.
A comprehensive extraction focused on health practices, protocols, claims, and safety caveats.
A comprehensive extraction focused on opportunities, strategy, markets, and company building.
Scientific findings, mechanisms, studies, hypotheses, and the limits of the evidence discussed.
Technologies, AI models, technical methods, capabilities, limitations, and adoption implications.
Investment theses, assets, catalysts, valuation reasoning, time horizons, and risks.
Chronologies, actors, causes, consequences, turning points, and competing historical interpretations.
Policies, proposals, stakeholders, arguments, implementation constraints, and predicted effects.
Career paths, skills, hiring signals, workplace decisions, transitions, and limitations of the advice.
Behavioral mechanisms, biases, motivation, habits, emotions, interventions, and evidence limitations.
Economic mechanisms, incentives, indicators, market structure, forecasts, and uncertainty.
Leadership principles, team systems, organizational design, culture, feedback, and failure modes.
Audience, positioning, messaging, acquisition, retention, experiments, metrics, and failed approaches.
Teaching methods, learning strategies, practice, feedback, assessment, and effectiveness evidence.
Theses, premises, arguments, objections, values, thought experiments, and unresolved questions.
Communication patterns, conflict, boundaries, expectations, repair methods, and contextual limitations.
Books, papers, authors, courses, and other learning resources mentioned in the episode.
Repeatable methods, frameworks, mental models, processes, and systems.
Explicit actions, next steps, habits, recommendations, and things to avoid.
Memorable statements and important claims with attribution and source context.
A dedicated inventory of concrete resources named in the episode.
A dedicated analysis of warnings, limitations, trade-offs, weak evidence, and uncertainty.