451. The Everyday Runner, Lara Kondor
"I just had to keep moving forward… I never let myself stop and wallow in it, because I was afraid that if I did, I'd never stop. I just had to keep going. So I did."
Lara Kondor is — and always has been — tough. She's a 46-year-old ultra-running mom of three who lives in New Hampshire, and on this episode, she talks about how she found running, and about the powerful role running has played in her life. Lara is a 13-time marathoner and nine-time ultramarathoner, with dreams of hitting the 100-mile mark in a single event. (Her longest so far is 92 miles at The Hamsterwheel 24-hour race.) Both on the run and off, Lara is a full-time caregiver for her oldest child, Noah, who is 25 and was diagnosed with autism at three years old. Noah is mostly nonverbal, but running has given him a new way to communicate. In this conversation, Lara talks about Noah's diagnosis, about new motherhood, and about how they started running together. She talks about asking for help, about accepting help, and about seeing Noah thrive (and get faster!) on the run.
SPONSOR: COROS — Use code ONTHERUN for a free keychain watch charger with the purchase of any watch!
What you'll get on this episode:
- All about Lara's childhood growing up in Florida (4:15)
- On having children at a young age, and what it was like getting Noah's autism diagnosis when he was three years old (6:20)
- How Lara found running (17:25)
- Why Lara loves running ultras — on a track (31:40)
- How Noah found running (36:00)
- Why Lara and Noah joined the Millennium Running Club (42:30)
- What's next for Lara and Noah? (55:40)
Check out:
Melissa Cummings on Episode 375 of the Ali on the Run Show
Follow Lara:
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.