Rep. Ro Khanna on Tech, Trump & Elon
Representative Ro Khanna represents the wealthiest congressional district in the country, but he wants to show Democrats how to speak to the working class. And perhaps surprisingly, he’s pretty good at it. But although Khanna was one of Bernie Sanders’ co-chairs in 2020, the “progressive capitalist” from Silicon Valley (don’t call him a democratic socialist) also hobnobs with tech titans. Because according to Khanna, the way to reindustrialize and revitalize the economy is by mobilizing both union leaders and tech and industry leaders — and he thinks he can be the one to bring them together.
Kara and Ro discuss everything from the DOGE committee, the killing of UnitedHealthcare CEO Brian Thompson, and Trump’s threats to jail members of the January 6 committee, AI policy, KOSA, and tech antitrust.
Questions? Comments? Email us at on@voxmedia.com or find us on Instagram and TikTok @onwithkaraswisher
Learn more about your ad choices. Visit podcastchoices.com/adchoices
More description
Representative Ro Khanna represents the wealthiest congressional district in the country, but he wants to show Democrats how to speak to the working class. And perhaps surprisingly, he’s pretty good at it. But although Khanna was one of Bernie Sanders’ co-chairs in 2020, the “progressive capitalist” from Silicon Valley (don’t call him a democratic socialist) also hobnobs with tech titans. Because according to Khanna, the way to reindustrialize and revitalize the economy is by mobilizing both union leaders and tech and industry leaders — and he thinks he can be the one to bring them together.
Kara and Ro discuss everything from the DOGE committee, the killing of UnitedHealthcare CEO Brian Thompson, and Trump’s threats to jail members of the January 6 committee, AI policy, KOSA, and tech antitrust.
Questions? Comments? Email us at on@voxmedia.com or find us on Instagram and TikTok @onwithkaraswisher
Learn more about your ad choices. Visit podcastchoices.com/adchoices
Listen elsewhere
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.
A comprehensive extraction focused on health practices, protocols, claims, and safety caveats.
A dedicated analysis of warnings, limitations, trade-offs, weak evidence, and uncertainty.
Repeatable methods, frameworks, mental models, processes, and systems.
Technologies, AI models, technical methods, capabilities, limitations, and adoption implications.
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.