How Historically Accurate Is ‘Once Upon a Time … in Hollywood’? Plus: Amazon’s Next Move and Celebrating the Music of 1999 | The Watch
There was a lot of news out of the TCAs this weekend, including what Amazon wants its streaming service to look like over the next few years (2:43). After Netflix canceled the critically acclaimed ‘Tuca and Bertie,’ the metric of success in the streaming world is called into question yet again (17:15). Plus: How historically accurate is ‘Once Upon a Time … in Hollywood’ (26:00)? And our favorite music from 1999 (39:20)
Host: Chris Ryan
Guests: Alison Herman, Kate Knibbs, and Lindsay Zoladz
Spoilers for ‘Once Upon a Time ... in Hollywood’ in the second half of this episode.
Learn more about your ad choices. Visit podcastchoices.com/adchoices
More description
There was a lot of news out of the TCAs this weekend, including what Amazon wants its streaming service to look like over the next few years (2:43). After Netflix canceled the critically acclaimed ‘Tuca and Bertie,’ the metric of success in the streaming world is called into question yet again (17:15). Plus: How historically accurate is ‘Once Upon a Time … in Hollywood’ (26:00)? And our favorite music from 1999 (39:20)
Host: Chris Ryan
Guests: Alison Herman, Kate Knibbs, and Lindsay Zoladz
Spoilers for ‘Once Upon a Time ... in Hollywood’ in the second half of this episode.
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.
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.