#321: How to Think About Money
Personal finance can seem intimidating, but the reality is it’s pretty basic — save more than you spend, find ways to earn more, invest for the long-term, and protect your assets. But if personal finance is so easy, why do so many people screw it up?
My guest today has spent his career exploring this topic. His name is Jonathan Clements and he’s been The Wall Street Journal’s personal finance columnist for years. During his writing career, he’s also published several popular personal finance books including "The Little Book of Main Street Money." In his latest book, "How to Think About Money," Jonathan distills decades of personal finance experience into punchy, insightful, and action-oriented advice.
Today on the show, Jonathan and I discuss the most common money mistakes people make and the psychological biases that cause us to make them. Jonathan then shares research-backed advice on how money can buy you happiness…and also misery. Just depends on how you use it. He then delves into brass tacks tips on how to save for retirement no matter how old you are, how to overcome your psychological biases so you don’t make stupid money mistakes, and why focusing on not losing money will help you have more money in the long run. Lots of actionable advice to enhance your finances in this episode.
See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.
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.
Scientific findings, mechanisms, studies, hypotheses, and the limits of the evidence discussed.
A dedicated analysis of warnings, limitations, trade-offs, weak evidence, and uncertainty.
Memorable statements and important claims with attribution and source context.
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.