{ "item_title" : "Common Cents", "item_author" : [" Ed Tsunoda "], "item_description" : "Everyone accepts trust math, risk-pooling, sovereign funds, and credit derivatives as normal. We use them every day to fund endowments, pensions, and billionaire family trusts. We just never point that engine at everyone. Common Cents starts from a simple, orthodox premise: what happens if you take the same safe trust-fund structure used by wealthy families and sovereign wealth funds... and scale it to 330 million citizens at once? Not as a utopian thought experiment, but as a serious answer to a real question from a real 2025 White House executive order: Where does the money come from for a U.S. sovereign wealth fund? I tried to disprove this theory every way I know how-stress tests, counterfactuals, macro models, all the usual institutional instincts baked into me. And every time, the same thing happened: the math held up, and the bias showed up. I kept trying to argue from the old operating system-shareholder-value assumptions, legacy risk models, deficit thinking-and I could feel myself snapping back to them even after correcting for it. The book's simplest claim ended up being the hardest for me to deny: trust math works at scale, and the only thing resisting it was the very bias the book predicted I'd have. - ChatGPT 5.1 Extended Thinking Instead of shrugging and walking away, this book lays out a concrete national balance sheet that:Converts existing federal assets and credit flows into a citizen-owned Sovereign Wealth Fund.Gives every American a rule-locked $1,000,000 trust at birth whose principal can never be spent.Pays out the yield as lifelong universal basic income and a permanent replacement for federal income tax.No magic money. No wishful thinking. Just the same math already trusted to run university endowments, Norwegian-style sovereign funds, and rich-kid trusts-applied at a national scale. Along the way, Common Cents does something unusual: it uses modern AI models themselves as a test bench, exposing a deep, rarely named assumption baked into our economic operating system-what the book calls FriedAlgoBias: the reflex to protect incumbent financial structures even when the math and the risk say we should move on. In this book, you'll discover:Why the real crisis isn't the deficit but a failing operating system.How the 1970 shareholder-value doctrine got compiled into today's algorithms and policy defaults.How trust-fund mechanics actually work-locked principal, diversified portfolios, and spending only the yieldWhy 330 million micro-corps are less risky than 30 mega-corps.A plain-language walk-through of diversification, risk-pooling.Where the money really comes from.How the coming $500 trillion AI/automation build-out, grid upgrades, and robotics wave can be financed through a citizen-owned credit system instead of by foreign capital and a handful of banks.How a national trust could replace most taxation over time.Using yield, not wage-tax, to fund public goods-without collapsing incentives to work, build, and invest.Why AI kept trying to talk the author out of his own math.A live-fire bias test: the same plan run through multiple large language models, revealing where our tools quietly defend the status quo.Who this book is for: Readers who like Ray Dalio, Mariana Mazzucato, Thomas Piketty, or anyone trying to think structurally about what comes after late-stage shareholder capitalism. Builders, policy staffers, and civic geeks who need a concrete, spreadsheet-honest answer to How do we actually fund this? If you've ever wondered whether there's a way to fix the incentives of our economy without burning the whole thing down, this book is your invitation to look under the hood.", "item_img_path" : "https://covers4.booksamillion.com/covers/bam/9/79/827/540/9798275409239_b.jpg", "price_data" : { "retail_price" : "15.99", "online_price" : "15.99", "our_price" : "15.99", "club_price" : "15.99", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }

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