Planet Money is an NPR podcast that explains economic concepts through narrative-driven stories rather than dry analysis. It treats economics like a conversation with a friend—accessible, surprising, and actually engaging.

• The show makes economics approachable by grounding abstract concepts in real stories and human situations
• It's built on the premise that learning about the economy doesn't have to feel like a lecture

a16z is launching a small, stage-matched community for finance leaders, with cohorts of eight CFOs meeting six times over a year. Each session mixes practical workshops—on planning, forecasting, AI tools and scaling finance teams—with candid peer discussions to build trust and lasting support networks.

• a16z is launching a year-long CFO community with cohorts of 8 finance leaders at similar growth stages, meeting in person every other month for 6 sessions.
• Sessions combine candid moderated peer discussions with deep dives on planning, forecasting, team scaling, AI tools, and GTM/engineering productivity.
• Curation rules: ~80% true peers with a few slightly ahead, no investors or observers allowed, and missing more than one session forfeits the spot.
• The idea originated from a16z's Martin Casado and SpaceX founder Michael Truell identifying CFO isolation as a key pain point at last year's Runtime summit.

Rillet’s AI-native ERP processes transactions as they happen, cutting manual month-end entries to under 1% and turning the traditional close into a daily routine. Data from 56 early adopters show nearly all entries auto-posted, though B2B and multi-entity firms still need more human judgment.

• Rillet's data across 56 customers shows 99.86% of entries auto-post in real time, leaving under 1% needing manual review in 87% of cases.
• Manual entry (5-15%) persists mainly in service-based B2B firms with complex transactions, while consumer-facing companies run near-fully automated books.
• Multi-entity firms (4+) see revenue/billing entries drop from 58% to 38% of the ledger but still achieve continuous close without a period-end crunch.

This daily digest covers SpaceX’s $60 billion stock deal to buy AI coding startup Cursor, Apple’s plan for camera-equipped AirPods and a foldable iPhone in 2027, and Genesis AI’s new industrial robot with LG. It also highlights Snap’s $2,195 AR glasses, AWS’s S3 annotations feature, Meta’s crumbling engineering culture, Anthropic’s talks with Trump officials, and leaked OpenAI finances showing huge losses.

• SpaceX is buying AI coding startup Cursor for $60 billion in stock, expected to close Q3
• OpenAI's leaked financials show revenue nearly quadrupled to $13.07B in 2025, but losses grew from $4.1B to $6.11B as expenses more than doubled
• Apple is reportedly developing camera-equipped AirPods, a foldable iPhone, and a 20th-anniversary model, all targeting late 2027
• Anthropic is negotiating with Trump administration officials over access restrictions after a security bypass was discovered in its latest models

Investors are rushing to claim stakes in AI through SPVs, secondary markets, and pre-IPO perpetual futures—synthetic or real—because demand for ownership outstrips supply. Framed by the internet’s evolution from “read” to “write” to “own,” this trend shows the next phase democratizes economic rights in AI alongside its technologies.

• Investors are turning to SPVs, secondary markets, and even crypto perpetual futures to get exposure to AI companies before they IPO, since demand for ownership far outstrips available supply.
• Chris Dixon's "read, write, own" framework explains this: after the internet made info accessible (read) and let anyone publish (write), the current phase is about owning stakes in the tools/networks people use.
• AI is framed as the culmination of the read/write era—models and agents that consume, generate, and act on data—making it the natural next target for this ownership wave, even via synthetic pre-IPO derivatives.

Goldman data show tech stocks have lost most of their valuation premium even as earnings forecasts and insider buying rise, while AI models and proxy advisors increasingly side with activists over management. Surveys reveal quantifiable AI gains climbing across sectors, and long-term charts highlight a 94% drop in global oil intensity despite recent supply disruptions.

• Tech stocks' valuation premium has collapsed toward 2018 levels even as 2026 earnings growth forecasts jumped from 31% to 43.4% since January, and insider buying in XLK-tracked firms hit a 15-year high.
• AI models back activist investors in proxy fights ~45% of the time (vs. 36-42% for ISS/Glass Lewis), but actual shareholder votes favor activists only 14% of the time, largely due to the Big Three asset managers' voting power.
• 37% of surveyed companies now report measurable AI benefits, up 23% quarter-over-quarter, with financial services, real estate and tech showing the sharpest gains.

The article critiques the flawed analogy that all money-losing companies are the next Amazon. It discusses how unique circumstances and strategies, like those of Amazon, don't apply universally, using examples like WeWork and Uber to illustrate the dangers of oversimplified comparisons.

• Amazon's early losses were a deliberate strategy under Bezos to prioritize long-term cash flow, not evidence that all unprofitable companies will eventually win big
• WeWork used the "Amazon analogy" to excuse its losses, but its business model couldn't generate the same cash flow, leading to its 2023 bankruptcy
• Uber survived its massive losses because it focused on operational efficiency and customer experience, giving it a real path to profitability that WeWork lacked
• DoorDash succeeded by adapting the Uber model to underserved suburban markets rather than fighting for saturated urban territory

This article discusses how stablecoins are becoming mainstream for online and international payments, drawing parallels to the impact of WhatsApp on messaging costs. It explores the potential for stablecoins to transform financial transactions and reinforce the dollar's dominance in the global economy.

• Stablecoins moved $12 trillion last year, approaching Visa's $17 trillion but at much lower cost — like WhatsApp did to messaging, they're on track to make money transfer nearly free and invisible.
• Real companies are already using them for practical reasons: Stripe/Fidelity cut payment fees, SpaceX routes around broken banking systems in Argentina and Nigeria.
• New US laws (Genius Act, proposed Clarity Act) are giving stablecoins regulatory legitimacy needed for mainstream adoption.
• Circle and Tether already hold ~$140 billion in US government debt (top-20 holder territory), and could become the largest holders of US debt by 2030 — meaning stablecoins are quietly cementing dollar dominance globally.

The ETHval dashboard calculates Ethereum's intrinsic value using ten different valuation methodologies, blending traditional finance approaches with crypto-specific metrics. It aims to provide a more rigorous, fundamentals-based framework for evaluating Ethereum beyond mere price speculation. Feedback and suggestions from users are encouraged.

• ETHval combines ten valuation methodologies—from DCF and P/S ratios to TVL multiples and Metcalfe's Law—to estimate Ethereum's intrinsic value.
• Each model is scored for reliability using three criteria: methodology validation, data objectivity, and sensitivity to assumptions.
• The Revenue Yield model rates highest in reliability due to its acceptance in traditional finance and real-time data grounding, while the TVL Multiple ranks lower for lacking a traditional finance analog and relying on variable assumptions.
• The Staking Scarcity model posits that rising staked ETH reduces liquid supply, potentially pushing prices upward.