Podcasts about indexing

In this episode, we break down the strategic decision to sell a portfolio of boutique hotels in Lake Tahoe, detailing the operational scaling challenges, rising interest rates, and the reality of 24/7 hospitality management. Understanding when to liquidate stabilized assets and redeploy trapped equity is a critical skill for any real estate investor looking to optimize returns and reduce active management stress.Beyond hospitality, we explore the current macroeconomic landscape, highlighting the unprecedented shift toward a buyer's market in housing and the potential impact of indexing capital gains tax to inflation. We also introduce the concept of "eustress" versus distress, providing actionable frameworks for high-performing entrepreneurs to leverage pressure for personal and professional growth.KEY TOPICS DISCUSSEDThe impact of rising interest rates on commercial real estate valuationsScaling challenges and operational realities of boutique hotel investmentsCalculating and understanding cap rates for passive investmentsUtilizing AI agents for investor relations and fund managementThe recent shift to a buyer's market in the US housing sectorProposed capital gains tax cuts and indexing gains to inflationThe psychological difference between distress and eustress for entrepreneursKEY TAKEAWAYSTrapped equity in stabilized real estate assets often yields a lower return, making it essential to unlock and redeploy capital into higher-yielding opportunities.Boutique hotels are 24/7 operating businesses, not just passive real estate, requiring significant scale to support a self-sustaining management team.The housing market currently holds a 51% seller surplus, creating a rare window of leverage for buyers to negotiate concessions before interest rates drop.Indexing capital gains to inflation could unlock stagnant housing supply by eliminating the lock-in effect and phantom profit taxation for long-term property owners.Engineering positive eustress into your routine forces growth and elevation, whereas unmanaged distress degrades focus and health.CONNECT & TAKE ACTIONImagos Income Fund: Text "INCOME" or "DEALS" to 844-447-1555 to learn more about Matty A's private debt fund targeting 10% fixed returns paid out monthly.Visit skylineocresidences.com to discover luxury condo ownership at Skyline OC, Orange County's tallest residential tower. Get a free financial audit on your investment portfolio by texting X-Ray to 844-447-1555

AI isn't just transforming the way we work, but also the way we write the software that people use for work. In this episode, we talk to two engineering productivity leads at Dropbox: Uma Namasivayam, senior director of software engineering productivity, and Anuradha Agarwal, director of software engineering. Whether it's writing tests, fixing bugs, tackling tech debt, or accelerating migrations, they explain how Dropbox engineers are using agentic AI—including in-house tools like Nova—to build the future of Dropbox, and create more space to do impactful work. ~ ~ ~  Working Smarter is brought to you by Dropbox. Find, organize, and share your work—all in one place—with context-aware AI from Dropbox. You can listen to more episodes of Working Smarter on Apple Podcasts, Spotify, YouTube, Amazon Music, or wherever you get your podcasts. To read more stories and past interviews, visit workingsmarter.ai This show would not be possible without the talented team at Cosmic Standard: producer Ben Montoya, sound engineer Aja Simpson, technical director Jacob Winik, and executive producer Eliza Smith. Special thanks to our illustrator Fanny Luor, marketing consultant Meggan Ellingboe, and editorial support from Catie Keck.  Our theme song was composed by Doug Stuart.  Working Smarter is hosted by Matthew Braga. Thanks for listening!

Hey friends! Today's episode comes to you from a parking lot in the rain, with a mint hot cocoa in hand and your host absolutely dragging his butt (D-R-A-G-G-I-N-G, not D-R-A-G-O-N – I've never seen a dragon's butt and can't speak to how mine compares). I've had a bunch of internals back to back lately and I'm basically a drooling dog who found a frisbee and refuses to put it down. Sleep be darned. So instead of walking through one test start to finish, I want to share a few things that have helped me claw out a foothold in environments that are otherwise really locked down: The "good problem" of a mature client – several of these engagements are third- or fourth-year tests, and the clients actually clear findings off the board. Which is great for them and rough for me, because this year's test shouldn't look anything like last year's. All my favorite go-tos came up empty – machine account quota set to zero, no broadcast traffic tomfoolery (Responder and mitm6 got me nothing), SMB signing on everywhere, ADCS either absent or buttoned up, and a low-priv account that BloodHound says has zero interesting permissions and zero local admin anywhere. Cool cool cool. When the network's clean, go file-hunting – which means firing up Snaffler and letting it comb the shares. Normally that wraps up in about an hour. On these engagements it was running three and four hours. Then Windows told me I was out of disk – I like having Snaffler pull down copies of interesting files so I can review them locally instead of authenticating to each share. Turns out it had grabbed 50-60 gigs and left me with about eight gigs of breathing room. Tip #1: put a 1 TB drive in your drop boxes – I ran with tiny drives for years early in the 7MS days and it was always a pinch. Beyond situations like this one, sometimes you find a giant backup file or VMDK on a share and you need somewhere to put it so you can crack it open and go shopping. Tip #2: you can grow a VM disk on the fly – in Proxmox you can resize the disk on a running VM, then hop into Disk Management inside Windows and extend the C drive. Instant elbow room, no downtime. Death by a million tiny files – the real culprit was one file extension I should have excluded, and the client had hundreds of thousands of them. Rather than restart a run I was already hours into, I had AI whip up a little PowerShell loop that swept the Snaffler dump folder every 10 minutes and deleted the extensions I didn't care about. Woke up the next morning to a finished run and plenty of free space. Making a gig-sized log file readable – I fed the log into Chimas, a slick web interface for Snaffler output that lets you filter down to just the red stuff or just the likely-credential files, and sort by modified date. Watch those timestamps – I kept finding AD creds in documents, then comparing the doc's date against the account's last password reset in BloodHound and discovering the file was a year stale. Son of a biscuit. The tool that actually cracked it open: Copernic Desktop Search – my pal Jeff McJunkin recommended this to me years ago, I talked about it on the show once, and then inexplicably forgot about it. Not a sponsor, no kickbacks, just a paid tool that's earned its keep. It's basically Google for your hard drive. How I use it – install it on the Windows VM, clear out the default indexing scope entirely, and point it only at the Snaffler dump folder. The top tier (about a hundred bucks a year) will chew through PSTs, DWGs, Office docs, PDFs and more, and it OCRs images too. Indexing took the better part of a day on these engagements, but then search is instant, and it previews basically every file type without Office installed.  Years ago this same tool surfaced a photo on a file share of a piece of printer paper where a sysadmin had handwritten a 40-character admin password in Bic pen. OCR for the win. What I search for – the obvious stuff like "password," plus the domain name, "plain text," and things like "=sa" to sniff out SQL admin creds. Nuggets and threads to pull – sometimes a hit is the gold. Other times it just tells you where to go dumpster-diving like a raccoon on the live share. That's how I found upgrade project plans with multiple teams and contractors involved, half-cleaned-up temp work, and high-privilege system, database and local admin creds just sitting there. Worth the hours – these didn't all end in domain admin, but they were rich, real findings, and a great teaching opportunity about what's sitting wide open to Domain Users. (Bonus: Copernic can also point straight at a UNC path with your AD creds and index it live.) Know a free alternative? – one of my favorite parts of doing this podcast is when someone writes in with "hey, there's an open source thing that does that." If that's you, I'd love to hear it! Also, on this week's TuesdayTOOLSday I walked through getting a self-hosted Bitwarden password vault (and file sender) up and running on Linux, and there's now a cheat sheet over at 7MinSec.wiki that'll get you there in about seven minutes – all the commands from the official install guide in one place, with a couple of gotchas flagged. Last thing: subscriptions to 7MinSec.club are free, but paid subs help cover hosting and the time this takes each week, and they're getting some exclusive content soon. No guilt trip here, Mom – I'm going to keep barfing up everything I learn either way. But if you've got the means, I'd sure appreciate it.

Send us Fan MailWatch the video!https://youtu.be/gIS4_2GwJJEIn the News blog post for July 31, 2026https://www.iphonejd.com/iphone_jd/2026/07/in-the-news839.html 00:00 Love it. Lease it. Upgrade it.27:19 We Want the NICE Soap, Apple!35:26 Where Y'at? Finding Our Daughters43:12 Pre-Indexing Your iPhone48:12 Faster Charging Valet 51:28 A Cool, No Joke Accessory56:10 Feel Good Lasso58:26 Brett's iTip: Digital Crown Orientation on the Apple Watch1:06:49 Jeff's iTip: Hold Digital Crown for SiriJuli Clover | MacRumors: Apple Upgrade: 20 Things to Know Before Leasing an iPhone, iPad, or MacJohn Gruber | Daring Fireball: John Ternus Should Reverse Apple's Slide Down the Advertising Slippery SlopeJason Snell | Six Colors: Always choose the good soapJohn Gruber | Daring Fireball: Ads in Software Are Like Stickers on LaptopsWilliam Gallagher | AppleInsider: Daughters overjoyed as Apple Watch gift saves their father's lifeZac Hall | 9to5Mac: iOS 26.6 now available for iPhone with these changesAndrew O'Hara | AppleInsider: Twelve South Valet mini review: A luxe MagSafe catch-all with new, faster speedsEd Hardy | Cult of Mac: I got this iPhone accessory as a joke. Now I love it.Brett's iTip: Change the Digital Crown orientation on your Apple Watchhttps://support.apple.com/en-sg/guide/watch/apd0bf18f46b/watchos  Jeff's iTip: Hold Digital Crown to use Sirihttps://support.apple.com/en-us/105063 Support the showBrett Burney from http://www.appsinlaw.comJeff Richardson from http://www.iphonejd.com

AI makes it easier than ever to find and act on information—especially now that teams can connect to and search across all the apps they use for work. So how do you ensure that only the right people and the right tools can access your team's most sensitive content? In this episode, we talk with Jess Jimenez, the head of security at Dropbox, about what security looks like in the age of AI at Dropbox-scale—from building AI products securely to building trust with the people who use them. Jess talks about the importance of access control lists, defending against the latest AI threats, and how Dropbox Protect helps teams securely share content with both humans and AI so they can collaborate more safely. ~ ~ ~  Working Smarter is brought to you by Dropbox. Find, organize, and share your work—all in one place—with context-aware AI from Dropbox. You can listen to more episodes of Working Smarter on Apple Podcasts, Spotify, YouTube, Amazon Music, or wherever you get your podcasts. To read more stories and past interviews, visit workingsmarter.ai This show would not be possible without the talented team at Cosmic Standard: producer Ben Montoya, sound engineer Aja Simpson, technical director Jacob Winik, and executive producer Eliza Smith. Special thanks to our illustrator Fanny Luor, marketing consultant Meggan Ellingboe, and editorial support from Catie Keck.  Our theme song was composed by Doug Stuart.  Working Smarter is hosted by Matthew Braga. Thanks for listening!

If you couldn't talk about performance for 10 minutes, what would you tell a client about the value you provide?Som Seif, Founder and CEO of Purpose Investments, joins Pierre Daillie on Insight Is Capital for a candid, wide-ranging conversation that challenges advisors to confront an uncomfortable truth: the portfolio management skills that built their practices over the last four decades are rapidly becoming a commodity. Seif argues that the 60/40 portfolio, long the default solution for most Canadians, succeeded largely because of a 40-year tailwind of declining interest rates, not because it was the most resilient framework. Now, with inflation structurally embedded, bonds no longer reliably offsetting equity risk, and passive investing producing painful results on the fixed income side, Seif contends that advisors who keep selling their investment sophistication as a value proposition are standing on eroding ground. The real job, he insists, is not to beat a benchmark but to answer one question for every client: Am I going to be okay? Drawing on his experience building both Claymore and Purpose from the ground up, Seif outlines what a truly outcome-driven, goals-anchored advisory practice looks like, and why the greatest financial product ever created, the defined benefit pension, is the experience every advisor should be designing for their clients. The conversation also covers Seif's conviction that Canada stands at a rare structural inflection point, why atoms are replacing bytes as the investment theme of the next decade, and why advisors who stop selling the plumbing and start being genuine accountability partners will not only survive fee compression but actually increase what clients are willing to pay.Timestamped Chapters00:00 Introduction: If you couldn't talk about performance, what's your value?02:00 The 40-year beta environment and why the 60/40 portfolio was never as resilient as advisors believed06:00 Building resilient portfolios: hedging, real assets, alternative credit, and why passive fixed income is broken10:00 Portfolio construction for scenarios, not optimal outcomes: inflation, interest rate regimes, and the role of gold and alternatives15:00 Indexing vs. active management in fixed income today17:00 Home country bias, global diversification, and why Canada may be at a genuine turning point22:00 Atoms vs. bytes: why resources, energy, and infrastructure are the investment themes for the next 20 years26:00 Canada's structural opportunity: talent, IP ownership, tax policy, and what has to change27:00 What it actually means to put holistic, outcome-driven planning at the center of the value proposition29:00 Portfolio management is commoditizing rapidly: the personal trainer as the model for what advisors should become34:00 The hard part: scaling a planning-first practice and linking the plan directly to the portfolio38:00 What statements should actually tell clients: stop showing the plumbing, start showing whether they are on track41:00 The defined benefit pension as the gold standard client experience advisors should be recreating45:00 The iPhone analogy: outpacing commoditization by continuously increasing your service level offering47:00 Fee pressure, the cost of advice, and why Som believes advice fees can actually go up50:00 One thing to do differently on Monday morning: put yourself in your client's shoes #FinancialAdvisor #WealthManagement #InvestmentStrategy #PortfolioManagement #SomSeif #PurposeInvestments #InsightIsCapital #AdvisorAnalyst #GoalsBasedInvesting #FinancialPlanning #ETF #CanadianInvesting #FeeCompression #AdvisorValueProposition #RetirementPlanning #PortfolioResilience #AlternativeInvestments #RealAssets #FixedIncome #BehavioralFinance #FinancialIndependence #WealthBuilding #InvestmentManagement #AdvisorGrowth #ClientExperience

What are Trump Accounts, and could they reshape how families save and invest for the next generation? Richard Rosso & Jonathan McCarty break down how Trump Accounts work, who qualifies, how they're funded, the role of employers and charitable contributions, and how these new custodial accounts compare with traditional UGMA and UTMA accounts. We also discuss investment choices, withdrawal rules, inflation considerations, and the potential addition of publicly traded securities. Beyond the mechanics, we explore the broader goal of improving financial literacy, raising financially responsible children, and avoiding the financial planning mistakes that can undermine long-term wealth. Whether you're a parent, grandparent, financial advisor, or simply curious about this new savings concept, we'll explain what matters most—and what questions still need answers. 0:00 INTRO 0:19 - Sleep Training & Trump Accounts 5:07 - Creating Financial Literacy Lessons? 8:51 - Evolution of Trump Accounts - How are they funded? 12:54 - Allowing publicly traded securities in Trump Accounts 14:51 - Employers' Contributions (Michael Dell donation) 15:53 - Custodial Account Aspects 18:55 - Making the first withdrawal 21:15 - E-bikes & Mopeds (Better Off Dead) 23:38 - UGMA's, UTMA's vs Trump Accounts 25:26 - The choices in Trump Accounts? 28:09 - Indexing for Inflation? 29:41 - The process & custodial choices 32:03 - The Charitable Donation angle 33:24 - The Financial Education Milestones with Trump Account funds 38:26 - Raising Financially Viable Children 40:43 - Financial Planning Minefields 43:38 - Final Thoughts on Trump Accounts Hosted by RIA Advisors Director of Financial Planning, Richard Rosso, CFP, w Senior Investment Advisor, Danny Ratliff, CFP Produced by Brent Clanton, Executive Producer ------- Do you enjoy our content? Rate us on Google: https://bit.ly/4b9JtEo ------- Watch Today's Full Video on our YouTube Channel: https://youtube.com/live/UGqEJxQ6Fls?feature=share ------- Articles mentioned in this report: "Why Retail Traders Consistently Underperform Over Time" https://realinvestmentadvice.com/resources/blog/why-retail-traders-consistently-underperform-over-time/ -------- Watch today's "Before the Bell" premarket commentary, "Markets Eye Earnings as Oil Lifts Yields" https://youtu.be/rWpYjR1_Cxs ------- Watch our previous show, "Why Investors Keep Chasing What's Hot" https://youtube.com/live/-ZZA_xtFZGg?feature=share ------- Get more info & commentary: https://realinvestmentadvice.com/insights/real-investment-daily/ ------- * REGISTER for our next Dynamic Learning Series, "Savvy Social Security Planning: More Income, Less Worry," Thursday, August 6, 2026: https://streamyard.com/watch/tQ3PS8hd64mt --- Visit our Site: https://www.realinvestmentadvice.com Contact Us: 1-855-RIA-PLAN --- Subscribe to SimpleVisor : https://www.simplevisor.com/register-new --- Connect with us on social: https://twitter.com/RealInvAdvice https://twitter.com/LanceRoberts https://www.facebook.com/RealInvestmentAdvice/ https://www.linkedin.com/in/realinvestmentadvice/ #TrumpAccounts #FinancialPlanning #FinancialLiteracy #Investing #RetirementPlanning

What are Trump Accounts, and could they reshape how families save and invest for the next generation? Richard Rosso & Jonathan McCarty break down how Trump Accounts work, who qualifies, how they're funded, the role of employers and charitable contributions, and how these new custodial accounts compare with traditional UGMA and UTMA accounts. We also discuss investment choices, withdrawal rules, inflation considerations, and the potential addition of publicly traded securities. Beyond the mechanics, we explore the broader goal of improving financial literacy, raising financially responsible children, and avoiding the financial planning mistakes that can undermine long-term wealth. Whether you're a parent, grandparent, financial advisor, or simply curious about this new savings concept, we'll explain what matters most—and what questions still need answers. 0:00 INTRO 0:19 - Sleep Training & Trump Accounts 5:07 - Creating Financial Literacy Lessons? 8:51 - Evolution of Trump Accounts - How are they funded? 12:54 - Allowing publicly traded securities in Trump Accounts 14:51 - Employers' Contributions (Michael Dell donation) 15:53 - Custodial Account Aspects 18:55 - Making the first withdrawal 21:15 - E-bikes & Mopeds (Better Off Dead) 23:38 - UGMA's, UTMA's vs Trump Accounts 25:26 - The choices in Trump Accounts? 28:09 - Indexing for Inflation? 29:41 - The process & custodial choices 32:03 - The Charitable Donation angle 33:24 - The Financial Education Milestones with Trump Account funds 38:26 - Raising Financially Viable Children 40:43 - Financial Planning Minefields 43:38 - Final Thoughts on Trump Accounts Hosted by RIA Advisors Director of Financial Planning, Richard Rosso, CFP, w Senior Investment Advisor, Danny Ratliff, CFP Produced by Brent Clanton, Executive Producer ------- Do you enjoy our content? Rate us on Google: https://bit.ly/4b9JtEo ------- Watch Today's Full Video on our YouTube Channel: https://youtube.com/live/UGqEJxQ6Fls?feature=share ------- Articles mentioned in this report: "Why Retail Traders Consistently Underperform Over Time" https://realinvestmentadvice.com/resources/blog/why-retail-traders-consistently-underperform-over-time/ -------- Watch today's "Before the Bell" premarket commentary, "Markets Eye Earnings as Oil Lifts Yields" https://youtu.be/rWpYjR1_Cxs ------- Watch our previous show, "Why Investors Keep Chasing What's Hot" https://youtube.com/live/-ZZA_xtFZGg?feature=share ------- Get more info & commentary: https://realinvestmentadvice.com/insights/real-investment-daily/ ------- * REGISTER for our next Dynamic Learning Series, "Savvy Social Security Planning: More Income, Less Worry," Thursday, August 6, 2026: https://streamyard.com/watch/tQ3PS8hd64mt --- Visit our Site: https://www.realinvestmentadvice.com Contact Us: 1-855-RIA-PLAN --- Subscribe to SimpleVisor : https://www.simplevisor.com/register-new --- Connect with us on social: https://twitter.com/RealInvAdvice https://twitter.com/LanceRoberts https://www.facebook.com/RealInvestmentAdvice/ https://www.linkedin.com/in/realinvestmentadvice/ #TrumpAccounts #FinancialPlanning #FinancialLiteracy #Investing #RetirementPlanning

In this episode of 'Retire with Style', Wade Pfau and Alex Murguia dive into the implications of the SpaceX IPO, exploring its unique characteristics, the risks associated with investing in IPOs, and the historical performance of such investments. They discuss the impact of index funds on IPOs and the broader lessons investors should consider when navigating the market, particularly in light of the excitement surrounding mega IPOs like SpaceX. Listen now to learn more!   Takeaways SpaceX's IPO is historically unique due to its unprecedented size. Investors should be cautious about the hype surrounding IPOs. Historical data shows that IPOs often underperform compared to established companies. The excitement of an IPO does not guarantee a good investment. Index funds can create forced buying and selling dynamics during IPOs. Investors should understand the methodology behind index funds. Not all IPOs are created equal; some may not be profitable. The performance of passive funds can vary significantly based on index rules. Investors should focus on long-term strategies rather than chasing trends. Understanding the risks associated with mega IPOs is crucial for investment success. Chapters 00:54 The Unique SpaceX IPO 04:05 Investor Sentiment and IPO Risks 07:03 Historical Performance of IPOs 11:59 Impact of Index Funds on IPOs 18:00 Broader Lessons for Investors   Links

Should you panic when your Search Console indexing report is showing pages that aren't indexed? Is a 404 error code always a sign of a broken website? In this episode of Search Off the Record, Martin Splitt and John Mueller from the Google Search Relations team dive deep into the Page Indexing report in Google Search Console. They unpack why treating this report as a static inventory checklist to "fix" things is the wrong response, how to spot massive SEO-ruining hosting or CDN traps, and why a healthy website doesn't actually need a 100% index rate. In this episode, you'll learn: The Indexing Report Shift: Insights from the Search Console team's Hillel on why you should look for trend lines and systemic patterns rather than treating the report as a giant list of errors. When 404s are Good: Why expected 404 errors are technically correct for deleted content, and how to survive the "boss panic" of numbers that won't go down. The Domain Property Advantage: How setting up a domain property handles canonical shifts, www vs. non-www tracking, and performance data much cleaner. The Site Query vs. Search Console: Why the site: query is an artificial tool that might show old domain moves or hreflang swaps for years, making Search Console your only true source of truth. Hosting & CDN Traps: How aggressive bot protections, hidden interstitials, and "Soft 200" error pages completely destroy your crawl data and lead to malicious canonicalization. Discovered vs. Crawled: What it actually means when pages sit in "Discovered/Crawled - currently not indexed," and how to recognize holistic site quality issues over technical bugs. Key Takeaways for SEOs & Developers: Patterns over Inventories: Use the report to verify that your intentional changes (like site migrations or page removals) are processing correctly over time. Forget the Ratio: There is no magic metric for indexed vs. non-indexed pages. Even Google's own developer documentation has a massive chunk of non-indexed content due to intentional choices. Watch Out for Soft Blocks: Ensure your security layers or CDNs aren't serving "Are you a bot?" challenge screens to Googlebot with a 200 success code. Computers Fail (And That's Fine): Minor server blips, failed DNS requests, or temporary 500 errors happen. Google's systems are resilient and will just try again later.   Chapters 0:00 - Introduction: The Search Central Live coverage report confusion. 1:45 - Shifting perspectives: Treating Search Console as a pattern tracker, not a checklist. 4:36 - Tracking site migrations and processing data delays. 6:25 - Why 404 errors can be a good thing  8:00 - Handling canonical shifts and the value of Domain Properties. 11:12 - Why the site: query isn't telling you what you think it does (Domain moves and hreflang bugs). 13:38 - CDN bot protection and the absolute nightmare of soft error pages. 17:49 - How to use "marked as fixed". 20:32 - Discovered vs. Crawled Not Indexed: Is it a technical or site quality issue? 25:31 - Debunking the indexed-to-non-indexed ratio myth. 27:48 - Final verdict: How to stop fearing your Indexing Report. Resources Mentioned: Google Search Central: https://developers.google.com/search Google Search Console: https://search.google.com/search-console Search Central Live Events: https://developers.google.com/search/events    Are you actively stressing over your non-indexed page counts, or are you tracking the big trend lines? Let us know in the comments! Episode transcript →  https://goo.gle/sotr112-transcript   Listen to more Search Off the Record → https://goo.gle/sotr-yt  Subscribe to Google Search Channel → https://goo.gle/SearchCentral   Search Off the Record is a podcast series that takes you behind the scenes of Google Search with the Search Relations team.  #SOTRpodcast #SEO #GoogleSearch #SearchConsole Speakers: Martin Splitt, John Mueller

Not all work happens in writing. Teams that work with photos, videos, and audio need AI that works for them too. This is why, with Dropbox, you can search within multimedia content for key moments and important information—not just text. In this episode, we talk with Appu Shaji and Hicham Badri, two Dropbox machine learning engineers who are part of the team that makes all of this possible. They explain how multimodal search works—from understanding the context of the initial query, to identifying objects and actions in complex scenes—and how they ensure those models work fast, even at Dropbox-scale. ~ ~ ~  Working Smarter is brought to you by Dropbox. Find, organize, and share your work—all in one place—with context-aware AI from Dropbox. You can listen to more episodes of Working Smarter on Apple Podcasts, Spotify, YouTube, Amazon Music, or wherever you get your podcasts. To read more stories and past interviews, visit workingsmarter.ai This show would not be possible without the talented team at Cosmic Standard: producer Ben Montoya, sound engineer Aja Simpson, technical director Jacob Winik, and executive producer Eliza Smith. Special thanks to our illustrator Fanny Luor, marketing consultant Meggan Ellingboe, and editorial support from Catie Keck.  Our theme song was composed by Doug Stuart.  Working Smarter is hosted by Matthew Braga. Thanks for listening!

In this Azure Friday episode, Scott Hanselman and Sajee demonstrate the Azure Cosmos DB Agent Kit — a skill you install with one command that gives your coding agent 100+ Cosmos DB best-practice rules across data modeling, partitioning, query optimization, and SDK usage and much more. Using a multi-agent fitness coaching app as an example, they show how the kit caught a missing partition key filter that was leaking member data across tenants, recommended hierarchical partitioning for multi-tenant scale, and fixed a fan-out query—all before the code shipped to production. Chapters 00:00 - Introduction 00:33 - Meet Sajee & overview of the Cosmos DB Agent Kit 00:50 - The problem: partition key & query mistakes that cost money in production 02:32 - How the Agent Kit works: one install, 100+ rules across 12 categories 04:52 - Demo setup: fitness coaching multi-agent app with Cosmos DB 06:26 - Showing the data: missing partition key filter exposes other members' data 08:23 - Agent Kit findings: SQL injection, singleton pattern, fan-out queries 10:46 - Indexing best practices & query optimization recommendations 12:34 - Applying the fix: correct results and single-partition RU cost 13:13 - Wrap up & how to get started Recommended resources Azure Cosmos DB Agent Kit Agent Kit Repository Connect Scott Hanselman | Twitter/X: @SHanselman Sajeetharan | Twitter/X: @sajeetharan Azure Friday | Twitter/X: @AzureFriday Azure | Twitter/X: @Azure

In this Azure Friday episode, Scott Hanselman and Sajee demonstrate the Azure Cosmos DB Agent Kit — a skill you install with one command that gives your coding agent 100+ Cosmos DB best-practice rules across data modeling, partitioning, query optimization, and SDK usage and much more. Using a multi-agent fitness coaching app as an example, they show how the kit caught a missing partition key filter that was leaking member data across tenants, recommended hierarchical partitioning for multi-tenant scale, and fixed a fan-out query—all before the code shipped to production. Chapters 00:00 - Introduction 00:33 - Meet Sajee & overview of the Cosmos DB Agent Kit 00:50 - The problem: partition key & query mistakes that cost money in production 02:32 - How the Agent Kit works: one install, 100+ rules across 12 categories 04:52 - Demo setup: fitness coaching multi-agent app with Cosmos DB 06:26 - Showing the data: missing partition key filter exposes other members' data 08:23 - Agent Kit findings: SQL injection, singleton pattern, fan-out queries 10:46 - Indexing best practices & query optimization recommendations 12:34 - Applying the fix: correct results and single-partition RU cost 13:13 - Wrap up & how to get started Recommended resources Azure Cosmos DB Agent Kit Agent Kit Repository Connect Scott Hanselman | Twitter/X: @SHanselman Sajeetharan | Twitter/X: @sajeetharan Azure Friday | Twitter/X: @AzureFriday Azure | Twitter/X: @Azure

Favour Obasi-ike, MBA, MS frames the discussion around the core distinction: broke (or broken) business websites vs pro (professional) business websites. A “broke” site often lacks structure, SEO, technical setup, and consistently underperforms, whereas a professional site is organized, optimized, and positioned for visibility, lead generation, and business growth 00:00:03, 00:05:16.Who Is This For?This episode is for business owners, entrepreneurs, and marketers—especially those responsible for their company's website and digital visibility. If you want practical, plain English insights into why your site isn't performing, how to spot technical flaws, and how to finally turn a “broken” website into a professional, revenue-driving asset, this is for you.Key Moments & TimestampsIntro & Website Audit Tools:00:00:03 - [Favour Obasi Ike] introduces the concept of "broke" vs. "pro" business websites and tools like Siteliner.com and GTMetrix to self-audit your site.Technical SEO & Why Sites Don't Rank:00:05:00 - 70% of ranking problems are technical, not content-based.00:07:00 - Explains the impact of page speed, broken links, and crawl errors.Site Architecture & Structure:00:12:06 - A “pro” site has a solid checklist, logical URL structure, all main pages (home, about, contact, etc.), and no duplicates or broken paths.Importance of Social, Content, and Indexing:00:10:15 – Social profiles now connect with Google Search Console; cohesive digital presence is critical.00:33:05 – Explains sitemaps, robots.txt, and how to check what pages Google sees vs. your actual site.Schema, Quality Content, and Velocity:00:48:23 – Why schema (structured data) is often missing and critical for SEO.01:11:28 – Content must attract and repel with clarity; use action-oriented headlines and answer real user questions.Budgets, DIY, and Final Advice:01:05:01 – Discusses real costs for professional sites, why you must invest money or time, and how “broke” sites result from neglect.01:23:29 – Final takeaways: clarity in copy, investing in continual learning, and practical analytics checks.SummarizeTechnical SEO is usually the culprit for low rankings—not just content issues. Site speed, mobile performance, clean architecture, and meta info (titles, descriptions) matter much more than flashy design.Sitemaps and robots.txt must be properly configured, or Google may ignore much of your site.Schema markup is almost always missing on poorly performing sites and can boost visibility.Consistent, high-quality content (using real user questions as headline structure) increases both visibility and engagement.Organic social and SEO now interact—Google draws from your digital presence as a whole.DIY is an option, but you must invest time if you can't invest money.Monitor click-through and conversion metrics (above 2% is good; below, revisit your site's value/clarity).FAQsQ: What free tools can I use to audit my site?A: Siteliner.com checks duplicate/broken pages; GTMetrix.com measures speed; NSLookUp.io checks domain health.Q: What's the most common reason websites don't rank?A: Technical SEO issues: slow speed, crawl errors, missing/incomplete sitemaps, improper robots.txt, lack of schema.Q: Is a newsletter/blog/journal page worth it?A: Yes—having unique, frequently updated content (news, blogs, resources) helps with indexing, authority, and user engagement 00:43:10.Q: Can I get a professional site cheaply?A: Investing either time (DIY, free learning resources) or money (professionals, payment plans) is required. Q: What defines a “pro” website?A: Fast, mobile-first, well-structured, SEO-optimized, schema'd, secure, maintained, and delivers what users expect—every time.Action StepsAudit your site using Siteliner, GTMetrix, and NSLookUp to identify technical flaws (00:01:38).Create or download a checklist for on-page, off-page, technical, and local SEO (00:05:48).Clean up your site map and robots.txt.Apply schema markup to each main page (00:48:23).Ensure all key pages exist: home, about, contact, products/services, privacy, FAQ, blog/newsletter (00:13:51).Update your titles/descriptions to include search terms and local info; keep within pixel/character limits (00:29:13).Track your conversions; if below 2%, revisit clarity, speed, mobile, and copy (01:27:24).Invest in learning if budget is tight (use LinkedIn Learning, online resources) or hire a pro with phased payments.Monitor progress and repeat regular checks to maintain a “pro” business website.For more strategies, connect directly via the podcast resources shared at the conclusion of the episode.

Today on the podcast, we're delighted to welcome back Jeremy Grantham to discuss his book, The Making of a Permabear: The Perils of Long-term Investing in a Short-term World, which he co-authored with Edward Chancellor. Jeremy is the long-term investment strategist at his namesake firm, Grantham, Mayo, Van Otterloo & Company, or GMO, which he co-founded in 1977. He serves on GMO's asset-allocation committee and board of directors. Prior to GMO, Jeremy was co-founder of Batterymarch Financial Management and, before that, was an economist at Royal Dutch Shell. He earned his undergraduate degree from the University of Sheffield and his MBA from Harvard University. Jeremy is a member of the Academy of Arts and Sciences, holds a CBE from the UK, and is a recipient of the Carnegie Medal of Philanthropy. In 1997, he and his family started the Grantham Foundation for the protection of the environment, which supports research and action to address climate change. Episode Highlights 00:00:00 Writing Permabear With Edward Chancellor 00:06:44 Value Investing and Identifying Market Bubbles 00:15:07 Current Market Outlook and Valuation Risks 00:20:28 Value Discipline, SpaceX's IPO, and Past Market Bubbles 00:27:26 Speculative Trading, Indexing, and Zero‑Sum Markets 00:34:24 Market Inefficiencies, Small-Cap Stocks, and the Greater Fool Theory 00:43:27 Artificial Intelligence Hype, Attractive Assets, and Market Pessimism 00:47:02 Climate Risks, Resource Constraints, and Shrinking Populations More From Morningstar 3 Warnings for Investors From the Ultimate Contrarian Ben Carlson: Exploring Risk and Reward What Today's Index ETFs Get Right, and Wrong, for Investors If you have a comment or a guest idea, please email us at TheLongView@Morningstar.com. Follow Christine Benz (@christine_benz) and Ben Johnson (@MstarBenJohnson) on X, and Christine Benz, Amy Arnott, and Ben Johnson on LinkedIn. Visit Morningstar.com for new research and insights from Christine, Ben, and Amy. Subscribe to Christine's weekly newsletter, Improving Your Finances. If you want more Morningstar podcasts, check out The Morning Filter and Investing Insights. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

When AI is at its best, the conversations can feel uncanny—almost magical in their accuracy, relevance, and speed. For that you can thank the AI agents that work together behind the scenes to search, reason, and sift through all your content to get you what you need to do your job. We talk with Jongmin Baek and Marta Mendez, two Dropbox machine learning engineers, about building conversational AI that's helpful, useful, and grounded in your team's shared context, so you can spend more time on the work that really matters. ~ ~ ~  Working Smarter is brought to you by Dropbox. Find, organize, and share your work—all in one place—with context-aware AI from Dropbox. You can listen to more episodes of Working Smarter on Apple Podcasts, Spotify, YouTube, Amazon Music, or wherever you get your podcasts. To read more stories and past interviews, visit workingsmarter.ai This show would not be possible without the talented team at Cosmic Standard: producer Ben Montoya, sound engineer Aja Simpson, technical director Jacob Winik, and executive producer Eliza Smith. Special thanks to our illustrator Fanny Luor, marketing consultant Meggan Ellingboe, and editorial support from Catie Keck.  Our theme song was composed by Doug Stuart.  Working Smarter is hosted by Matthew Braga. Thanks for listening!

Thanks to fast-tracking, SpaceX is already part of the Russell 1000 and soon to be part of Nasdaq 100. Will other mega-IPOs pursue the same route to adoption and what could it mean for index-tracking ETFs?         Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Tom welcomes legendary investor educator and longtime friend Paul Merriman for a wide-ranging conversation about the evolution of indexing, the proposed changes to the S&P 500, and why investors should understand both the strengths and limitations of traditional index funds. Paul explains why firms like Dimensional Fund Advisors and Avantis Investors use a more flexible, evidence-based approach than traditional indexing and discusses how academic research has reshaped portfolio construction over the past several decades.The discussion also explores lessons from market history, including the importance of understanding major bear markets, determining appropriate risk levels, and building portfolios that align with personal goals rather than chasing maximum returns. Paul shares insights from the latest Dimensional Matrix Book and explains why he believes studying 100 years of market data helps investors stay disciplined during inevitable downturns.Finally, Paul introduces a simple but powerful strategy for helping newborns and young children build substantial retirement wealth through small annual investments that can compound over many decades.Timestamps0:11 Special guest Paul Merriman joins Talking Real Money0:55 Long friendship and investing partnership between Tom and Paul1:20 S&P 500 rule changes and earlier inclusion of major IPOs like SpaceX2:07 Historical examples of S&P 500 additions and omissions2:35 Microsoft's delayed entry into the S&P 5002:56 NVIDIA replacing Enron in 20013:29 How index rule changes can affect future returns and volatility4:08 Why indexing remains the preferred strategy for most investors5:16 Traditional versus non-traditional index funds6:37 How Avantis and Dimensional incorporate factors beyond company size8:05 Why factor-based investing differs from traditional indexing9:02 Problems with rigid index reconstitution schedules10:16 Momentum, flexibility, and portfolio management advantages11:22 Introduction to Dimensional's annual Matrix Book11:53 Using market history rather than forecasts to guide investing decisions13:09 Lessons from past bubbles, crashes, and lost decades14:20 Why Paul trusts academic research more than Wall Street forecasts15:14 The case for small-cap value investing15:49 Clarifying Paul's allocation to small companies16:53 Investing for heirs, charities, and future generations18:10 Remembering investor panic during the 2008 financial crisis19:18 Determining an appropriate risk level for retirement portfolios20:43 Different investor goals: beating the market, maximizing returns, or minimizing risk21:28 Peace of mind versus maximum growth21:55 Helping young people build retirement wealth early22:54 The $365-per-year retirement funding concept24:09 Final thoughts and appreciation between Tom and PaulQuestions? Comments? Click!

How do you build AI that actually understands you and the work you do? It all starts with having the right context.  We talk with Dropbox staff product manager Noorain Noorani and principal engineer Sean-Michael Lewis about the art of context engineering and how Dropbox connects to all the tools your team needs for work—so you get AI that works wherever you do.  ~ ~ ~  Working Smarter is brought to you by Dropbox. Find, organize, and share your work—all in one place—with context-aware AI from Dropbox. You can listen to more episodes of Working Smarter on Apple Podcasts, Spotify, YouTube, Amazon Music, or wherever you get your podcasts. To read more stories and past interviews, visit workingsmarter.ai This show would not be possible without the talented team at Cosmic Standard: producer Ben Montoya, sound engineer Aja Simpson, technical director Jacob Winik, and executive producer Eliza Smith. Special thanks to our illustrator Fanny Luor, marketing consultant Meggan Ellingboe, and editorial support from Catie Keck. Our theme song was composed by Doug Stuart.  Working Smarter is hosted by Matthew Braga. Thanks for listening!

Don takes listeners on a journey through nearly four decades of investment advice, explaining how his thinking evolved from recommending active mutual funds in the 1980s to embracing index funds, factor investing, and eventually ETFs. Along the way, he and Tom discuss Vanguard's rise, Don's early relationship with Paul Merriman, the emergence of Dimensional Fund Advisors and Avantis, and why their recommendations have changed over time. They also address listener skepticism about fund recommendations, compare Avantis and Vanguard products, answer a tax-efficient portfolio rebalancing question from a retired couple, and debunk a marketing pitch for “layered income portfolios.”0:08 Don shares the story of his early days giving investment advice from Leadville, Colorado2:56 The active management era and why great fund managers were once considered essential3:52 Vanguard's early growth and the gradual acceptance of index investing5:38 Don discusses Vanguard sponsoring his radio show and maintaining disclosure transparency6:55 Paul Merriman introduces factor investing and Fama-French research9:10 Early Dimensional Fund Advisors portfolios and advisor-only access10:56 The rise of ETFs, Dimensional's hesitation, and Avantis' origins11:23 The 2010 ETF flash crash and why Tom and Don were initially cautious13:29 Why factor investing remains compelling despite uncertain future returns14:20 Addressing listener skepticism about Avantis recommendations16:07 Comparing AVUV and Vanguard VBR small-cap value funds17:44 Comparing AVGE and Vanguard VT global equity funds19:15 Clarifying compensation, conflicts of interest, and transparency21:27 Listener Anton asks about tax-efficient portfolio rebalancing in retirement26:03 Why holding bonds inside IRAs can improve tax efficiency27:23 Discussion of Roth conversion strategies and tax considerations30:20 Listener asks about “Layered Income Portfolios”31:05 Why income portfolio marketing pitches are often more sales than substanceQuestions? Comments? Click!

Modern work can be frustrating and chaotic—if you don't have the right tools. From context engineering to multimodal search, go behind the scenes and hear how Dropbox engineers are building AI that actually understands you, so you can focus on the work that matters most. If you're new to Working Smarter, we've travelled from the F1 track to the bottom of a lake, and heard real stories from chefs, doctors, lawyers, and founders about how AI is helping them do more of what they love about their jobs. But in our third season, we're talking to the people behind the tools—the engineers and product leaders building helpful, time-saving AI features into the Dropbox experience you already know and trust. You'll hear all about their work on agents, inference, security, and, of course, how the people building AI use AI themselves. ~ ~ ~  Working Smarter is brought to you by Dropbox. Find, organize, and share your work—all in one place—with context-aware AI from Dropbox. You can listen to more episodes of Working Smarter on Apple Podcasts, Spotify, YouTube, Amazon Music, or wherever you get your podcasts. To read more stories and past interviews, visit workingsmarter.ai This show would not be possible without the talented team at Cosmic Standard: producer Ben Montoya, sound engineer Aja Simpson, technical director Jacob Winik, and executive producer Eliza Smith. Special thanks to our illustrator Fanny Luor, marketing consultant Meggan Ellingboe, and editorial support from Catie Keck.  Our theme song was composed by Doug Stuart.  Working Smarter is hosted by Matthew Braga. Thanks for listening!

Vanguard is the most effective vehicle ever created for participating in the fruits of American capitalism. Today it's the single largest equity owner of the majority of corporations in the S&P 500, on behalf of 50 million clients (including, likely, many of you). And yet Vanguard itself is essentially a communist organization — it has no shareholders, makes no profits, and operates more like REI than Fidelity. If you own a Vanguard fund, you own a piece of the firm itself. Any excess margin instead gets returned to clients in the form of lower fees, which since 1975 have added up to roughly five hundred billion dollars transferred out of Wall Street managers' pockets and into retail investors' savings accounts. And oh yeah, it all started as a cockamamie revenge plot by a guy who'd just been fired by his partners. Today we tell the story of communist capitalism at its finest — Vanguard.Sponsors:Many thanks to our fantastic Spring '26 Season partners:J.P. MorganWeAreDevelopers eventServiceNowVercelStatsigLinks:Sign up for email updates, get our takeaways and research photos from each episode, and vote on future topics!Our Vanguard "episode preview" in WSJStay the Course: The Story of Vanguard and the Index Revolution by John C. BogleThe Bogle Effect by Eric BalchunasWorldly Partners' Multi-Decade Vanguard StudyWorldly Partners' Article Generational Investing: The Discipline Behind 100+x OutcomesAll episode sourcesCarve Outs:Our WSJ pieces on Ferrari and VanguardMacBook Pro M5 MaxMichael MacKelvie on YouTubeThe Super Mario Galaxy MovieBrooks Vanguard sneakersMore Acquired:Get email updates and vote on future episodes!Join the SlackCheck out the latest swag in the ACQ Merch Store!00:00:00 Start00:00:41 Intro00:05:30 Jack Bogle's Early Life & Family Ruin (1929)00:12:34 Princeton Thesis & Mutual Funds Emerge (1949-1951)00:27:20 Joining Wellington Management (1951)00:30:38 The Go-Go Years & Fidelity's Ascent (1958-1965)00:40:36 Jack Takes the Reins & The Ivest Merger (1965)00:46:04 The Go-Go Bust & Jack's Crisis of Conscience (1970-1973)00:53:28 Jack is Fired: The Genesis of Vanguard (1974)01:13:03 The Journal Article That Inspired It All (1974-1976)01:35:02 Building the Fund & Early Struggles (1976-1981)01:44:32 The Rise of Indexing & Vanguard's Growth (1988-1992)01:49:06 Jack's Health & The CEO Transition (1995-1996)02:00:06 The ETF Debate & Jack's Second Firing (1999)02:24:18 The 2008 Financial Crisis: Vanguard's Moment02:30:46 The Warren Buffet Bet (2008-2019)02:41:28 Fidelity & BlackRock's Resurgence (Post-2008)02:52:04 Salim Ramji: Vanguard's First Outside CEO03:04:43 Wellington's Comeback & Mutual Ownership03:08:23 Analysis03:30:58 Quintessence03:39:35 Carve-Outs + Outro‍Note: Acquired hosts and guests may hold assets discussed in this episode. This podcast is not investment advice, and is intended for informational and entertainment purposes only. You should do your own research and make your own independent decisions when considering any financial transactions.

Adam Gent returns to Search with Candour to discuss how Google's indexing works and why large websites should monitor it closely.Adam explains that statuses like “URL unknown to Google” can mean Google has deprioritised and effectively forgotten pages, and that Search Console may misreport or fail to alert when pages are actively de-indexed. He describes a “130-day rule” for indexing, where low page quality can affect the status of existing pages.They also cover index bloat on large websites, the importance of long-term indexing, and practical steps like segmenting sitemaps by site sectioning or seasonality.Follow AdamIndexing InsightFollow Adam on LinkedInFollow Adam on BlueskyAdam at SearchNorwichXLChapters00:00 Highlight reel of Adam Gent01:40 Introduction04:57 Why index monitoring matters08:11 Search Console blind spots10:29 URL unknown to Google13:13 Why Adam built Indexing Insight14:04 The 130-day rule for indexing15:28 What page quality means21:36 Site sections and patterns29:37 Index bloat on big sites32:20 Cleaning up for AI visibility33:51 Indexing ratios that matter36:44 Is indexing getting harder37:33 Short-term vs long-term indexing40:50 Demand-led recovery44:29 Indexing misconceptions explained48:39 Sitemaps for seasonality52:11 Reducing Search Console noise55:44 Recommendations01:03:15 Wrap up

Favour Obasi-ike, MBA, MS breaks down the semantic web SEO concept of "page indexing," explaining that it is simply the process by which search engines discover, crawl, and store your web pages in their database. Using a library analogy, he explains that just as a library must log a newly purchased book before patrons can find it on the shelf, Google must index your pages before users can discover them in search results.Favour emphasizes that high-quality content is practically invisible if it hasn't been properly indexed.He also walks the audience through the technical steps of verifying a domain via Google Search Console and stresses the importance of owning your hosting and DNS records.Who is this for?This content is tailored for business owners, content creators, podcasters, and website managers who want to understand fundamental SEO concepts to increase their online visibility and website traffic.Key MomentsSegment 1: Introduction to page indexing and how it builds long-term business visibility.Segment 2: Step-by-step technical guide to setting up Google Search Console and submitting sitemaps.Segment 3: Understanding how accidental "no-index tags" can hide your website from the internet.Segment 4: How third-party platforms (like Apple Podcasts and Spotify) generate indexed links that boost your search presence.Segment 5: The "Library Analogy" explaining why indexing is simply digital storage.Segment 6: The importance of controlling your Domain Name Server (DNS) and hosting platforms.FAQsWhat is page indexing?It is the process where search engines discover, crawl, and store web pages into their database, making them searchable and eligible to appear in search results. Ultimately, indexing simply means "storage on the web".Why isn't my website showing up on Google?Your site might not be indexed. This can happen if you haven't submitted your sitemap to Google Search Console, or if your site has default "no-index tags" that actively tell Google to ignore your pages.Does podcasting help with indexing?Yes. When you publish a podcast episode to platforms like Apple, Spotify, or Amazon, each of those platforms creates a link that gets indexed by Google, multiplying your online footprint.What is a DNS and why does it matter?DNS stands for Domain Name System or Server. It connects your domain to your hosting platform. You must have access to your DNS records to verify your site ownership with Google and ensure you maintain full operational control over your business's online presence.Action Steps Recommended by Favour Obasi-ikeCheck your site status: Use a tool like nslookup.io to research your website's domain records.Set up Google Search Console: Go to Google Search Console and add your domain property.Verify your domain: Copy the provided TXT record and add it to your DNS records within your hosting platform to prove you own the site.Submit your sitemap: Once verified, submit your sitemap (e.g., yourwebsite.com/sitemap.xml) to Google Search Console to prompt Google to scan your pages.Audit your hosting setup: Ensure you have direct, personal access to your own domain name server and hosting plan to avoid losing control of your intellectual property.Ready to Rank? Book Your SEO & Web Dev Services Today

The growth of the portfolio solutions segment of the market has been one of the most exciting and interesting developments in global insurance in the past five years. The streamlining of placements in syndicated insurance markets is producing scale, speed efficiency and cost benefits for underwriters, brokers and their clients alike. And this is a phenomenon that is really only just getting into its stride. Billions of dollars of premium are now being transacted this way as brokers look to facilitise significant percentages of their placements while consortia and other underwriting pooling arrangements proliferate. As Director of QBE Portfolio Solutions, Tessa Wardle runs one of the lead markets for this pioneering form of delegated authority underwriting and collectively her small team underwrite on a scale that in premium terms is many multiples of that achieved by conventional market underwriters. In this podcast we look at where this phenomenon is likely to be heading, as well as delving into the core mechanics of just how business of such a high volume is transacted in practice. What are the core skills of a portfolio solutions underwriter and how do they differ from conventional underwriting practice? And what are the principle levers and controls that senior executives like Tessa have at their disposal to keep these huge contracts on track? It's a fascinating world that is in many ways revolutionary, but in many others reassuringly familiar. Tessa is an excellent guest and one of the best qualified people to guide us through this huge change in global insurance business flows and give us an idea of where the trend will be heading as it matures. LINKS: We thank our naming sponsor AdvantageGo, now part of Sapiens: https://www.advantagego.com

Rodney Comegys is the CIO of Vanguard Capital Management and its Head of Global Equity Indexing, where he oversees $8.5 trillion in index assets across domestic, international, and multi-asset strategies. Rodney joined Vanguard twenty seven years ago and has worked across operations, customer service, risk management, and investing.    Our conversation covers the philosophy and mechanics behind running one of the world's largest index fund operators. We discuss Vanguard's ownership structure, values, product selection, and mechanics of delivering an index fund. We then turn to common issues around indexing, including concentration in U.S. equities, corporate governance, private assets, and AI.  Learn more about our Strategic Investments: Thema. Learn More Follow Ted on Twitter at @tseides or LinkedIn Subscribe to the mailing list Access Transcript with Premium Membership   Editing and post-production work for this episode was provided by The Podcast Consultant (⁠https://thepodcastconsultant.com⁠)

1. Eric Swalwell Campaign Collapse Eric Swalwell reportedly ended/suspended his campaign for California governor after multiple sexual misconduct allegations. Allegations include sexual assault, rape, unwanted contact, and inappropriate behavior, some allegedly involving intoxicated individuals. The Manhattan District Attorney’s Office is described as opening a criminal investigation, raising potential legal exposure. Around 50 former staffers publicly condemned Swalwell, suggesting alleged behavior was widely known. Swalwell denies all allegations, calling them false and politically motivated. 2. Democratic Party Hypocrisy and Political Calculations The speaker claims Democrats: Are calling for Swalwell to suspend his campaign, but not resign from Congress, due to narrow House margins. Act only when misconduct threatens electoral chances rather than out of concern for victims. California’s “jungle primary” system is highlighted as a reason Democrats panicked, since two Republicans could theoretically advance to the general election. The segment accuses Democrats of double standards, comparing Swalwell’s situation with other Democratic lawmakers allegedly facing ethics violations. 3. Republican Strategy: Reconciliation and Legislative Urgency A Republican lawmaker argues this is the last realistic window to pass conservative priorities before likely midterm losses. Advocates for a large-scale budget reconciliation bill with “tentpole” items such as: Long-term funding for ICE and CBP Preventing government shutdowns Indexing capital gains taxes to inflation Airport and TSA funding guarantees Election integrity provisions tied to federal funding Criticism of past Republican leadership (including Mitch McConnell) for failing to use reconciliation aggressively. 4. New York City Luxury Property Tax Criticism Focuses on NYC politician (Mamdani) promoting a “pied-à-terre” tax on luxury second homes over $5 million. The tax aims to raise $500 million annually to fund social programs. Commentary portrays the policy as: Anti-wealth, vindictive, and punitive Likely to accelerate wealth and job flight from NYC Examples cited include: Ken Griffin (Citadel) Elon Musk leaving California for Texas Claims that high taxes drive businesses and wealthy individuals to lower-tax states, harming long-term economic health. Please Hit Subscribe to this podcast Right Now. Also Please Subscribe to the 47 Morning Update with Ben Ferguson and The Ben Ferguson Show Podcast Wherever You get You're Podcasts. And don't forget to follow the show on Social Media so you never miss a moment! Thanks for Listening YouTube: https://www.youtube.com/@VerdictwithTedCruz/ Facebook: https://www.facebook.com/verdictwithtedcruz X: https://x.com/tedcruz X: https://x.com/benfergusonshowYouTube: https://www.youtube.com/@VerdictwithTedCruzSee omnystudio.com/listener for privacy information.

DHS Shutdown & Democratic Opposition An extended shutdown continues of the Department of Homeland Security (DHS), leaving approximately 200,000 employees unpaid. Attributes the shutdown to Democratic refusal to fund DHS due to opposition to Immigration and Customs Enforcement (ICE). Republican Strategy on DHS Funding Explains that ICE and Customs & Border Protection (CBP) were pre‑funded through a prior reconciliation bill, insulating them from the shutdown. Criticizes short‑term funding approaches and argues Democrats will not support ICE funding in the foreseeable future. Use of Budget Reconciliation Advocates using budget reconciliation to bypass the Senate filibuster and pass funding with a simple majority. Proposes funding ICE and CBP for the maximum allowable 10 years rather than shorter-term extensions. Proposed Offensive Policy Approach Argues that Democratic obstruction should result in increased ICE funding (e.g., a 10% increase) rather than status‑quo responses. Frames this as both a policy and political countermeasure. Broader Conservative Legislative Agenda Calls for leveraging reconciliation to advance multiple conservative priorities before potential Republican losses in upcoming elections. Examples include: Preventing future shutdowns of critical services (air traffic control, TSA). Indexing capital gains taxes to inflation to reduce “phantom gains.” Expanding school choice and tax‑advantaged family policies. Economic & Housing Policy Rationale Explains how inflation‑indexed capital gains could increase housing supply by discouraging long-term holding solely for tax avoidance. Links tax reform to affordability and economic growth concerns. Election Integrity Measures Supports incorporating election integrity provisions into reconciliation where budget rules allow. Suggests conditioning federal election funding on compliance with integrity standards. Urgency & Historical Warning Draws comparisons to missed legislative opportunities in past Republican majorities. Argues reconciliation represents the last realistic chance to enact significant conservative legislation before expected political gridlock. Strategic “Tentpole” Concept Describes ICE and border security as unifying issues capable of holding a broad Republican coalition together. Warns that narrower or fragmented legislative efforts are likely to fail. Please Hit Subscribe to this podcast Right Now. Also Please Subscribe to the 47 Morning Update with Ben Ferguson and The Ben Ferguson Show Podcast Wherever You get You're Podcasts. And don't forget to follow the show on Social Media so you never miss a moment! Thanks for Listening YouTube: https://www.youtube.com/@VerdictwithTedCruz/ Facebook: https://www.facebook.com/verdictwithtedcruz X: https://x.com/tedcruz X: https://x.com/benfergusonshowYouTube: https://www.youtube.com/@VerdictwithTedCruzSee omnystudio.com/listener for privacy information.

For all those who missed out on London, see you in Miami next week!Notion, the knowledge work decacorn, has been building AI tooling since before ChatGPT, with many hits from Q&A in 2023 and unified AI in 2024 and Meeting Notes in 2025. At the end of their last Make user conference, Ryan Nystrom teased Notion 3.0's Custom Agents - and they are finally embracing the Agent Lab playbook!Sarah Sachs and Simon Last of Notion join us for a deep dive into how Notion built Custom Agents, why it took years and multiple rebuilds to get right, and what it means to turn a productivity tool into an agent-native system of record for enterprise work.We go inside the product, engineering, evals, pricing, and org design decisions behind one of the most ambitious AI product efforts in software today — from early failed tool-calling experiments in 2022 to agent harnesses, progressive tool disclosure, meeting notes as data capture, and the long-term vision for software factories and agentic work.We discuss:* Sarah and Simon's path to launching Notion Custom Agents, and why the feature was rebuilt four or five times before it was ready for production* Why early agent attempts failed: no tool-calling standard, short context windows, unreliable models, and too much complexity exposed to the model* The “Agent Lab” thesis: not just wrapping a model, but understanding how people collaborate and building the right product system around frontier capabilities* How Notion thinks about roadmap timing: not swimming upstream against model limitations, but also building early enough that the product is ready when the models are* Why coding agents feel like the kernel of AGI, and how Notion is thinking about “software factories” made up of agents that spec, code, test, debug, review, and maintain codebases together* How Sarah runs AI engineering at Notion (“notes from Token Town”): objective-setting over idea ownership, low-ego teams comfortable deleting their own work, and a culture designed to swarm around fast-changing opportunities* The “Simon Vortex,” company hackathons, and why security gets pulled in early rather than late* How Notion organizes AI: core AI capabilities and infrastructure, product packaging teams, and a broader company mandate that every product surface must increasingly work for both humans and agents* Why prototypes have become much easier to build internally, and how “demos over memos” changes product development inside a tool the whole company already uses every day* Notion's eval philosophy: regression tests, launch-quality evals, and “frontier/headroom” evals that intentionally only pass ~30% of the time so the company can see where model capabilities are going* What a “Model Behavior Engineer” is, and why Notion treats eval writing, failure analysis, and model understanding as a distinct function rather than just software engineering* The changing role of software engineers in the age of coding agents, and why the new job looks less like typing code and more like supervising a rigorous outer system of agents, PRs, and verification loops* How the “software factory” should work: specs, self-verification, bug flows, subagents, and minimizing human intervention while preserving the invariants that matter* A live walkthrough of a Notion Custom Agent handling coworking space tenant applications by triaging email, enriching applicants with web search, and writing structured data into a Notion database* How agents compose inside Notion: shared databases as primitives, agents invoking other agents, “manager agents” supervising dozens of specialized agents, and memory implemented simply as pages and databases* Notion's take on MCP vs CLI: why Simon is bullish on CLI's self-debugging nature, where MCP still makes sense, and how Sarah thinks about capability, determinism, permissioning, and pricing alignment* The evolution of Notion's internal agent harness: from early JavaScript coding agents, to custom XML, to Markdown and SQL-like abstractions, to tool definitions, progressive disclosure, and a much shorter system prompt* Why Notion cares about teaching “the top of the class,” building for sophisticated operators rather than abstracting away too much capability for everyone* How agent setup works today: agents that can configure themselves, inspect their own failures, and edit their own instructions — with guardrails around permissions* How Notion prices Custom Agents: credits as an abstraction over tokens, model type, serving tier, web search, and future sandbox costs; why usage-based pricing was necessary; and how “auto” tries to match the right model to the right task* Why Notion is not eager to train a foundation model, where they do fine-tune and optimize today, and why retrieval/ranking is one of the most important investment areas as more searches come from agents rather than humans* Why Meeting Notes became one of Notion's strongest growth loops: not just as transcription, but as high-signal data capture that powers search, custom agents, follow-up workflows, and the broader system of record for company collaboration* Why Notion is more interested in being the place where collaboration data lives than in building hardware themselves — and how wearables or other capture devices may eventually feed into that systemSarah SachsLinkedIn: https://www.linkedin.com/in/sarahmsachsX: https://x.com/sarahmsachsSimon LastLinkedIn: https://www.linkedin.com/in/simon-last-41404140X: https://x.com/simonlastFull Video EpisodeTimestamps* 00:00:00 Introduction and launching Notion Custom Agents* 00:01:17 Why Notion rebuilt agents four or five times* 00:03:35 Building for where models are going, not just where they are* 00:05:32 The Agent Lab thesis, wrappers, and product intuition* 00:08:07 User journeys, leadership, and low-ego AI teams* 00:13:16 The Simon Vortex, hackathons, and bringing security in early* 00:16:39 Team structure, demos over memos, and building for agents* 00:20:25 Evals, Notion's Last Exam, and the Model Behavior Engineer role* 00:27:37 Evals as an agent harness and the changing role of software engineers* 00:30:42 The software factory: specs, verification, and agent workflows* 00:32:18 Live demo: a custom agent for coworking space applications* 00:35:08 Composing agents, manager agents, and memory as pages* 00:38:15 Notion Mail, Gmail, native integrations, and tools* 00:39:43 MCP vs CLI and the cost of capability* 00:44:13 When Notion uses MCP vs building its own integrations* 00:47:43 The history of Notion's agent harness rebuilds* 00:55:35 Power users, public tools, and the setup agent* 00:58:01 Self-fixing agents, permissions, and “flippy”* 01:01:13 Pricing, credits, and choosing the right model automatically* 01:09:01 Why Notion isn't training its own frontier model* 01:14:07 Retrieval, ranking, and search built for agents* 01:17:27 Meeting Notes as data capture and workflow automation* 01:21:18 Wearables, hardware, and Notion as the system of record* 01:23:45 OutroTranscript[00:00:00] Alessio: Hey everyone. Welcome to the Latent Space podcast. This is Alessio founder of Kernel Labs and I'm joined by swyx, editor of the Latent Space.[00:00:11] swyx: Hello. Hello. We're back in the beautiful studio that, uh, Alessio has set up for us with Simon and Sarah from Notion. Welcome.[00:00:18] Sarah Sachs: Thanks for having us.[00:00:19] Alessio: Thanks for having us. Yeah.[00:00:20] swyx: Congrats on the launch recently the custom agents, finally it's here. How's it feel?[00:00:26] Sarah Sachs: We ship things slowly. So it had been in Alpha for a little bit and at the point at which is it's an alpha, um, there's a group of people that are making sure it's ready for prod, and then there's a group of people working on the next thing.So sometimes some of these launches are a bit delayed satisfaction, so it's quite nice to remind yourself all the work you did because we do have a habit of like. Being two or three milestones ahead. Uh, just ‘cause you have to be, you know, you can't get complacent. Um, but it's been great that people understood how this is helpful.And I think that's just easier in general building AI tools today than it was two, three years ago. People kind of get it and so that user education, um, there's just, it was our most successful launch in terms of free trials and converting people and things like that. It was really successful, so yeah.But there's a lot to build.[00:01:12] swyx: Making it free for three months helps.[00:01:16] Sarah Sachs: Yep.[00:01:17] Simon Last: It was definitely super exciting for me because it's probably the fourth or fifth time that we rebuilt that.[00:01:22] swyx: Yes.[00:01:23] Simon Last: And I mean,[00:01:24] swyx: you've been building this since like 20, 22.[00:01:26] Simon Last: Yeah, I mean, like, it was even right when we got access to like GPT four in late 20 22, 1 of the first ideas we had is like, oh, okay, let's make an agent that I, we used the word assistant at the time, there wasn't really the word, the word agent yet, but, oh, we'll give an access to all the tools the notion can do, and then it, we run in the background like, like do work for us.And then we just tried that many times and it just. Was too early. Um,[00:01:48] swyx: I need to force you to like double click on that. What is too early? What didn't work?[00:01:52] Sarah Sachs: We were fine to, like, before function calling came out. We were trying to fine tune with the Frontier Labs and with fireworks, like a function calling model on notion functions.This is right when I joined. I joined because, um, we needed a manager as Simon was needed to be able to go on vacation. So, uh, that's, that's around when I joined, so you can speak much more to it.[00:02:11] Simon Last: Yeah, we did partnerships with both philanthropic and open AI at different times, uh, to try to, at the time the, I mean, when we first tried, there wasn't even a constant of like tools yet.We, we sort of designed our own like, like tool calling framework and then we tried to fine tune the models to, uh, to use it over multiple turns. Um, and because it, it didn't work well out the box, I think. Yeah. The models are just too dumb and the context thing was also way too short.[00:02:37] Alsesio: Yeah.[00:02:37] Simon Last: Um, and yeah, we just kind of banged our head against it for a long time.Uh, unfortunately it was always like, there was always like sort of. Glimmers that it was working, but um, it never felt quite robust enough to be like a useful, delightful thing. Um, until I would say, uh, the big unlock was probably like Sonic 3.6 or seven, uh, early last year. And that's when we started working on our agent, which we shipped last year.Um, and then, and then uh, uh, custom agents, kinda a similar capability and that, that one just took longer because we, we just wanted to get the reliability up a lot higher. ‘cause it's actually running in the background.[00:03:14] Sarah Sachs: And the product interface of like permissions and understanding, you know, this custom agent is shared in a Slack channel with X group of people and has access to documents that are surfaced to Y group of people.And the intersect experts, Y might not be whole. And so how do you build the product around making sure administrators understand that permissioning took multiple swings.[00:03:35] Alsesio: Everything is hard back at the end of the day. Yeah. I'm curious, like when the models are not working, how do you inform the product roadmap of like, okay, we should probably build, expecting the models to be better at some reasonable pace, but at the same time we need to, you know, you had a lot of customers in 2022.It's not like you were a new company or like no user base.[00:03:54] Simon Last: Yeah, I mean I think there's always the balance of, you know, like you want to be a GI pilled and thinking ahead and building for where things are going. Uh, but also you wanna be like shipping useful things. And so we always try to like, like keep a balance there.You know, we. We try to take clear, like a portfolio approach. You know, we're always working on multiple projects and, and we're always trying to work on, you know, maintaining things where that have already shipped, like, like shipping new things that are like eminently working well and make them really good.And, and then we wanna always have a few projects that are a little bit crazy. Um,[00:04:23] Alsesio: and what are the a GI peel projects that you have today? I'm curious about, uh, you don't have to share exactly what you're working on, but I'm curious what are things today that maybe in 18 months people will be like, oh, obviously this was gonna work[00:04:35] Sarah Sachs: 18 months.[00:04:37] Alsesio: Yeah, 18 months is, you know,[00:04:37] Sarah Sachs: it's a long time and Yeah. Yeah.[00:04:39] Simon Last: I mean, there's a number of things happening. I think one thing that's becoming more clear is I think like, like, uh, coding agents are the kernel of EGI, sort of, everything is a coding agent. Mm-hmm. I think that's, that's sort of one, one direction.Um, and then, yeah, the exciting thing about that is sort of your agent can sort of bootstrap its own software and capabilities and actually debug and maintain them. And so yeah, we're, we're, we're thinking a lot about that. And then, yeah, like, like another category of things that I'm, I'm really excited about is like, uh, we call the software factory also.People are using this, uh, this, this sort of word. Um, basically it just means can you create sort of like a, as automated as possible, a workflow for developing debugging. Mm-hmm. Merging, reviewing, and maintaining a code base and a service where there's a bunch of agents working together inside, and like, like how does that work?[00:05:28] Sarah Sachs: If you think back to your initial question, like, why did this take so long? I think something,[00:05:32] swyx: I didn't say that, but Yes. Okay. Go ahead.[00:05:34] Sarah Sachs: Why, what, what changed over the three and half years of trying[00:05:37] swyx: it? Exactly. Right. Because most people always say like, it didn't work yet. Then reasoning models came, then it worked.I was like, okay, let's go a little[00:05:43] Sarah Sachs: bit. That's, I mean, that's part of it, but I think the other part of it that I actually think is really what will set notion apart for every new capability is we have like. Two skills that are crucial when it comes to frontier capabilities. One is not letting yourself swim upstream.So like quickly realizing if you're just pressing against model capabilities versus not exposing the model to the right information, not having the right infrastructure set up. That and of itself is the skill of intuition. And the second is to see, okay, you're not swimming upstream. Which direction is the river flowing and what is like, how do we think ahead about the product and start building it even if it's not great yet, so that when it is there, we're ready for it.Right? And like those can sometimes feel like counterintuitive things. Like we can be trying to fine tune a tool calling model when they don't exist yet. And that the trick is to not do that for too long, but realize that there was something there. And we've had a lot of things which like, um, we're just like not swimming in the right direction with the streams.I think we had multiple versions of transcription before we got meeting notes, right? Oh, I gotta talk[00:06:39] swyx: about that. Yeah.[00:06:40] Sarah Sachs: Yeah. Um, and so. I, I, I think that like we, we really closely partner with the Frontier Labs on capabilities and we also have to have strong conviction on, as those capabilities move.Notion is about being the best place for you to collaborate and do your work. And how does that narrative change if the way that we work changes?Yeah.[00:06:58] swyx: Yeah. You told me you were a fan of the Agent Lab thesis, and this is, this is kind of it, right?[00:07:02] Sarah Sachs: Right. I show that thesis to so many candidates. Like I have it as like micro chrome autofill.Um, at this point, like it's one of my most visitations[00:07:10] swyx: because like, is this the, here's why you should work in notion and not open, open eye. I, it's like,[00:07:14] Sarah Sachs: here's, here's what's different about it.[00:07:16] swyx: Yeah.[00:07:16] Sarah Sachs: And here's why. It's not just a rapper. I actually think more and more people understand it's not just a wrapper.[00:07:21] swyx: Yeah.[00:07:22] Sarah Sachs: Um, and by the way, like in the beginning, parts of what we build are wrappers on functionality. That works well, of course, but that's not really the most, um. I would say that's not the product that, that drives revenue. And that's not necessarily always what users need.[00:07:35] swyx: I mean, you know, notion is the AWS wrapper, but like the, the wrapper is very beautiful and like very, very well polished.So[00:07:40] Sarah Sachs: like the analogy,[00:07:41] swyx: like[00:07:42] Sarah Sachs: the analogy that I've been coming back to his Datadog in AWS[00:07:45] swyx: Yeah.[00:07:46] Sarah Sachs: So, uh, Datadog could not exist with, without cloud storage. Right. That it's kind of fundamental that that works. Um, and AWS has like a CloudWatch product, but Datadog is an expert on understanding how people want observability on the products they launch.And we're experts in understanding how people wanna collaborate, and that's really where our expertise lies.[00:08:04] swyx: Totally.[00:08:04] Sarah Sachs: Um, regardless of the tools that we use,[00:08:07] Alsesio: I'm kind of curious how you think about implicit versus explicit expertise. I feel like Datadog is half and half implicit and explicit. It's like they understand across markets and industries what engineering teams usually look for.With notion, it's almost like more of the expertise is at the edge because you as a platform, you're like so horizontal that the end user is not really the same. Mm-hmm. Like with Datadog, the end user is always like, yeah, an engineering lead, a kinda like SRE related person with notion. It can be anything.So I'm curious how you put that expertise into a product versus, you know, obviously it, WS cannot build notion. It's, that doesn't quite work in this case, but[00:08:44] Simon Last: it's, it's a little bit differently shaped. I think, you know, a classic vertical SaaS, like the data is kind of like that. They understand their individual customer very deeply.It's kinda a narrow slice, um, notion has always been super horizontal. And our, our task has always been to sort of balance these two somewhat opposing forces of like, we're listening to our customers and what they want us to build. It's a broad slice. And then also we're thinking about like, okay, how do we decompose what they want into, uh, nice primitives that are, that are really nice to use and we'll, we'll get us like as much bang for the buck as possible.And then, you know. Maintain the whole system, make it all like, like super clean and nice to use.[00:09:22] Sarah Sachs: We still have user journeys. I mean, we still focus on like core. I actually think the failure of our team is when we focus too much on what are cools that are, what are tools that are[00:09:31] Simon Last: mm-hmm.[00:09:31] Sarah Sachs: Cool tools. I actually think that's when we make have the least velocity because you still need some sort of focus on a user journey.So like for instance, we'll all sit down every Friday and look at the P 99 of like the most token exhaustive custom agent transcript and just look at why it didn't do well and cut a bunch of tasks. Like we still focus on like, this has, like this should work. Email triaging should work. Mm-hmm. Right. And similarly, like when we're talking about before building, um, chatting, um, before we started filming about, okay, how can I do PDF export?Well that's functionality that then merits. Maybe we should build a tool that has access to a computer sandbox in a file system and the ability to write code. Right? Right. Um, but it's because we're thinking about the fact that our users to do their, to do their daily work, need to export PDFs, not because we're like, Hmm, I think a computer tool could be cool.Like, let's just see what happens. Mm-hmm. Like we, we have to focus on some user journeys, otherwise we just don't have like, enough strategy to, to prioritize.[00:10:29] swyx: I think there's a lot of like really strong opinions that you've had. Do you have like sort of like a towel of Sarah Sachs? Like, you know, like what, how do you run your team?Like I feel like you just have accumulated all these strong opinions. Obviously part, part of this is your, your token town thing.[00:10:43] Sarah Sachs: I think the TAs working with Service X is, um, you'd have to, it depends who you ask. Um, I think it depends if you're on my team or a partner Right. Or a vendor.[00:10:54] swyx: Yeah. There other people want to run their teams the way that you're Yeah.You're like bringing these things. And then also similarly, uh, Simon, when you did the custom agents demo, you had like, well, we've been using custom agents and here's the super long list of everything that we do. No humans ever read it. Right? That's what you said. I was like,[00:11:07] Sarah Sachs: yeah. So I think for, for me, um, something that I learned very quickly and became very comfortable with was that my job was not to be the ideas per person or the technical expert.My job was to make it so that everybody understood the objective, had a resource to help prioritize what they should work on, and had an avenue to prioritize what they thought was important. And I think that's true with all, all leadership, but I think especially on the AI team. Almost all of our best ideas come from prototypes, from people that have a cool idea because they saw a user problem, and it's a huge disservice if all of those ideas have to pass, like the sniff test of what me and a product partner or Simon and Ivan decided were the direction, right?Because a lot of what we're doing is leaning into capabilities, so. I think that's the first thing is like, I don't really view like the role of engineering leadership as like, uh, hierarchical, nor has it ever been, but especially now, like very willing to change direction based on, um, like proof is in the pudding.Yeah. And like, and I think we have rebuilt our harness three or four times. And when you do that, then the second rule of engineering leadership is like you need to build a team that's comfortable deleting their own code and is very low ego and is driven by what's best for the company. And, um, doesn't write design docs because they think it's their promotion packet.Right. And that's a culture that notion had long before I joined, but like our willingness to just swarm on different problems and um, redo things that we've built before because something has changed. Like, there's a lot of friction that can happen at companies when you do that. And it doesn't happen at Notion.And because it doesn't happen when new people join. Like they don't wanna be the ones that are saying, we shouldn't do this. I wrote that code. So then it's, you know, you, you create a culture that everyone thoughts and that culture comes directly, I think from Simon and Ivan though, um, because they're very open-minded.[00:12:50] swyx: Anything that you,[00:12:50] Simon Last: you'd add? I'm not a manager, like, like, like Sarah is. Um, a lot of my role is really to try to think a little bit ahead, make sure that we're, we're building on the right capabilities and then like the prototyping stuff. And yeah, it's really, really critical to always just be starting again.It's like, okay, this is new thing. What does this mean? What if we just rethought everything or wrote everything? And so I, I'm, I'm basically just doing that in a loop every six months.[00:13:16] swyx: Yeah. Do you believe in internal hackathons for this stuff?[00:13:19] Sarah Sachs: I think there's like two different versions. So one is like, we just have a, a, a solid bench of senior engineers that come and go on what we call the Simon Vortex and Productionizing what we built, right?Because when you're in the Simon Vortex, the velocity is super high. The direction changes daily, and it's meant to be like the equivalent of a SC Works lab. We don't need to do hackathons for that. We need to have senior engineers that we trust to come in and out of those projects. For instance, like management boundaries are really loose.Like you report to him, but you work for her right now. Yeah. That's something that when we hire managers, it's important they don't care about because we tend to form more structures. Yeah. Don't be too[00:13:54] swyx: territorial.[00:13:55] Sarah Sachs: We form more. It's after we ship things, not not before, just historically. Um, the second thing is we do have companywide hackathons.Actually we just had our demos day for the hackathon we had last week this morning. That's more for people that aren't directly working on the project, feeling like they have the time to pause and learn how to make themselves more productive or how they would use notion custom agents to build something.Or part of the hackathon was actually encouraging everyone across the company to build their own agentic tool loop, calling from scratch. Follow like an every blog post on how to do what I think because we want[00:14:26] swyx: just with the compound engineering one. Yeah.[00:14:28] Sarah Sachs: We want everyone to use cloud code in the company or whatever the coding agent they please and understand that fundamental.So we set aside a day and a half. We're all leadership, encourage everyone on their teams across the company to do it. So we have hackathons like that. I would say like kind of facetiously, like everything we build is a little bit like a hackathon until it graduates and puts on big boy pants and as a product ops rollout leader and has a assigned data scientists and stuff like that,[00:14:54] swyx: security review enterprise stuff,[00:14:56] Sarah Sachs: actually security reviews one of the things that we bring in first because it just slows us down way more and, um, causes a lot of tension and they build better product if they're involved early.So, um, that is probably the first person to get involved in something that's the[00:15:09] swyx: right PR approved answer.[00:15:10] Sarah Sachs: No, but it's not just PR approved. It like, um, um, it's[00:15:13] swyx: actually real. It's actually real. It's like, um, I'm just saying scar[00:15:15] Sarah Sachs: tissue.[00:15:15] swyx: Yeah,[00:15:16] Sarah Sachs: because like, you know, my background's also, I worked at Robinhood for a number of years.Yes. So like, uh, compliance and things like that, um, are a little bit more, you learn the hard way when it doesn't come naturally.[00:15:26] Simon Last: Yeah. I think the. The hackathon is really important for uplifting the general population, but like, if that's the only way you can build new things, you're kind of toast. I mean, it, it has to be like the daily processes, like, you know, building these new things.Um, and it has to be about, I think like, I think in the AI era a lot more leverage accumulates to the most curious and excited people. And so it's like we're all about just like activating that energy. You know, like if someone's protesting something on the weekend that they're excited about and it's important, that should be the main thing that we're doing.Yeah. Um, it's not a hackathon that we schedule once a quarter, it's just like, yeah. Daily process. Part of the culture.[00:16:02] Sarah Sachs: I mean, that's how we shift image generation and notion now. It was always this thing that would be kind of nice to have, but it wasn't really clear where that was necessarily aligned in product priorities.It'd be a lot of work. And we had someone on the database collections team, Jimmy, who was like. I really wanna do image generation for cover photos and inside notion. And we're like, if you wanna build it, like it's, do it please. Like we encourage you. We gave ‘em all the resources of working directly with Gemini and being able to like track the token usage and it working through endpoints.We gave them eval, support, everything, and then became a, a full project.[00:16:34] Alsesio: Yeah.[00:16:35] Sarah Sachs: That's why you can't have like ego as a, a leader. Like that's, that's how we work.[00:16:39] Alsesio: What's the size of the team today, both engineering and overall?[00:16:43] Sarah Sachs: I manage, uh, the team. That's what we'll call it. Core AI capabilities and infrastructure.That's about 50 people. But then we have per i partner teams that do packaging. So how it shows up in the corner chat versus custom agents versus meeting notes, that's another 30, 40 people. And, and then every team that has a product service at Notion that a user can interface with owns the tool that the agent interfaces with the editor team.The team that did CRDT for offline mode is the same team that handles how two agents, um, edit competing blocks. Mm-hmm. Right? It's the same problem. The team that built the underlying SQL engine is the same team that owns how the agent asks it to run a SQL query, and it does it performantly. And so from that regard, anyone working on product engineering is tasked with making them work for customers that are humans and agents because over time the majority of our traffic will be coming from agencies using in our interface, not humans.And so. Our objective is to make it so that the whole product org is building for agents.[00:17:40] Alsesio: Yeah. How has it changed internally? The activation bar is kind of lowered a lot. Like anybody can kind of create a prototype very, somewhat easily, especially if you're like an existing code base. Have you raised the bar on like what type of prototype people need to bring forward to gonna be taken?Not like seriously, but like, you know what I[00:17:58] Simon Last: mean? Yeah. I think the bar is lowered in many ways. Be like, one thing our, uh, our team built that is really cool is our, uh, our, our design team made a whole separate GitHub repo, uh, called the, the design Playground. And it's basically just to create a bunch of like, like helper components and you, uh, for, for quickly a throwing together UIs.And it's become like actually quite sophisticated. Like it has like an agent in there and like, uh, that's pretty fun. So like, we pretty much, like, they don't do mocks, they just make like, like full, full prototypes.[00:18:27] swyx: Here it is. It works.[00:18:28] Simon Last: They give you like a u rl. They're like, okay, all right. So we have to make the, like the real production version of that.Um, and then for engineers. A prototype looks like just making it a feature flag that actually works. Like that's sort of the bar.[00:18:39] Sarah Sachs: Something to understand that's really unique about notion. One of the reasons I joined we're super lucky is no one uses Notion in their job as much as people that work at Notion.[00:18:46] Simon Last: Of course.[00:18:47] Sarah Sachs: So I think there's very few companies, maybe if you worked on Chrome I guess, but like everything that we ship, we ship internally first and get a lot of really quick feedback. And also sometimes our dev instance is totally borked and you have to change a bunch of flags to get things done. And that's kind of like, but everyone, so people that do it ticketing, people that do supply chain procurement, recruiting, everyone is using the same instance of notion with like a lot of flags on for these prototypes people build.Um, and so we have this, Brian Levin, one of the designers on our team, I think evangelize this concept of demos over memos.[00:19:18] swyx: Ooh, too[00:19:20] Sarah Sachs: good. Um, which has been, uh, very good for building demos, and I think it's put a big pressure point on us to have really strong product conviction, because if anything can be demoed, you really need a strong filter of making sure that if you know, you're doing X amount of work, you're making the, you're, you're focusing on one tower, you're not just building a really flat hill.Right. That's actually where I think there has to be more conviction from our PMs, um, and our designers and, and well, the company really to have conviction of what journey we're going on.[00:19:52] Simon Last: But overall, I feel like it works pretty well. Like people, almost all the engineers have good enough taste to realize that like, this prototype doesn't actually make sense in the product, or, or it does.So it's not that common that I would see a prototype. It's like, oh, this makes no sense. Mm-hmm. It's like, you know, people are doing reasonable things and, and, and then it's just a matter of. Which things we build first and then often just, just figuring out how to turn it on and off. There's our, in the, in our like experimental chat ui, there's this, there's probably like, like a hundred check boxes in there.[00:20:22] Sarah Sachs: Kills me[00:20:23] Simon Last: the things you could turn on and off.[00:20:25] Sarah Sachs: Uh, but I think that, okay, so that is kind of true, Simon, but like being the person that manages the evals team, like there is a level of intensity that it adds to the platform team. So, you know, if we're gonna do image generation and notion, all of a sudden the way that we do attachments and the way that we, um, our LLM completion like cortex talks and expects tokens back and now it's getting images back.Like there's a lot of platform work that we do need to, like solidify a little bit. So sometimes it'll be in dev for a couple weeks before it makes it to prod just because we still have to like, make it robust, make it HIPAA compliant, ZDR compliant, figure out the right contracting with the vendor, whatever it is.And we need to eval it because we want the team. To still maintain what they build. That's the one thing is like if we have a bunch of prototypes, it can't just be like a small group of people that then maintain whatever end prototypes. So we have invested a lot of people in an eval and model behavior understanding teams that, we call it agent dev velocity.So your dev velocity building agents can be faster if we invest in that platform. And so we have a whole org dedicated to Asian, um, platform velocity so that you can build your own eval and then maintain it once you ship it. So if a new model release comes out and we, every[00:21:38] swyx: team maintains their own eval,[00:21:40] Sarah Sachs: we maintain the eval framework.Every team owns their own evals and a lot of them we've integrated to Optin, to ci, or we run them nightly and we have a team, uh, a custom agent that triggers to a team to look at the major failures. That's really critical because if we have like all these different surfaces now, a lot of it's on the same agent harness, so it's easier to maintain.It's just packaging of different agent harnesses, but new functionality of the agent. Let's say that like we wanna update like. Uh, you know, they deprecated, sonnet, um, four or whatever it is and we need to auto update. Are[00:22:11] swyx: they already? That's so, okay. Yeah. Actually wasn't that long ago.[00:22:14] Alsesio: Theywere[00:22:14] Alsesio: just 3.5.[00:22:15] Sarah Sachs: 3.537. Just got deprecated.[00:22:18] swyx: 3 7, 5 0.2 or, yeah. No,[00:22:20] Sarah Sachs: it's not. 5.2 is five point. Five point no. Yeah, five four is 40% more expensive than five two. So if they deprecated five two, you would hear they can, you would hear from me about that one. Um, but, uh, another conversation to have.[00:22:35] swyx: I have a cheeky evals question for you.Have you noticed any secret degradation from any of the major model providers?[00:22:40] Sarah Sachs: Secret degradation,[00:22:42] swyx: like. During the War Bay, when it's high traffic, it suddenly gets dumber.[00:22:47] Sarah Sachs: Yeah. I mean, not just between the, I mean, we definitely notice flakiness, we've definitely noticed, particularly for some providers, that things are slower during working hours and[00:22:57] swyx: there's a latency argument.Yes. Not a quality argument.[00:22:59] Sarah Sachs: No. I think the quality difference that's interesting is, um, even though companies that say they're selling the same, a, it's really into like quanti quantization, but like companies that say they're selling the same model through different vendors, whether it be through first party or Bedrock, Azure, et cetera.We do see different qualities sometimes, and that's not necessarily what's advertised.[00:23:21] swyx: Yeah. Kidney went to the point of like, if we, they shipped like this, like eval across all the providers and it was like very obvious we were secret equalizing and it was very,[00:23:28] Sarah Sachs: yeah. But[00:23:29] swyx: that's very embarrassing.[00:23:30] Sarah Sachs: You know, um, we hire Subprocess to figure that out for us.So we just wanna understand where it's regressing or where it's optimized. And sometimes we're okay with regressions that optimize latency if they're the appropriate regressions. Our job is to make sure we have the evals to understand the changes that are important to us. And even like when we're partnering with labs on pre-releasees of models, they'll send us multiple snapshots.And this is less about quantization, but more just regressions. Like they have shipped models that were not the snapshots that we wanted, and they have changed the snapshots that they shipped based on the feedback that we give. Because our feedback tends to be more enterprise work focused and not coding agent focused.And definitely those can be bummers, like, you know, uh, we know that this wasn't the version you wanted, but we'll help you make it work. I mean, we always make it work, but that definitely happens.[00:24:16] Alsesio: Yeah. Do you have, um, failing evals that you're just hoping, oh, that will have success eventually when a good model comes out?[00:24:23] Sarah Sachs: Uh, I mean, yeah. So I think. I mean, I could talk about this for 60 minutes, so I will limit myself. I think it's a real issue when people say evals and it's just like, that's quality, that's like unit, I mean, it's like saying testing. It's not just unit tests, right? So. We have the equivalent of unit test.Regression test. Those live in ci, those have to pass a certain percent, you know, within some stochastic error rate. Then we have, as you're building a product, evals of these aren't passing right now, and this is launch quality. So we have a report card and we need to, on these categories, you know, be it 80 or 90% of all of these user journeys to launch, and then what we have what we call frontier or headroom evals, where we actively wanna be at 30% pass rate.And that's actually been a effort that we took in partnership with philanthropic and OpenAI in the past maybe two or three months, because we actually hit a point where our evals were saturated and we weren't able to really give insightful feedback other than it wasn't worse. And not only is that not helpful for our partners, it's not helpful for us to understand where the stream is going.You know, going back to that analogy. And so we spent a lot of time thinking about. What notions last exam looks like, right? Mm-hmm. Not just humanities, last exam. Ooh, notions last exam. Mm-hmm. And, um, there's a lot of, you know, dreams about what that would look like. I know we've talked a lot about benchmarking, um, swix, but, uh, yeah.Notions last exam is a big thing inside the company and we have people, full-time staff to it exclusively. Mm. We have a data scientist, a model behavior engineer, and an full-time, um, evals engineer just dedicated to the evals that we pass 30% of the time.[00:25:56] swyx: What you're hiring for[00:25:57] Sarah Sachs: MBEs? I am hiring[00:25:58] swyx: What is an MBEA[00:25:59] Sarah Sachs: model?Behavior Engineer Model. Behavior engineers started with a title data specialist before I joined when they were working with Simon on like, uh, Google Sheets and like Simon just needed someone to look through Google Sheets and say, yes, no, this looks bad. This looks good. Right? And so we hired people with kind of diverse linguistics background.We had like a linguistics PhD dropout. Mm-hmm. And a Stanford ate new grad. And they're amazing. And they formed a new function basically. And over time we've built a whole team, um, with a manager who's now kind of reinventing what that role is with coding agents. So they used to be kind of manually inspecting code.Now they're primarily building agents that can write evals for themselves or LLM judges. There's a really funny day I can send you the picture where Simon, about a year and a half ago, was teaching them how to use GitHub. Um, and they're on the whiteboard and it was like, okay, I think it would be so much faster if our data specialists learned how to use GitHub and like learned how to commit these things in Dakota.And, and that was then and now I think, you know, coding has been a lot more accessible. Um, but moving forward it's this mix of like data scientist PM and prompt engineer because there's craft in understanding like even like what models can and can't do things. How do we define like that headroom? How do we define like what a good journey is?Um, is this model better or not? Why is this failing? There's some qualitative work, but then there's also like a lot of instinct and taste to it, and that's not necessarily software engineering. And so we have like very firm conviction and we have had for a number of years now that that is its own career path and we have always welcomed the misfits, so to speak.So we really firmly believe that you don't need an engineering background to be the best at this job. And that's what's quite unique about this particular role.[00:27:37] Simon Last: Yeah, this is something that I've been pretty excited about recently is we made an effort basically to treat the eval system as like an agent harness.So if you think about it, like, you know, you should be able to have an agent end-to-end, download a dataset, run an eval, iterate on a failure, debug, and, and then implement a fix. And ultimately you should be able to, you know, drive the full time process with a human sort of observing the, you know, the outer uh, system.So yeah, we went, went pretty hard on that. And that's, that's worked extremely well so far. It's like basically just to turn it into a coding agent, uh, uh, problem.[00:28:11] swyx: Your coding agent or just whatever[00:28:13] Simon Last: harness No coding agent. Yeah, code, cloud code. It should be totally general. Yeah. I think if it would be a mistake to like, like fix it on any, any particular coding agent.At the end of the day, it's just like CLI tools.[00:28:21] Sarah Sachs: It's like the same way that you would've a coding agent write the unit test. You should have a coding agent write the eval.[00:28:26] swyx: Yeah.[00:28:26] Sarah Sachs: But there's a lot of supervision in that still. We just don't believe that supervision has to come from software engineers because a lot of it is like, um, kind of you XREE and whatever, and these are the people that also triage failures and tell us where we should be investing next.[00:28:40] swyx: Yeah. I'm gonna go ahead and ask a spicy question. Is there a data, there are no software engineers at Notion.[00:28:46] Simon Last: Um,[00:28:46] Sarah Sachs: what does it mean to be a software engineer?[00:28:47] swyx: Exactly.[00:28:48] Simon Last: I mean, I think the way things are going is like we're on some continuum where. If, if you look back three years ago, humans were typing all the code and then we had auto complete, you're typing list of the code.Then we had sort of like filling agents, filling lines, and now we're getting into like agents doing longer range tasks where you can debug and implement a fix and then verify it works and you know, get your, get your PR even like, like Merion deployed. I think we're sort of just moving up the abstraction ladder and then the human role becomes more about observing and maintaining the outer system.There's a string of agents flowing through, like me prs what's going off the rails. Like what do I need to approve? Is there like a learning or memory mechanism that that works? So it's kind of a hard engineering problem. There's a, you know, there's, there's a lot to do there. I think we're just sort of moving up stack[00:29:34] Sarah Sachs: the same transition machine learning engineers have made, right?Like I haven't looked at a PR curve in a while.[00:29:39] swyx: Yeah. You used to do this stuff and now, um, auto research can do it,[00:29:42] Sarah Sachs: right? Like I think it depends on what you define as a software engineer.[00:29:46] swyx: Yes. It's, that's changing for sure.[00:29:49] Sarah Sachs: I think every software engineer in notion this summer went through like this, um, sheer, um, one of our engineering leads of the company called it, like every software engineer is going through the, the, uh, identity crisis that every manager goes through, where all of a sudden they realize their ability to write code is less important than their ability to delegate in context switch.And I think that is a transition out of being a software engineer. But[00:30:12] Simon Last: yeah. Yeah, there's a critical difference to being a manager, which is that like, it is actually very deeply technical. The problem, you know, humans are very like, like, like fuzzy and you can't like treat a team of humans like a, like a rigorous system where like, you know, prs like, like flow through and can be in like a block status and then what happens when they're blocked, right.With a set of agents, you actually can do that. And, and, and I think it's actually, there's a lot of interesting technical rigor that that goes into that it's like it's a technical design problem. Ultimately.[00:30:42] Alsesio: What is the design of the software factory that you're building?[00:30:46] Simon Last: Yeah, I mean, I think we're. Trying a lot of different things.I mean, ultimately you want to design a system that requires as little human intervention as possible, but like still maintaining the in variance that, that you care about. So yeah, we're exploring a lot different ideas there. I mean, I think I could talk about a few things I think are important there.Like, one thing I think is really important is, um, having some kind of like specification layer you can just commit marked on files. Mm-hmm. That works pretty well, but[00:31:15] swyx: it's nice to be notion man. I'm just saying like the spec, like Yeah. The natural home for specs is notion.[00:31:21] Simon Last: Yeah. Right. It can be a database of pages.Yeah. I mean, it needs to be something that is, you know, human readable and I viewable and I think that's pretty key. Another really key component is like the, the self verification loop. Yes. You need really, really good testing layers, basically. And that's a really deep, uh, uh, problem. But by getting that right, you know, and then, and then it's kinda like the workflow of like.What happens when there's a bug? How does it flow into the system? Like, is it like a subagent working on it? How does it make a PR and how does that get reviewed? And me, and then, you know, so there's like the, the flow or process.[00:31:56] swyx: Yeah. Cool. Uh, you know, one thing we did work out before you guys came in was this demo or this[00:32:01] Simon Last: agents[00:32:02] swyx: agent demo.Uh,[00:32:03] Simon Last: so every,[00:32:04] Alsesio: every time we do an episode, we try the product. Right. I don't think there's ever been an episode that I haven't tried. Yeah. Um,[00:32:11] swyx: and we, we try, try is a, a big word. Like since day one lane space has been on Notion, but this is the, this is the net new thing. Yes.[00:32:18] Alsesio: So this is for Nel Labs, which is the space we're in.So next week we're opening applications for tenants. So there's a web form, let me, we got this form done here. Uh, so, uh, before. Uh, the workflow would be I get an email, then I look at the person. It was like, should I spend time talking to this person? Then I respond, they respond back. So I build this. So the name it came up for on its own.Can you maybe h how do, how does it come up with its own name?[00:32:43] Simon Last: Yeah, that's a pretty app name. It's, it, it is just a random, it's a random, a name generator.[00:32:47] Alsesio: Oh, that's funny. It just came,[00:32:49] Simon Last: the fact that it picked that is, is kind of hilarious. I'm pretty sure it's just determined,[00:32:54] Sarah Sachs: resilient collector. I, I think I've never looked at the code for that.I've never second guessed it. I think it's kind of like a madlib situation.[00:33:00] Simon Last: Yeah, I think you're right. Yeah. It's, it's totally a, a deterministic. Oh, I thought it was great. Yes. Although, although when the, if you use the AI to set itself up, it can update its own name, so. Okay. Um,[00:33:11] Sarah Sachs: how did you create it? It, did you just do[00:33:12] Alsesio: classroom?I,[00:33:13] Sarah Sachs: okay.[00:33:13] Alsesio: I did, yeah. I'll say just check my inbox for applications for a coworking space. Keep a people, so it created the database for me. Which I have here. And I guess database is like an notion table because everything is notion. Um, and then whenever um, an email comes in, like here, it just creates a new role for the person.Mm-hmm. And then it uses web search to enrich the mm-hmm. The profile. So it kind of like searches the web and it's like, this is who this person is, this is when they say they wanna move in and kind of updates everything else. This is, I mean, it's not a GI, but to me, I don't wanna do this work. So it feels like, I mean, it took me maybe like 15 minutes to set up the whole thing.Um, and I really like that most of the information should live here. You know, it is not like some other tool asking me[00:34:01] Sarah Sachs: Yeah.[00:34:01] Alsesio: To like, bring my stuff there. It's like I would've probably already created an ocean thing.[00:34:06] Sarah Sachs: Mm-hmm.[00:34:06] Alsesio: So[00:34:07] Sarah Sachs: most of our biggest use cases and gains are from. That extra layer of human involvement in the process to make it so right.And so like one of our biggest use cases is bug triaging. So if someone posts something in Slack, can you just have a custom agent that lives there that has its own routing constitution of what team this belongs to, creates a task in your task database and then posts in that Slack channel, right? Like that's like one of the first things that we built internally, I think.And it's completely changed the way that notion functions as a company. Nothing falls through, well, most things don't fall through the crack. We don't know what we don't know. But it's not replacing people, it's replacing processes.[00:34:44] Alsesio: Yeah.[00:34:44] Sarah Sachs: Right.[00:34:45] Alsesio: And I'm curious how you think about composability of these things.So the other one I was working on is like a. These filler. So whenever somebody signs up as a tenant, kind of he'll sell the lease for them. There should probably some agent that is like office manager agent mm-hmm. That can handle the request, make the lease, and then, uh, give them a ADA access to the office and all of that.How do you think about that feature?[00:35:08] Simon Last: Yeah, so I mean, there's, there's two ways you can compose. One way is by using like the data primitives. So you can, you know, you, you could give, you have one agent, uh, be writing to the database and there's another agent that's walked in the database. So that's, that's one way that they, they can coordinate that's like a little bit more decoupled and mm-hmm.Works really well. Or you, you can couple them. So I, I think it's actually not released yet. Releasing it like next week is, uh, in the settings for an agent, you can give access to invoke any other agent.[00:35:34] swyx: Hmm.[00:35:34] Simon Last: So you can have them just. Just, uh, uh, talk directly. So[00:35:37] swyx: you, was there a limit on like, number of recursions or just,[00:35:40] Simon Last: um, probably,[00:35:42] swyx: you know what I mean?Like, you can just get an infinite loop that way there's[00:35:45] Simon Last: some kind of Yeah,[00:35:46] Sarah Sachs: I think it's, there is actually a number somewhere.[00:35:49] swyx: I believe I'm just, you know, like, you're, you're, someone's gonna screw up. You[00:35:51] Simon Last: should you try to see[00:35:53] swyx: Yeah. I mean, everything's gonna be paperclips.[00:35:55] Simon Last: Oh, yeah. Yeah. But, uh, but, but that's really useful.Yeah. So we, you know, like I just, I, I helped, uh, someone internally the other day, they had, they had built like over 30 custom agents for, uh, for our go to market team doing all kinds of different things. You know, for example, like researching, you know, like, like filling information about, about a customer or like, like triaging customer feedback or like, uh, something like that.Literally over 30 of them. And, and then he, and then he even made like a database of all the agents and then he is like, okay, and, and now I'm getting 70, over 70 notifications per day with just the agents are blocked on various things. Uh, and then I was like, oh, okay, cool. You know, the obvious thing to do there is to make a manager agent,[00:36:32] Sarah Sachs: right?[00:36:33] Simon Last: That's gonna sort of blocks be another abstraction layer in between your, your, uh, uh, 30 agents. Uh, so yeah, we, we send out with like a manager agent and then has access to invoke all the other agents and it's sort of like, like watching and observing them and then it sort of, it just creates a layer of abstraction.So instead of 70 notifications per day, it's like, like five. And then, and then the manager agent can help like, uh, debug and fix any problems with the,[00:36:54] swyx: does this is a concept of like an inbox or something like piece, you're basically saying that they can message each other?[00:37:00] Simon Last: Yeah.[00:37:01] Sarah Sachs: Well[00:37:01] swyx: they use the system of record, which, which is[00:37:02] Sarah Sachs: notion, so we[00:37:03] Simon Last: actually, yeah, we didn't make any special concepts at all.[00:37:06] swyx: They're interested to the motion notifications that I would've got,[00:37:09] Sarah Sachs: they can just like write a task to a database that the other agent's task to listening to, or they can actually call a web book to the agent, like they can just add the agent. Okay.[00:37:17] Simon Last: Yeah, I mean, this is something that, that we're still working on.I, I think we, you know, like, like generally, generally the way we do these things is, you know, you first make it possible, maybe like a sort of janky way. So I, I, I think the way I set ‘em up is like, you know, we created like a new database that was sort of like issues mm-hmm. That the custom agents were, were experiencing, and then gave them all access to file an issue and then the manager has access to, to read the issues.Um, and that works pretty well, essentially like, like give it its own like internal issue tracker just for the agents. And then, you know, if that becomes a, a concept that seems useful, generally maybe we will think of how to package it in. But I mean, generally we try to just keep it to composing the primitive if we can.You know, another example of this is we have no built-in memory concept. Memory is, is just pages and databases. And so if you wanna give a memory, just give it a page and give it. Edit access to that page and the[00:38:03] swyx: human can edit it. Agent can edit[00:38:04] Simon Last: it. Yeah. And so that works, that pattern works extremely well on it.And you know, depending this case, you can have it be just a page or it could be an entire database with, you know, or, you know, I can have sub pages is is pretty on what you can do with that.[00:38:15] Alsesio: So when I was setting this up, uh, I connected my inbox and it was like, do you wanna use Gmail or Notion Mail? And I'm like, I don't wanna use Eater, I just want you to do it.I'm curious how you think about, you know, notion, mail, notion, calendar, all of these kind of ui ux interfaces, full stack[00:38:29] Simon Last: notion.[00:38:30] Alsesio: Yeah. When like at the same time you have the agents abstracting them away from you in a way, you know, how do you spend like the product calories so to speak?[00:38:37] Simon Last: Yeah, I mean, I think it's pretty important that you don't have to use, not your mail to connect to the mail capability.So we can just connect to Gmail or, or whatever you want, uh, to use. And we're thinking of the mail service as being really great to the extent that it's really agent built, right? So maybe the mail app is just sort of a prepackaged agent that helps you automate your, your inbox.[00:39:00] Alsesio: Yeah, the auto labeling is great.Think[00:39:03] Sarah Sachs: the, when we, um, integrate with Gmail for instance, we have a series of tools available that are available via MCP or API to Gmail. When we integrate with Notion Mail, we have the Notion Mail engineering team to build us the, um, exact right tools that optimize latency, optimize performance and quality.They own that quality. Um, there's product leads there. They're directly thinking about the user problems that happen in mail. So it tends to be when we build integrations and connections, we build natively first. Um, and then think about, um, extending them generally just because it's also easier. Mm-hmm. Um, um, to build natively first.Um, so that tends to be how we phase things out.[00:39:43] swyx: Talking about integrations, you prompted me, so I gotta ask. M-C-P-C-L-I. What's going on? What's the[00:39:48] Simon Last: Yeah. Opinion. I think, I mean, I'm, I'm definitely bullish and excited about cli. I think there's a few really cool things about cli. So one really cool thing is like, um, is that it's in the terminal environment, so it gets a bunch of extra power.So it, you know, for example, it can like, like paginating and cursor through like long outputs. Um, and it has a progressive disclosure inherently. Uh, so, you know, you don't see all the tools at once. It's just, you see the CLI wrapper and you can like use the, the help commands and, and, and read files. And then I think the most important thing that's, that's super cool is that there, it's also inherently a, a bootstrapped.So if there's an issue, uh, the agent can debug and fix itself within the same environment that it uses the tool.[00:40:30] swyx: Mm.[00:40:30] Simon Last: Right. Like, you know, I think I saw a tweet this morning. Someone said, you know, my agent didn't have a browser, so I asked it to make all a browser tool and within a hundred lines of code, it gave itself a little browser, like, like wrapping the, the, the chromium API, um.That's pretty incredible. And then if there was a bug, it would just immediately try to fix it. Mm-hmm. Right. On the other hand, if you use an, you know, if you use like of, of the Chrome dev tools, MCP, I've had this issue where like, like sometimes the transport gets like messed up. If it gets messed up, the agent has no way to fix itself.It, it no longer has a browser, it's, it's not broken. Right. I think that's, that's pretty fundamental, but I would say like a lot of the, the bad things about it can be fixed. Uh, so I think like, as a progressive disclosure, that can be fixed with, with right harness. Like, it, it obviously doesn't make sense to show it all the tools all the time.That's not really inherent to the MCP protocol. It's just like how you wrap it and use it.[00:41:16] swyx: There's many poorly built MCPs because we didn't know.[00:41:19] Simon Last: Yeah, yeah. I mean it was just early, like, like the obvious thing is, uh, you know, to start with is, is to just show it all the tools and it's like, okay, now we have a hundred tools.Yeah. And like the tool calling actually works. So let's of[00:41:28] swyx: your success[00:41:29] Simon Last: give it a way to like, like filter to source the tools. So yeah, I would say like broadly speaking, I'm really bullish on cli. I'm still bullish on CPS and in a certain environment. I think in, in particular, CP is really great for when you want sort of like a narrow, lightweight agent.I think there's, there's definitely a lot of use cases where, where you don't want like a full coding agent with a compute run time. And also you want it to be like more tightly permissioned. MCP inherently has a really strong permission model, like all you can do is call the tools. A CLI is a little bit murkier.It's like, can I access the, if PI token are you, like, properly sort of like re-encrypt the token so it can't like exfiltrate it, it introduce a lot of like, like new issues, which are. Real and hard to solve. And MCP is just like the dumb simple thing that works and it that it's pretty good.[00:42:12] Sarah Sachs: I'll add two more perspectives, not from it working well for Notion, but how notion like commits to both platforms.Notion is dedicated to being the best system of record for where people do their enterprise work. So we will always support our MCP and so far as other people are using cps, right? So regardless of our perspective, we've put a lot of effort into our MCP and we have a fantastic team that we're building, um, to do more there.And the second thing I'll say, I think, um, we all think a lot, but lately I've been thinking a lot about making sure there's a value alignment and pricing, um, with capability.[00:42:43] swyx: Literally our next question[00:42:44] Sarah Sachs: and. Needing language to execute deterministic tasks feels wasteful and requiring on a language model to interface with third party providers seems wasteful for tasks that don't require it.And particularly because our custom agents are using usage-based pricing. We think of pricing as like the barrier of entry for use of our product, and we're quite committed to making sure that it's not wasteful. Um, not just because it's a bad deal for our customers, but it's also bad business. We wanna have as many buyers, like there's a, there's an elasticity of demand and so if we can have our agents properly execute code that calls on CLI deterministically, it's a one-time cost, right?Versus constantly having a language model integrate with an MCP over and over and over and paying those like repeated token fees and it's happening outside the cash window, then you're paying for it over and over and over and it's just kind of unnecessary and less deterministic when it doesn't have to be.[00:43:36] Alessio: Yeah, the open-endedness I think is like, the main thing is like, well, if I go write code to just call an API, I would never use an MCP. But then you need an NCP sometimes when you know what to call, but you don't want it to restart versus like, I think the it built a browser from scratch is like, it's great when you're doing it on your own, but like if your customers were having your AI write a browser from scratch every time and you had to pay the token cost of that, yeah.You'd be like, no, no. The Chrome dev tools CP is actually pretty great. Just use that. I'm curious, how do you make that decision? Like should it be. Just straight API call very narrow. Should it be an MCP? Should it be super open-ended?[00:44:10] Sarah Sachs: Do you mean for when we ship notion capabilities or when we add capabilities to[00:44:13] Alessio: notion[00:44:14] Sarah Sachs: AI or,[00:44:14] Alessio: I mean, you might have a capability that the only way to do is an open-ended agent, like an agent with a coding sandbox.[00:44:21] Sarah Sachs: Yeah. In Notion ai they're not explicit, not We also ship an MCP.[00:44:24] Alsesio: Yeah. Yeah. In B,[00:44:25] Sarah Sachs: yeah.[00:44:26] Alsesio: Internally. Okay. Like is there ever a discussion of like, we're not gonna ship it because we're not able to tie it down? Or are you happy to just like,[00:44:33] Sarah Sachs: um, no. I mean, there are a lot of things where we choose not to use MCP because we wanna add more high touch to quality.I think search an agent to find is like the largest instance of that, where we have. Um, slack and linear and Jira search and notion that is not using necessarily the search MCP functionality that is provided by those companies. And that's because it's quite critical we think, to how our agent trajectories work is for us to have a little bit more control on the functionality of the search journey.And so it usually comes from quality and there's a long tail of things and that's why we built an MCP client or an MCP server, excuse me, so that people can connect whatever they want. There's that long tail, right. But we, for search particularly, I would say that's like the primary entry point, but there are other connections as well that it's a little bit of secret sauce a

Favour Obasi-ike, MBA, MS discusses the critical differences between "fat" (bloated) and "lean" (optimized) websites. He explains how large file sizes, unoptimized images, and poor technical setups negatively impact search engine rankings and user experience. Favour emphasizes technical SEO, structured data, and webpage indexing, providing actionable advice on compressing assets, improving site speed, and preparing websites for future search engine updates. The conversation highlights the value of consistent content creation and building a strong technical foundation for long-term business success.Who is this for?Business owners, web developers, digital marketers, and SEO professionals looking to optimize their websites for better search engine indexing, faster load times, and improved user experience. It's valuable for understanding technical web performance, managing page bloat, optimizing images, and implementing structured data for long-term growth.Key Moments & Timestamps00:00 - Introduction: Fat vs. Lean websites, technical SEO, and webpage indexing.02:08 - Impact of large images and web bloat on site speed and rankings.05:35 - Defining a lean website and benefits of compressing files (e.g., compressor.io).07:21 - Checking website health and page sizes using Siteliner and GTmetrix.09:38 - Historical context: Median mobile homepage file size increased from 845 KB in 2015 to 2.3 MB in 2025.29:08 - Importance of legible fonts and responsive design for users and search bots.31:34 - Utilizing structured data and Schema.org to enhance technical SEO.50:50 - Jason's feedback on Favour's consistency and the value of qualitative feedback.01:00:50 - Timeline for SEO results (3-12 months for initial impact, 6-24 months for realistic growth).01:05:29 - Final summary: Building lean websites with crucial semantics for future-proofing (2026+).FAQsQ: What is the difference between a fat and a lean website?A: A fat website has excessive bloat (large images, heavy code), slowing load times and hurting SEO. A lean website uses compressed assets and efficient code, resulting in faster load times, better UX, and improved indexing.Q: How can I check if my website is fat or lean?A: Use Siteliner.com to check page sizes and identify thick/thin pages. GTmetrix.com helps analyze loading speed and performance grade.Q: Does compressing images ruin their quality?A: Not necessarily. It depends on lossless vs. lossy compression. Tools like compressor.io reduce file sizes while maintaining acceptable visual quality.Q: How long does it take to see results from technical SEO improvements?A: Generally, 3 to 12 months for initial results, but expect 6 to 24 months for more realistic and substantial long-term growth.Action StepsAudit Your Website: Use Siteliner and GTmetrix to evaluate page sizes, load speeds, and site health.Compress Assets: Identify large files and use compressor.io to reduce size without sacrificing quality.Implement Structured Data: Visit schema.org to apply structured data mapping to help search engines understand your content.Optimize for Mobile & Accessibility: Ensure body text is at least 16px and scales up to 200% without breaking layout.Book a Consultation: Reach out to Favour Obasi-ike at info@playinc.online or via his booking link for a personalized website audit and SEO strategy or visit Favour's quick link here.Ready to Rank? Book Your SEO & Web Dev Services Today

Send us Fan MailAmazon has implemented a significant update regarding alt text functionality within A+ content, impacting how sellers previously handled indexing. This video explains that Amazon now uses artificial intelligence to automatically generate alt text for all images. This change affects amazon listing optimization and amazon seo practices, requiring sellers to adapt their strategies for enhanced brand content moving forward.Fix lost rankings fast before traffic drops further get a full listing strategy review now: https://bit.ly/4jMZtxu#AmazonSEO #AmazonFBA #EcommerceTips #AmazonListing #keywordranking Want free resources? Dowload our Free Amazon guides here:Amazon Catalog Spring Cleaning: https://hubs.ly/Q046BVfp0Growth Email Marketing Strategies: https://hubs.ly/Q04457QF0Amazon Proft Margin Defense 2026: https://hubs.ly/Q042trRH0Amazon SEO Toolkit 2026: https://bit.ly/4oC2ClTAmazon Seller Strategy Report 2026: https://bit.ly/3YN1RME2026 Ecommerce Website & SEO Readiness Checklist: https://hubs.ly/Q040Jg0M0Amazon 2026 PPC guide: https://bit.ly/4lF0OYXTimestamps00:00 - Amazon alt text removed update00:30 - AI generated alt text explanation01:00 - Why this hurts keyword indexing01:26 - Loss of Spanish keyword ranking01:50 - What sellers should do now02:07 - Focus on crawlable text and FAQs--------------------------------------------------------------------------Follow us:LinkedIn: https://www.linkedin.com/company/28605816/Instagram: https://www.instagram.com/stevenpopemag/Pinterest: https://www.pinterest.com/myamazonguys/Twitter: https://twitter.com/myamazonguySubscribe to the My Amazon Guy podcast:My Amazon Guy podcast: https://podcast.myamazonguy.comApple Podcast: https://podcasts.apple.com/us/podcast/my-amazon-guy/id1501974229Spotify: https://open.spotify.com/show/4A5ASHGGfr6s4wWNQIqyVwSupport the show

This week's episode is basically with AI environments and search overlapping, we're now at a point where we need to go BEYOND indexation INTO Induction. Our content needs to rise above the consensus and showcase a Unique Indentification Signal.And no place better than Confessions of An SEO and no person more able to introduce you to the process of of Induction than Carolyn Holzman.This marks a move from a search environment to an "AI recommendation era" requiring new optimization strategies.Last week's episode: ⁠https://www.confessionsofanseo.com/podcast/how-to-make-your-content-a-magnet-for-ai-citation-season-6-ep-12/⁠Mentioned in the show:Written in the Logs: GoogleOther's Gemini Alignment - Season 5, Ep 48Subscribe to Confessions of an SEO™ wherever you get your podcasts. Your subscribing and download sends the message that you appreciate what is being shared and helping others find Confessions of an SEO™An easy place to leave a review ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://www.podchaser.com/podcasts/confessions-of-an-seo-1973881⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠You can find me on⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Carolyn Holzman⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ - Linkedin⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠American Way Media⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Google Directly⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠AmericanWayMedia.com⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Consulting AgencyNeed Help With an Indexation Issue? - reach out Text me here - 512-222-3132Music from Uppbeathttps://uppbeat.io/t/doug-organ/fugue-stateLicense code: HESHAZ4ZOAUMWTUA

Jesse is joined by Rubin Miller—former Dimensional Fund Advisors insider, founder and CIO of Peltoma Capital Partners, author of the Fortunes and Frictions blog, and national chess master—for a wide-ranging conversation about how investment philosophy, behavioral discipline, and real-world client psychology intersect. Rubin pulls back the curtain on how factor tilts like small-cap, value, and profitability work. The discussion moves beyond theory into practice, tackling commoditization in passive investing, the tradeoffs between index funds and structured tilts, and the uncomfortable truth that great investment decisions can look wrong for years. Rubin also challenges spreadsheet-only thinking, defending dollar-cost averaging for large windfalls as a behavioral risk-management tool rather than a return-maximization tactic. Throughout, he emphasizes that the most important portfolio design principle isn't squeezing out incremental expected return—it's building a strategy clients can stick with when markets inevitably deliver noise, volatility, and surprise. The result is a candid, technically grounded, and deeply human look at what long-term investing actually demands. Key Takeaways: • Factor tilts—such as small-cap, value, and profitability—are grounded in decades of academic research but require patience to endure long droughts. • Expected returns dominate over long horizons; unexpected returns dominate in the short run. • Spreadsheet-optimal strategies are not always behaviorally optimal strategies. • The best portfolio is one an investor can stay invested in during extreme volatility. • Financial advisors add value not just through portfolio construction but through expectation management. • Long-term investing success depends less on brilliance and more on discipline, humility, and staying on the bus. Key Timestamps:(01:30) – Meet Ruben Miller (05:47) – Passive vs Indexing (13:22) – Factor Tilts Explained (20:21) – Rules and Rebalancing (24:21) – Is 100 Percent S&P Enough (26:16) – Small Caps vs Large Caps (32:00) – Dollar Cost Averaging Debate (36:13) – Behavioral Finance and Regret (39:07) – Chess vs Investing Feedback Loops (44:42) – Fortunes and Frictions, and Peltoma Capital Key Topics Discussed: The Best Interest, Jesse Cramer, Wealth Management Rochester NY, Financial Planning for Families, Fiduciary Financial Advisor, Comprehensive Financial Planning, Retirement Planning Advice, Tax-Efficient Investing, Risk Management for Investors, Generational Wealth Transfer Planning, Financial Strategies for High Earners, Personal Finance for Entrepreneurs, Behavioral Finance Insights, Asset Allocation Strategies, Advanced Estate Planning Techniques Mentions: Website: https://www.peltomacapital.com/ LinkedIn: https://www.linkedin.com/in/rubinmiller/ Mentions: https://www.fortunesandfrictions.com/  More of The Best Interest: Check out the Best Interest Blog at https://bestinterest.blog/ Contact me at jesse@bestinterest.blog Consider working with me at https://bestinterest.blog/work/ The Best Interest Podcast is a personal podcast meant for education and entertainment. It should not be taken as financial advice, and is not prescriptive of your financial situation.

Favour Obasi-ike, MBA, MS delivers a tutorial on why Pinterest is a search engine, not social media, and how to connect it with Google Search Console for SEO impact.Pinterest is the least skipped ad platform while YouTube is the most, and Pinterest ads cost two to thirty cents versus dollars elsewhere.He covers claiming your business account, how earned media works exclusively on Pinterest, and why a pin lives three to five months compared to an Instagram post's 19 to 72 hours. Favour shares a client case study where organic image impressions grew from 54.1 million to 154 million in three months with zero ad spend, with Pinterest ranking in the top three linking sites.The conversation covers MCP servers, Google's crawl budget drop from 15 to two megabytes, why 67 percent of searches result in zero clicks, and why GoDaddy is not scalable.Mark recommends WordPress, and Shira shares how evergreen content generates leads years after posting.Book SEO Services? Save These Quick Links for Later>> ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Book SEO Services with Favour Obasi-ike⁠>> Visit Work and PLAY Entertainment website to learn about our digital marketing services>> ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Join our exclusive SEO Marketing community⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠>> Read SEO Articles>> ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Subscribe to the We Don't PLAY Podcast⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠>> Purchase Flaev Beatz Beats Online>> Favour Obasi-ike Quick Links>> Start Recording your Podcast with Riverside Today | Sign Up with My Affiliate Link HereTimeline and Timestamps[00:08] Introduction — Pinterest SEO Marketing on Clubhouse.[02:53] Pinterest: least skipped ad platform vs. YouTube.[04:02] Pinterest is a search engine for images.[07:04] You cannot be on ChatGPT if not on Google.[08:15] Claiming your Pinterest business account.[10:02] Earned media — only Pinterest offers it.[12:05] Pin lifespan: 3–5 months vs. Instagram: 19–72 hours.[19:00] Tuna on WebMCP and AI impact on SEO.[21:56] Google crawl budget: 15 MB down to 2 MB.[23:35] 67% of Google searches result in zero clicks.[33:09] Why GoDaddy is not scalable.[40:03] Mark: WordPress — own your website.[58:45] Pinterest + Google Search Console: the perfect blend.[60:30] Case study: 54.1M to 154M impressions organically.[73:49] Shira: evergreen content still generates leads.[79:50] SEO scorecard tool — 10 questions, instant report. 93:01] 97% of Pinterest searches are unbranded.[95:32] Pinterest and Amazon partnership.Memorable Quotes"Pinterest is the least skipped ad platform. YouTube is the most — people pay to skip ads.""If you drop the P, it's interest. Pinterest is interest, literally.""You build a house on land you don't own." — Mark, on closed-source builders."Keep putting out your message, even when nobody's watching, because someone is." — Shira"67% of Google searches don't result in a click. That's a culture shift." — TunaFAQs AnsweredIs Pinterest social media?On the personal side, yes. On the business side, it is a visual search engine where you own 100% of your data through a claimed account.What is earned media?When someone saves your paid pin and revisits it later, you earn impressions without spending again — dividends on your ad spend.Why not GoDaddy?It lacks code injection, scalable pop-ups, and flexibility. WordPress is recommended for full ownership and SEO control.How long does Pinterest SEO take?It depends on domain authority and consistency — no fixed timeline, but articles linked to Pinterest accelerate results.Key TakeawaysClaim your website on Pinterest Business. Track Pinterest as a linking site in Google Search Console. Pins live 3–5 months versus hours on Instagram. 97% of Pinterest searches are unbranded. Own your site on WordPress. Evergreen content compounds and generates leads long after posting.KeywordsPinterest SEO, Google Search Console, earned media, Pinterest ads, visual search engine, domain authority, crawl budget, WordPress, claimed accounts, unbranded search, evergreen content, zero-click searches, SEO scorecard, MCP servers.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

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Real-time analytics at a petabyte scale isn't just a technical challenge; it's a business survival requirement. Catherine Johnson, VP of Global Solutions Engineering at Hydrolix, joins the show to deconstruct the "impossible" architecture required to power the 2025 Super Bowl broadcast for Fox Sports. From managing 1.4 petabytes of daily log data to the brutal reality of why traditional auto-scaling fails during mission-critical events, Catherine reveals the strategic framework behind being a "Truth Teller" in the high-stakes world of Solutions Engineering.Key Takeaways1. Data Architecture as a Competitive Moat- Normalization is Non-Negotiable: At a petabyte scale, you cannot afford "dirty" data. Success requires normalizing disparate CDN logs—matching units (ms vs. s) and handling recursive URL encoding—into a single, queryable schema.- Indexing vs. Regex: Computational intensity kills performance. Strategic indexing for exact matches must replace regular expressions for high-frequency queries to avoid massive, costly table scans.- Schema Flexibility: Implementing multiple schemas on a single table allows for both granular technical deep-dives and high-level executive overviews without duplicating storage.2. Scaling Strategies for "High-Intensity" Events- The Limits of Auto-scaling: For predictable surges like the Super Bowl, relying on auto-scaling is a risk. Pre-scaling to 3x expected peak ensures availability when AWS regional compute limits are hit.- Multi-Region Redundancy: True global scale often exceeds the capacity of a single cloud region. Architecting for multi-region deployment is a requirement, not an option, for Tier-1 broadcast events.- Segregated Query Pools: Prevent "compute competition" by isolating resources. Executive dashboards, SRE monitoring, and ad-hoc troubleshooting should never fight for the same compute cycles.3. Solutions Engineering as "Truth Telling"- The Trust-Based Framework: A Solution Engineer's (SE) primary role isn't selling—it's building trust through accurate empathy. If the product isn't a fit, say it. Protecting your professional reputation outlasts any single sales cycle.- Root Cause Inquiry: When a customer asks for a feature or query optimization, pause. Don't answer the technical question until you've uncovered the business outcome they are trying to achieve.- Business Mapping: Every technical requirement must map directly to a business requirement. If it doesn't, it's just unnecessary complexity.4. The "Break-Fast" Learning Philosophy- Fearless Experimentation: The learning curve is shortened by breaking things in dedicated environments. If you only follow the "happy path" of a tutorial, you haven't actually learned the system.- Bridging Data Realities: There is often a gap between how data is stored for performance and how it looks in the real world. Success in SE requires the ability to bridge these two perspectives for the customer.Chapters:00:10 - Introduction: Meet Catherine Johnson00:50 - The Origins of Hydrolix: Solving the CDN Log Crisis06:10 - Deep Dive: Behind the Scenes of the 2025 Super Bowl10:14 - When the Path Changes: Adjusting Architecture Mid-Season14:25 - Multi-Region Deployment & AWS Compute Limits16:51 - Half-Second Query Times: How to Segregate Compute25:49 - The Non-Obvious Skills of Top-Tier SEs31:32 - The "Farming" Lesson: Understanding How Businesses Make Money37:04 - Lightning RoundVisit our website - https://saassessions.com/Connect with me on LinkedIn - https://www.linkedin.com/in/sunilneurgaonkar/

Freight markets are turning earlier than usual. In this episode of Supply Chain Secrets, Caroline Weaver and Lars Jensen break down sharp declines in quoted rates, early signs that the Chinese New Year peak has already passed, and what actual paid spot rates are signaling across key trades.Lars also walks through a real-world example showing how choosing the wrong index in an index-linked contract can materially impact costs, underscoring why detail matters as indexing gains traction. The conversation then turns to tariffs and the Red Sea, where new signals—from carrier routing decisions to a fresh Houthi warning—suggest risk may not be fully behind us yet.A practical discussion on what shippers should watch as volatility continues into 2026.

When Paul first started this show, indexing and target-date funds were not very popular at all, as the world experienced a decade where large U.S. companies struggled to generate any returns for investors. Fast forward another decade, and indexing and target date funds are now all the rage as investors believe that “indexing” is synonymous with great returns, low fees, and wealth in retirement. Indexing may sound like diversification, but Paul explains what really happens when millions of investors choose this path for their portfolios. Later in the episode, Paul shares where fund companies make the biggest mistakes with indexing and provides a blueprint for capturing market returns that won't leave you overweight in a few companies.   Want to cut through the myths about retirement income and learn evidence-based strategies backed by over a century of data? Download our free Retirement Income Guide now at paulwinkler.com/relax and take the stress out of planning your retirement.   This material is for general educational purposes only and is not personalized investment, financial, tax, or legal advice. Past performance does not guarantee future results. Nothing here is an offer, solicitation, or recommendation for any security or strategy. All financial decisions involve risk, and you should consult qualified professionals before acting on this information. Advisory services offered through Paul Winkler, Inc., an SEC-registered investment adviser.

As 2026 gets underway, early signals are already diverging. In this episode of Supply Chain Secrets, Caroline Weaver and Lars Jensen are joined by Matthew Chicalace of Hellmann Worldwide Logistics to break down the growing gap between quoted and paid rates, early NYFI movements post–Chinese New Year, and what those signals really say about the market.The conversation also dives into rising interest in index-linked contracts, how forwarders and carriers are approaching contract season, and why volatility remains structural. Finally, Lars unpacks the latest developments around the Red Sea reopening, geopolitical risks tied to Iran and Greenland, and how quickly trade lanes could shift again in 2026.A timely discussion on how shippers are navigating uncertainty—and why flexibility and alignment matter more than ever.

SEO Secrets for 2026: A Deep Dive into Schema Markup, Structure, and Indexing with Favour Obasi-ike with Favour Obasi-Ike | Sign up for exclusive SEO insights.Happy New Year! This episode provides a focused, actionable roadmap for business and website owners aiming to dominate search rankings in 2026. It moves beyond basic SEO to reveal three foundational, yet often overlooked, strategies: two internal and one external.Favour synthesizes the strategy into a winning formula: Schema + Structure + Speed. A website that excels in these three areas becomes a "triple threat"—it's understood by algorithms, technically sound, and delivers a superior user experience, making it the preferred result in search.Call to Action: For professional SEO help, you can book a call at playinc.online, listen to the podcast at wedontplaypodcast.com, or contact the me via email (info@playinc.online). More resource links available below.Core Framework for 2026 SEO Success:Internal Secret #1: Master Schema MarkupWhat it is: Explicit code (microdata) that tells search engines and AI exactly what your content means (e.g., Article, FAQ, Product).Why it matters: It "future-proofs" your content by turning pages into structured assets that AI-driven search tools can understand and feature correctly. It's the essential language for communicating with modern algorithms.Internal Secret #2: Prioritize Logical Site StructureWhat it is: A clear, hierarchical blueprint for your website using heading tags (H1, H2, H3, etc.) in the correct, sequential order.Why it matters: It serves both crawlers and users. It guides algorithms through your content while creating an intuitive, trustworthy experience for visitors. A confused structure repels both.External Secret: Leverage Automatic IndexingWhat it is: A technical method using an API to submit thousands of pages per day to Google, bypassing the strict 10-URL daily limit of manual submission in Search Console.Why it matters: For content-rich sites, it ensures your work is efficiently seen and indexed by Google, preventing valuable content from being overlooked.Episode Timestamps[03:30] Internal Secret #1: Master Schema MarkupWhat it is: Explicit code that tells search engines and AI what your content means.Why it matters: It future-proofs content, turning pages into structured assets that modern algorithms and AI search tools can correctly understand and feature.[13:00] Internal Secret #2: Prioritize Logical Site StructureWhat it is: A clear hierarchy using heading tags (H1, H2, H3) in correct order.Why it matters: It guides search engine crawlers and creates an intuitive, trustworthy experience for human users. Poor structure confuses both.[22:00] External Secret: Leverage Automatic IndexingWhat it is: Using an API to submit thousands of pages/day to Google, bypassing manual limits.Why it matters: Ensures large volumes of content are efficiently seen and indexed. A case study showed 27% of a 17M-page portfolio indexed in two weeks.[29:30] Key Conclusion: The "Triple Threat" FormulaThe winning formula is Schema + Structure + Speed. This combination ensures a site is understood by algorithms, technically sound, and delivers a superior user experience.[31:00] Call to Action: For help, book a call at playinc.online, listen to the podcast, or contact the host via email/LinkedIn.Next Steps for Booking A Discovery Call | Digital Marketing + SEO Services:>> ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Need SEO Services? Book a Complimentary SEO Discovery Call with Favour Obasi-Ike⁠ here⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠>> Visit our Work and PLAY Entertainment website to learn about digital marketing services.>> ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Join our exclusive SEO Marketing community⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠>> Read SEO Articles>> ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Subscribe to the We Don't PLAY Podcast⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

- Introduction and Interview Setup (0:10) - China's Technological Dominance (2:28) - Brighteon.ai's Growth and Challenges (4:27) - AI Hallucinations and Brighteon.ai's Solution (11:35) - Future of AI and Technological Advancements (14:48) - Gold and Silver Market Analysis (55:15) - Conclusion and Call to Action (1:19:11) - Brightelearn.ai Book Creation Process (1:20:57) - Expansion and Classification of Research Library (1:27:01) - Challenges in Indexing and Classifying Books (1:27:49) - Critique of ChatGPT and Brightelearn.ai's Unique Approach (1:34:37) - Decentralization and Open Source Models (1:36:50) - Technocracy and the Role of AI in Control Systems (1:40:59) For more updates, visit: http://www.brighteon.com/channel/hrreport  NaturalNews videos would not be possible without you, as always we remain passionately dedicated to our mission of educating people all over the world on the subject of natural healing remedies and personal liberty (food freedom, medical freedom, the freedom of speech, etc.). Together, we're helping create a better world, with more honest food labeling, reduced chemical contamination, the avoidance of toxic heavy metals and vastly increased scientific transparency. ▶️ Every dollar you spend at the Health Ranger Store goes toward helping us achieve important science and content goals for humanity: https://www.healthrangerstore.com/ ▶️ Sign Up For Our Newsletter: https://www.naturalnews.com/Readerregistration.html ▶️ Brighteon: https://www.brighteon.com/channels/hrreport ▶️ Join Our Social Network: https://brighteon.social/@HealthRanger ▶️ Check In Stock Products at: https://PrepWithMike.com

In this episode of Lead-Lag Live, I sit down with Stephen Sikes, Chief Operating Officer at Public, to explore how artificial intelligence is transforming retail investing, brokerage platforms, and portfolio construction.From AI-powered research to custom-built indexes and the rise of agentic brokerage, Sikes explains how new tools are giving individual investors access to capabilities once reserved for institutions and what risks and responsibilities come with that shift.In this episode:– How AI research tools are changing how retail investors analyze stocks– What it means to build custom indexes using natural language– The rise of agentic brokerage and automated portfolio management– Where AI can help investors and where human judgment still matters– Why the next generation of brokerages may look nothing like the lastLead-Lag Live brings you inside conversations with the financial thinkers who shape markets. Subscribe for interviews that go deeper than the noise.Start your adventure with TableTalk Friday: A D&D Podcast at the link below or wherever you get your podcasts!Youtube: https://youtube.com/playlist?list=PLgB6B-mAeWlPM9KzGJ2O4cU0-m5lO0lkr&si=W_-jLsiREjyAIgEsSpotify: https://open.spotify.com/show/75YJ921WGQqUtwxRT71UQB?si=4R6kaAYOTtO2V Support the show

Questions? Comments?Don and Tom question a surprising Wall Street Journal column arguing that annuities should become the default option in 401(k) plans. They explore why the idea is gaining traction, where the logic breaks down, and how the insurance industry benefits when complexity outpaces understanding. Along the way, they dig into the real shortcomings of annuities—fees, opacity, inflation risk, liquidity traps—and why “guarantees” often mask the true cost. Listener questions follow, covering tax-efficient stock cleanup at Schwab, spouse disagreements over individual stock picking, automatic ETF withdrawals at Vanguard, and building Dimensional portfolios inside Aspire plans.0:04 Don's rant: “What the world needs now is… more annuities?”1:20 WSJ's argument: make annuities the 401(k) default2:05 Why income complexity doesn't justify default annuities3:01 Do annuities actually solve longevity risk?3:29 Inflation, joint-life costs, and who really wins4:20 Insurance industry reputation and the unanswered criticisms5:15 High fees, opacity, and why mistrust is earned5:59 Are annuity sales tactics the real barrier?7:02 Should annuities be in 401(k)s at all? Don vs. Tom7:36 Why annuities are mostly sold, not bought9:10 Liquidity traps and major-life-event risks10:01 Why “plans” matter more than “products”10:57 Listener questions: why nobody calls anymore11:14 Q1: Selling a brokerage full of individual stocks at Schwab12:46 Q1b: How to convince a spouse who loves stock picking14:21 Indexing vs. anecdotal evidence16:21 SPIVA data and why active managers lose17:02 Q2: Can Vanguard automate ETF withdrawals?19:05 Fractional shares and why purchases are allowed20:25 Q3: Aspire 403(b) options and DFA overload23:46 How many DFA funds do you really need?24:44 Micro-cap risks and portfolio sprawl25:42 Tom's pumpkin-patch grandkid cameoLearn more about your ad choices. Visit megaphone.fm/adchoices

Don and Tom question a surprising Wall Street Journal column arguing that annuities should become the default option in 401(k) plans. They explore why the idea is gaining traction, where the logic breaks down, and how the insurance industry benefits when complexity outpaces understanding. Along the way, they dig into the real shortcomings of annuities—fees, opacity, inflation risk, liquidity traps—and why “guarantees” often mask the true cost. Listener questions follow, covering tax-efficient stock cleanup at Schwab, spouse disagreements over individual stock picking, automatic ETF withdrawals at Vanguard, and building Dimensional portfolios inside Aspire plans. 0:04 Don's rant: “What the world needs now is… more annuities?” 1:20 WSJ's argument: make annuities the 401(k) default 2:05 Why income complexity doesn't justify default annuities 3:01 Do annuities actually solve longevity risk? 3:29 Inflation, joint-life costs, and who really wins 4:20 Insurance industry reputation and the unanswered criticisms 5:15 High fees, opacity, and why mistrust is earned 5:59 Are annuity sales tactics the real barrier? 7:02 Should annuities be in 401(k)s at all? Don vs. Tom 7:36 Why annuities are mostly sold, not bought 9:10 Liquidity traps and major-life-event risks 10:01 Why “plans” matter more than “products” 10:57 Listener questions: why nobody calls anymore 11:14 Q1: Selling a brokerage full of individual stocks at Schwab 12:46 Q1b: How to convince a spouse who loves stock picking 14:21 Indexing vs. anecdotal evidence 16:21 SPIVA data and why active managers lose 17:02 Q2: Can Vanguard automate ETF withdrawals? 19:05 Fractional shares and why purchases are allowed 20:25 Q3: Aspire 403(b) options and DFA overload 23:46 How many DFA funds do you really need? 24:44 Micro-cap risks and portfolio sprawl 25:42 Tom's pumpkin-patch grandkid cameo Learn more about your ad choices. Visit megaphone.fm/adchoices

 Wall Street noise is loud—Barry Ritholtz shows you How Not to Invest. In this episode, we cut through models, headlines, and hype to focus on the few decisions that actually compound. Barry shares a practical framework for decision-making grounded in behavioral finance: why models are “wrong but useful,” how to build a checklist to filter signal from noise, and why broad indexing should anchor most portfolios. We dig into direct indexing for tax management, the attention economy's impact on investors, and the real effects of tariffs and Fed timing on markets and Main Street. He also maps the “two businesses” every investor must master: deploying capital quietly for decades and consuming information without getting captured by clickbait. If you're curious about AI's productivity boost, global mean reversion beyond the U.S., and realistic expectations after back-to-back strong years, this conversation is for you. By the end, you'll know How Not to Invest—and what to do instead.Connect with Barry Ritholtz: hownottoinvestbook.com Chapters:00:00 – Introduction02:32 – “All models are wrong, some are useful” & avoiding media-driven fear16:21 – Wealthy vs. middle-class planning: indexing, direct indexing, tax loss harvesting20:19 – AI's real impact on advisors, workflows, and productivity24:46 – Where are the opportunities? U.S. vs. developed ex-U.S., mean reversion35:14 – Rates, the Fed, soft landing probabilities & realistic return expectations49:33 – Gino wraps it up We're here to help create multifamily entrepreneurs... Here's how: Brand New? Start Here: https://jakeandgino.mykajabi.com/free-wheelbarrowprofits Want To Get Into Multifamily Real Estate Or Scale Your Current Portfolio Faster? Apply to join our PREMIER MULTIFAMILY INVESTING COMMUNITY & MENTORSHIP PROGRAM. (*Note: Our community is not for beginner investors)

Today's Post - https://bahnsen.co/47Ly2Ab Understanding Index Funds and Their Evolution: A Comprehensive Analysis In this episode of the Friday Dividend Cafe, David Bahnsen, Chief Investment Officer of The Bahnsen Group, delves into the topic of index funds and their evolution over the years. He discusses the impact of index funds on the investment landscape, comparing their performance and risk profile to other investment approaches like dividend growth investing. David examines the significant growth in index fund ownership, changes in the composition of the S&P 500, and the implications of market capitalization-weighted indices. He also addresses common concerns, such as market liquidity, valuation risks, and the role of financial advisors in tailoring portfolios to individual needs. The discussion is aimed at providing a deeper understanding of the current dynamics in indexing and its relevance to both investors and financial advisors. 00:00 Introduction to Dividend Cafe 00:17 The Evolution of Indexing 00:59 Indexing vs. Dividend Growth Investing 03:39 Understanding Market Beta 07:27 The Role of Advisors and Fees 13:06 The Growth of S&P 500 Index Funds 22:35 Systemic Risks and Market Dynamics 31:13 Conclusion and Final Thoughts Links mentioned in this episode: DividendCafe.com TheBahnsenGroup.com

Steve Roud is a Librarian, folklore scholar and creator of the Roud Folk Song Index, which contains upwards of 750,000 entries to around 45,000 English language folk songs, as found in books, recordings, manuscripts and other sources the world over. His index, and ‘Roud Numbers' (a numbering system employed to identify the same song across many different titles) are widely acclaimed for the scope, breadth, depth and impact. Steve worked as a local studies Librarian in the London Borough of Croydon, and also served as Honorary Librarian for the Folklore Society for eighteen years. He has published books on calendar custom, popular tradition, folk belief, London lore, children's games, and folk drama. In 2004, he was the winner of the Folklore Society's Katharine Briggs Folklore Award for The Penguin Guide to the Superstitions of Britain and Ireland. In 2009, he was one of five people to be awarded the Gold Badge of the English Folk Dance and Song Society. This award recognises "those who have made unique or outstanding contributions to the art or science of folk dance, music or song, and/or those who have given exceptional support in furthering the aims of the Society”. For four years now, Steve has been visiting the NFC, parsing through our manuscript and book, broadside and pamphlet collections for entries to add to his index. He is an incredibly gifted, meticulous and generous scholar, who is always glad to share his expertise with us, particularly in discussion around the inherent problems in the description, cataloguing and indexing of folklore materials. It was an honour, and a great pleasure to host Steve at the NFC recently, and during his visit (for our collective benefit) I subjected him to a 75 minute interview, in which we discussed his index, the problems inherent in describing folk song, approaches to the cataloguing of folklore, conducting research in folklore archives, and the problems inherent in the digitisation of folklore records and some scholarly critique of the NFC's online platform Dúchas.ie. As a health warning for this episode - listeners (or viewers!) hoping to listen to scores of lovely ballads will be sorely disappointed, as our discussion essentially consists of nerding out about folklore indexes for over an hour. Steve's Folk Song Index can be found here, at the website of the Vaughan William's Memorial Library: https://www.efdss.org/vwml-catalogues-and-indexes/vwml-help/roud-indexes-help For a wonderful talk of Steve's at the Library of Congress, see here: https://www.youtube.com/watch?v=zVTMoN4Arvo My thanks especially to Veronica, Andrew and Dominic in UCD Communications, for their support of the podcast, and for filming this episode!

On this episode of Animal Spirits: Talk Your Book, ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Michael Batnick⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ and ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Ben Carlson⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ are joined by Ehren J. Stanhope, CFA, Principal, Chief Investment Strategist at Canvas Custom Indexing to discuss: the evolution of investment products, why 2019 changed everything, how financial advisors are using Canvas with their clients and why technology is such an important component in this process. Find complete show notes on our blogs... Ben Carlson's ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠A Wealth of Common Sense⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Michael Batnick's ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠The Irrelevant Investor⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Feel free to shoot us an email at ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠animalspirits@thecompoundnews.com⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ with any feedback, questions, recommendations, or ideas for future topics of conversation. Check out the latest in financial blogger fashion at The Compound shop: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://idontshop.com⁠⁠⁠⁠⁠⁠⁠⁠⁠ Investing involves the risk of loss. This podcast is for informational purposes only and should not be or regarded as personalized investment advice or relied upon for investment decisions. Michael Batnick and Ben Carlson are employees of Ritholtz Wealth Management and may maintain positions in the securities discussed in this video. All opinions expressed by them are solely their own opinion and do not reflect the opinion of Ritholtz Wealth Management. See our disclosures here: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://ritholtzwealth.com/podcast-youtube-disclosures/⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ The Compound Media, Incorporated, an affiliate of ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Ritholtz Wealth Management⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠, receives payment from various entities for advertisements in affiliated podcasts, blogs and emails. Inclusion of such advertisements does not constitute or imply endorsement, sponsorship or recommendation thereof, or any affiliation therewith, by the Content Creator or by Ritholtz Wealth Management or any of its employees. For additional advertisement disclaimers see here ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://ritholtzwealth.com/advertising-disclaimers⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠. Learn more about your ad choices. Visit megaphone.fm/adchoices