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Max talks with ferry pilot Sarah Rovner, founder of Full Throttle Aviation, about her adventures and challenges flying planes across continents. Sarah stumbled into ferry flying when she helped deliver a plane and quickly found herself flying everything from gliders to agricultural aircraft across Central America and even the Atlantic. Her unique edge wasn't just piloting—it was handling the complex international paperwork required for cross-border flights. Sarah explains the nuances of flying foreign-registered aircraft, using handlers, and dealing with customs and regulatory hurdles in countries like Mexico and Canada. She shares hair-raising tales like flying over the Arctic in winter in a Cessna 210, discovering a failed axle, and performing repairs in subzero temps. She's faced oxygen failures, ferry tank malfunctions, and the infamous “ice bridging” during Atlantic crossings. Despite the flat-rate pay and frequent mechanical delays, Sarah loves the freedom, camaraderie, and adventure. She also trains and mentors pilots, including retirees and aspiring time-builders, emphasizing the importance of judgment over just stick-and-rudder skills. Her company now provides aircraft imports, paperwork, and check rides, and she encourages others interested in ferry work to learn multiple aircraft types and fly smart. If you're getting value from this show, please support the show via PayPal, Venmo, Zelle or Patreon. Support the Show by buying a Lightspeed ANR Headsets Max has been using only Lightspeed headsets for nearly 25 years! I love their tradeup program that let's you trade in an older Lightspeed headset for a newer model. Start with one of the links below, and Lightspeed will pay a referral fee to support Aviation News Talk. Lightspeed Delta Zulu Headset $1199 Lightspeed Zulu 3 Headset $899Lightspeed Sierra Headset $699 My Review on the Lightspeed Delta Zulu Send us your feedback or comments via email If you have a question you'd like answered on the show, let listeners hear you ask the question, by recording your listener question using your phone. News Stories Helicopter crash in New York's Hudson River kills six FAA requests unleaded fuel pireps FAA Winding Down Flight Service After string of near-collisions, FAA wants to change Class C at Palm Beach Unither Achieves First Hydrogen-powered Helicopter Flight Pilot who died in Duxford SR22 plane crash was 'inexperienced' Failure to discontinue unstabilized approach leads to crash Pilot seriously injured on third flight in new airplane Unsecured penguin caused helicopter crash in South Africa Mentioned on the Show Buy Max Trescott's G3000 Book Call 800-247-6553 Lightspeed Delta Zulu Headset Giveaway Video of the Week: SR22 Pilot Induced Oscillation Max's Max Impact FLYING magazine column: February Stop the prop by Barry Schiff Free Index to the first 282 episodes of Aviation New Talk So You Want To Learn to Fly or Buy a Cirrus seminars Online Version of the Seminar Coming Soon – Register for Notification Check out our recommended ADS-B receivers, and order one for yourself. Yes, we'll make a couple of dollars if you do. Get the Free Aviation News Talk app for iOS or Android. Check out Max's Online Courses: G1000 VFR, G1000 IFR, and Flying WAAS & GPS Approaches. Find them all at: https://www.pilotlearning.com/ Social Media Like Aviation News Talk podcast on Facebook Follow Max on Instagram Follow Max on Twitter Listen to all Aviation News Talk podcasts on YouTube or YouTube Premium "Go Around" song used by permission of Ken Dravis; you can buy his music at kendravis.com If you purchase a product through a link on our site, we may receive compensation.
Matt Waldman discusses the quarterback prospects from the 2025 NFL Draft in this RSP Solo Cast. https://youtu.be/_rE4WRKesk8 Topics State of quarterback development in the NFL. Thoughts on confidence as a tangible/measurable asset with quarterback evaluation. Quick hits on 12 quarterback prospects from the 2025 NFL Draft class. Thoughts on Hunter Dekkers. Announcing the two contest winners from last week's RB sleeper question. Now entering its 20th season, learn more about Matt Waldman's RSP — the most in-depth analysis of offensive skill position players available (QB, RB, WR, and TE). Or if you already know the deal, go ahead and pre-order (you know you want to) for $21.95. Matt's new RSP Dynasty Rankings and Two-Year Projections Package is available for $24.95 If you're a fantasy GM interested in purchasing past publications for $9.95 each, the 2012-2024 RSPs also have a Post-Draft Add-on that's included at no additional charge. Best yet, proceeds from sales are set aside for a year-end donation to Darkness to Light to combat the sexual abuse of children.
DJ Bauer joins Colter Nuanez on the SWX Spotlight to recap the Class C tournaments from Butte. Plus: Travis DeCuire on Montana's first-round matchup with Wisconsin and Jetton Ailes of the Billings Central girls team on winning back-to-back state titles.
Send us a textThe Class C RV is one of the most popular types of motorhomes you can buy.But there is a multitude of RV manufacturers that make the Class C RV. And many of them do not build their motorhomes with good overall quality.So this podcast will help you find out which brands are the best to choose from when you are in the market for a new Class C RV.To watch my video on how to improve ride and handling on Class C motorhomes click this link - https://youtu.be/Dfue7PRy9rQ
Capital Raised and Deal Structure Dr. Raj Venkatramani, a pediatric oncologist turned real estate capital allocator, has raised approximately $20 million from investors, 95% of whom are doctors, since launching REIDOC Capital in 2021. His typical deal size ranges from $10 million to $30 million, and on average he raises $2 million per deal. His primary focus is on multifamily properties of at least 100 units, targeting Class A and B assets and new construction projects, rather than Class C properties, following hard-earned lessons from the market peak in 2021. Leveraging Group Capital for Better Returns Dr. Raj secures better economics for his investors by leveraging group capital. While a typical syndication might offer a 15% IRR with a 6-7% preferred return, Raj pools investors together to negotiate, for example, an 80/20 split (instead of 70/30) and an 8% preferred return, effectively increasing investor returns without requiring larger individual commitments. Underwriting and Market Lessons His underwriting philosophy is focused on analyzing sponsor assumptions, particularly around rent growth projections, occupancy expectations, expense growth, and debt structure. He talks about how bad assumptions can make a weak deal look good, citing an early investment in a Class C Florida asset where insurance costs doubled (from $196K to $400K in one year) and variable rate debt wiped out NOI. Transition to Ground-Up Development Raj expanded the kinds of deal he invests in from value-add to ground-up development and now partners on new construction projects in Sioux Falls, South Dakota, a market he believes is undervalued. His due diligence process before partnering with a sponsor involves a multi-year vetting process, meeting them at conferences, reviewing past deals, and even visiting completed projects before committing capital. LinkedIn as a Primary Investor Source Perhaps most surprising is how he sources capital: 90% of his investors have never met him in person, and nearly all were acquired through LinkedIn and referrals. His LinkedIn strategy? Post consistently for two years, even when people don't engage, until they reach out ready to invest. Key Takeaway: Trust but Verify His biggest lesson? Trust but verify—real estate is not medicine, where all parties have the same goal. Misalignment of incentives is real, and capital allocators must be rigorous in due diligence to avoid costly mistakes. *** Explore the world of real estate capital allocators—a fresh approach to financing that's reshaping the industry. In this series, I talk with allocators, investors, sponsors, and service providers to give you an inside look at this fast-growing space. PLUS, subscribe to my free newsletter for real estate investors and gain access to: * Introductions to sponsors, allocators, and investment opportunities. * Insights drawn from my 30+ years of experience in real estate investing. * Hacks and tactics for raising capital to help you scale your real estate portfolio. Visit GowerCrowd.com/subscribe
Updates on MSU-Northern Skylights basketball and Class C sports
In 2022, Just Stop Oil protestors threw tomato soup on a Van Gogh painting in London. The world collectively gasped, but some UK lawmakers responded by supporting fewer investments in new oil projects. On this episode, meet one of those soup-throwers, and hear from two other people who have been part of creative protests: a spokesperson from an anti-circumcision group that wears all white with giant, red splotches on the groin area; and a woman who organized a college campus protest featuring thousands of sex toys to rally against Texas gun laws. GUESTS: Anna Holland: Member of Just Stop Oil, a nonviolent civil resistance group demanding that the UK Government stop licensing all new oil, gas and coal projects. In 2022, alongside Phoebe Plummer, they threw tomato soup onto Vincent van Gogh's "Sunflowers" painting in London's National Gallery Harry Guiremand: Spokesperson for the anti-circumcision group, Bloodstained Men and Their Friends. They protest wearing all white with red splotches of paint over their groin Jessica Jin: Organizer of Cocks Not Glocks, protesting Texas laws that allow concealed handguns on college campuses, while openly carrying sex toys is a Class C misdemeanor Support the show: https://www.wnpr.org/donateSee omnystudio.com/listener for privacy information.
Donald Trump has officially won the presidency, and his policies are already set to disrupt the rental housing market in major ways. With 12 million illegal immigrants set to be deported and 10-20% tariffs on Mexico, Canada, and China, landlords, property managers, and real estate investors need to prepare for massive shifts in rental demand, pricing, and tenant demographics. In this episode of OKC Real News, host Landon Whitt sits down with real estate expert Michael to break down: • How mass deportations will impact Class C and D rental properties • Why tariffs on building materials will increase costs for landlords and drive higher rents in Class A and B properties • How government-backed rental programs (Section 8, VA housing, workforce housing) will become critical for investors • Why a strong property manager is more important than ever for cutting vacancies and optimizing cash flow • Best investment opportunities in transitional housing, distressed properties, and high-demand rental markets The next four years will create both risks and opportunities for landlords—learn how to protect your investments and even expand your portfolio during this market shift. SCHEDULE YOUR CONSULTATION NOW https://www.okcreal.com/investors
Old Capital Real Estate Investing Podcast with Michael Becker & Paul Peebles
Did you go? If not…these were the themes, of the 3-day event, between apartment operators, investors, investment sales brokers and lenders. This nationwide conference had optimism in multifamily for the long term…but continued challenges (higher interest rates, higher cap rates, and the lack of distressed assets coming to the market) for the shorter term. 1. NMHC Meeting Overview: The meeting was held at the Aria Hotel in Las Vegas, attended by around 10-12,000 people from various sectors of the multifamily industry. 2. Market Sentiment: Despite challenges, there is optimism about the fundamentals of apartment ownership and investing improving. The sentiment among brokers is more optimistic than among operators. 3. Class A and C Properties: Class A properties are in high demand, while Class C properties are currently out of favor. There is limited availability of properties on the market, and the bid-ask spread remains wide. 4. Interest Rates and Financing: Interest rates are expected to stay higher, but there is some expectation of rate cuts in the future. Banks are starting to open up to lending again after a period of tightening. 5. Distressed Properties: There is some distress in the market, particularly among properties financed with bridge loans. However, the overall percentage of distressed properties is relatively small. 6. Dallas-Fort Worth Market: The Dallas-Fort Worth market is highly favored, with strong fundamentals and high demand. 7. Future Outlook: Michael & James believe that the market will improve, with rent growth expected to return and supply issues easing. They suggest that now might be a good time to consider buying multifamily properties. New apartment supply is coming down rapidly and rental growth is coming back after 138 consecutive weeks of year-over-year decline. 8. Events and Networking: The Old Capital Bus Tour is on March 28th and a virtual Old Capital speaker series on February 5th are upcoming events for networking and learning more about the multifamily market. RSVP to OldCapitalPodcast.com Overall, the discussion highlights cautious optimism in the multifamily housing market, with a focus on strategic buying and navigating current challenges. Are you interested in learning more about how Multifamily Syndications work? Please visit SPIADVISORY.COM to understand more about Michael Becker's Real Estate Syndication business.
Today, Lane Kawaoka is investing in real estate syndications, which invest in Class C & B Multi-Family apartments, RV Parks, mobile homes, and assisted living facilities because of the USA's demand for affordable housing – not rich-people Class-A assets. His mission is to help regular people make good deals that were once only accessible to the rich.The passive income from investing in stabilized rental properties made it possible for me to move back home to Hawaii , where the cost of paradise is 10%+ the cost of living and 30% less than the pay for comparable jobs in the US mainland. There, I was able to live a lifestyle where I could bike to work. It did not take me long, however, to finally quit my day job and ditch the e-bike for a Mercedes.Summary of the PodcastIntroductions and background Graham and Kevin introduce their guest Lane Kawaoka, CEO of The Wealth Elevator, who is joining them from Hawaii, which is a day behind their current time. They discuss Lane's background in real estate investing, starting with single-family rental properties and then transitioning to larger commercial real estate deals and syndications.The 1% rental ruleLane explains the "1% rule" for evaluating rental properties - the monthly rent should be at least 1% of the property's purchase price. He discusses how this is easier to achieve in secondary and tertiary markets compared to high-cost primary markets like California. He also highlights the benefits of focusing on cash flow over pure appreciation.Scaling up to commercial real estateAs Lane's portfolio grew, he found the hassle of managing numerous single-family rentals became too much. He pivoted to investing in larger commercial real estate deals through syndications, which provide more institutional-quality assets and economies of scale. This allowed him to focus more on value-add strategies and force appreciation.The Wealth Elevator serves different investor profilesLane discusses his book "The Wealth Elevator" and how it aims to guide investors at different net worth levels on appropriate investment strategies. He is passionate about empowering the "first generation" of wealth creators, providing free educational content, and building a community of like-minded investors.Future plans and diversificationWhile real estate remains Lane's core focus, he is also exploring opportunities in other asset classes like micro private equity and digital marketing agency acquisitions. He emphasizes the importance of having a clear financial track record and P&L when evaluating new investments, rather than "flying blind".The Next 100 Days Podcast Co-HostsGraham ArrowsmithGraham founded Finely Fettled ten years ago to help business owners and marketers market to affluent and high-net-worth customers. Graham founder of MicroYES, a Partner for MeclabsAI, which combines the world's biggest source of 10,000 marketing experiments with AI. Find Graham on LinkedIn.Kevin ApplebyKevin specialises in finance transformation and implementing business change. He's the COO of
We have the meats...2024's breakout designer & the mind behind some of the most profoundly impactful pyromusical field shaping's in 2024, Nathan Dexter; climbs in the ring for COBRA-CON 2025's Class C Championship in April. He raps with us this week on the experience so far. Support the Sh*t Show!! Contribute -> Patreon Hang with us -> Discord Buy some Merch, balls, DB25 Cables or leave us a Voicemail (we'll play it on-air)!
Discover How Crown Capital Raised $1.2M in Just 45 Minutes!How do top capital raisers secure millions in record time? In this powerhouse episode, we sit down with Crown Capital's elite team—Noel Parnell, Lupe Chow, and Tiffany Spann—to unpack their exact playbook for raising $1.2 million in just 45 minutes. From leveraging strategic marketing and investor relations to building a rock-solid database, they reveal the real systems that make capital flow effortlessly. This episode is a masterclass in scaling your portfolio and accelerating wealth creation. Don't miss out—tune in now!Key Takeaways to Listen For:Consistency is Key in Capital Raising: - Crown Capital's success stems from consistent investor engagement through social media, email campaigns, and webinars. Staying visible builds trust and keeps investors ready to deploy capital when opportunities arise.Diversified Marketing Strategies Drive Investor Interest - The team leverages multiple channels, including LinkedIn, Instagram, and webinars, to attract and nurture investors. Tracking engagement metrics helps refine strategies for maximum impact.Building Strong Relationships Leads to Faster Funding -– Raising $1.2M in 45 minutes wasn't luck—it was the result of years of investor relationship-building. Trust and credibility are built over time, making it easier for investors to commit when deals arise.Tailor Investment Opportunities to Investor Preferences:- Understanding investor risk tolerance and asset class preferences ensures smoother capital raises. Crown Capital segments investors based on interest in Class A vs. Class C properties, making fundraising more efficient.A Winning Deal Presentation is Critical - Deals that are visually appealing, well-structured, and offer strong returns attract investor attention faster. Crown Capital ensures their pitch decks and webinars clearly communicate key investment benefits and projected returns.About Tim MaiTim Mai is a real estate investor, fund manager, mentor, and founder of HERO Mastermind for REI coaches.He has helped many real estate investors and coaches become millionaires. Tim continues to help busy professionals earn income and build wealth through passive investing.He is also a creative marketer and promoter with incredible knowledge and experience, which he freely shares. He has lifted himself from the aftermath of war, achieving technical expertise in computers, followed by investment success in real estate, management skills, and a lofty position among real estate educators and internet marketers.Tim is an industry leader who has acquired and exited well over $50 million worth of real estate and is currently an investor in over 2700 units of multifamily apartments.Connect with TimWebsite: Capital Raising PartyFacebook: Tim Mai | Capital Raising Nation Instagram: @timmaicomTwitter: @timmaiLinkedIn: Tim MaiYouTube: Tim Mai
On this episode of The Property Profits Podcast, host Dave Dubeau chats with Zach Bagby, a determined and resourceful real estate entrepreneur based in Denver, Colorado. Zach shares his inspiring journey from house hacking to managing multifamily syndications while balancing a full-time job and a growing family. Zach dives deep into the lessons learned from one of his most challenging deals—a condemned 16-unit property in Council Bluffs, Iowa. He recounts how the city's sudden shutdown of the building pushed him to the brink, forcing him to sell his personal residence and assets to protect his investors. Despite these hurdles, Zach's unwavering commitment and integrity kept him moving forward, proving that even the hardest setbacks are opportunities for growth. Key takeaways from the episode: How Zach built a niche with Class C multifamily properties in Colorado and beyond. What went wrong in his most challenging deal and the lessons he learned from it. The importance of transparency, integrity, and resilience in real estate investing. How Zach leverages broker relationships and tools like Crexi to find deals. Tips for balancing a full-time job, family life, and a real estate business. ======================== ======================== ================= Want to grow your real estate investing business and portfolio? You're in the right place. Welcome to the Property Profits Real Estate Podcast
We continue the one-fuse slow burn to COBRA-CON 2025 and the Class C Championship this week with two-time PGI Class C Unlimited Participant, JP Hanson! Support the Sh*t Show!! Contribute -> Patreon Hang with us -> Discord Buy some Merch, balls, DB25 Cables or leave us a Voicemail (we'll play it on-air)!
Old Capital Real Estate Investing Podcast with Michael Becker & Paul Peebles
Have you ever heard the saying, “Slow and steady wins the race?” For Cory and Candice Muldrow, this timeless principle is the foundation of their success in apartment investing. The Muldrows began their journey in 2017 with the purchase of an 18-unit multifamily building, all while juggling full-time W2 careers. With a keen eye for value, they rehabilitated and repositioned this older asset, transforming it from a CLASS C- to a thriving CLASS B+ property. But they didn't stop there. In 2019, they took a bold step forward, acquiring a 102-unit apartment building that was in need of a fresh vision and new management. Through hard work and determination, the Muldrows not only revitalized this property but also made the leap to become full-time apartment investors. Since then, they've acquired hundreds of units, impacting the lives of both their tenants and investors. Their story proves that with the right mindset and strategy, transitioning from a W2 job to full-time real estate investing is not just a dream – it's a reality. Does apartment investing call to you? Are you ready to explore how you, too, can break free from the 9-to-5 grind and build lasting wealth in real estate? The Muldrows are living proof that it's possible, and they're here to show you how it can be done.
Don't let Michael Karr's YouTube brand fool you. The dude's has come a long way in the short time he's honed his craft as a choreographed show designer. "The Novice" Pyro...well...isn't so much a novice any more. Jamie, AJ, and Bo talk with Mike about his journey, his previous experience in pyromusical competitions so far, and his next big challenge...COBRA-CON 2025 and their inaugural Class C Championship. Support the Sh*t Show!! Contribute -> Patreon Hang with us -> Discord Buy some Merch, balls, DB25 Cables or leave us a Voicemail (we'll play it on-air)!
Short term loan maturities are a death sentence in a down market, which is causing major pain for sponsors and Limited Partners. Since mid-2022, multifamily prices have plummeted as high as 40%, and transaction volume is down 80%. Class C, in particular, has taken the largest beating. Currently, lenders are giving loan extensions to sponsors who can raise more money, thereby reducing their exposure. In turn, the lenders are hoping they'll be able to foreclose at the end of the extension, and sell the properties in a better market. Brian Burke, President and CEO of Praxis Capital, has been through several cycles, and believes that 2025 will be a transition year for multifamily.
Are you just starting out in real estate investment and finding yourself drawn to cheap properties, thinking they're the best option for quick profits? You're not alone! In today's episode, we delve into the real-life challenges and costly mistakes that come with investing in cheap properties. Join Brian Davis and Andrew Cushman, founder of Vantage Point Acquisitions, as he shares invaluable insights from his personal experiences and why cheap properties are often the most expensive. This episode is packed with real-world advice, practical solutions, and guidance on how to avoid these pitfalls, making it a must-watch for any investor looking to optimize their portfolio. With a more selective investment strategy focusing on class B properties, Andrew shows how you can reduce risk, attract better property managers, and still achieve solid returns. His tips will guide you in making smarter decisions that minimize risk and maximize long-term success in real estate. 10 Things You'll Learn in This Episode: 1. The Hidden Costs of Cheap Properties -why inexpensive real estate investments often come with unforeseen expenses that can erode your profits. 2. Lessons from a Real Estate Nightmare -how Andrew Cushman's experience with a 348-unit property taught him the true cost of ""affordable"" investments. 3. The Impact of Crime and Location -learn why the quality of a neighborhood directly influences the success of a property. 4. The Role of Tenant Turnover in Profitability -discover how high eviction rates and tenant churn affect your bottom line. 5. The Importance of Screening Investments -understand the criteria Andrew uses to evaluate properties and avoid costly mistakes. 6. Class C vs. Class B Properties -find out why class B properties in better neighborhoods often yield more consistent and profitable returns. 7. The Challenge of Property Management in Rough Areas -insights into why good property managers avoid working in bad neighborhoods—and what that means for investors. 8. Minimizing Downside Risk -how focusing on risk mitigation can lead to better investment decisions and long-term success. 9. Breaking the Spreadsheet Illusion -why properties that look great on paper often fall short in real-life scenarios. 10. Strategies for Smarter Real Estate Investing -practical advice for avoiding the beginner traps and building a more resilient and lucrative portfolio. Key Takeaways:
COBRA-CON becomes a battleground in 2025 as it's the latest venue to host a 1.4G pyromusical competition...and it's going to be a stellar inaugural year that features three really talented choreographed show designers. John Hanson, Michael (The Novice Pyro) Karr, and Nathan Dexter gear up for an early season Class C slobberknocker this April! Support the Sh*t Show!! Contribute -> Patreon Hang with us -> Discord Buy some Merch, balls, DB25 Cables or leave us a Voicemail (we'll play it on-air)!
Join seasoned real estate experts Jim Pfeifer and Brian Burke as they unpack the landscape of multifamily investing in 2025. In this insightful discussion, they navigate the complexities of today's market, from construction delays to debt challenges, offering their seasoned perspectives on where opportunities lie. The conversation dives deep into why multifamily properties continue to attract investors, while honestly addressing the headwinds facing the industry - from operational challenges to the evolving dynamics between buyers and sellers. Burke and Pfeifer share their unvarnished take on realistic return expectations and offer a nuanced analysis of different property classifications, from stable Class A assets to the more challenging Class C properties. Whether you're a seasoned real estate investor or just getting started, this episode provides valuable insights into market trends, risk assessment, and potential opportunities emerging in 2025. Don't miss Burke's optimistic outlook on the year ahead and learn why timing might be everything in the current market cycle. Perfect for: Real estate investors, property managers, market analysts, and anyone interested in understanding the future of multifamily real estate investment. Don't forget to subscribe and leave a review to stay updated on future episodes packed with investment strategies, market insights, and more! Take our Survey: PassivePockets.com/Survey Disclaimer: The content of this podcast is for informational purposes only. All host and participant opinions are their own. Investment in any asset, real estate included, involves risk, so use your best judgement and consult with qualified advisors before investing. You should only risk capital you can afford to lose. Remember that past performance is not indicative of future results. This podcast may contain paid advertisements or other promotional materials for real estate investment advisers, investment funds, and investment opportunities, which should not be interpreted as a recommendation, endorsement or testimonial by PassivePockets, LLC or any of its affiliates. Viewers must conduct their own due diligence and consider their own financial situations before engaging with any of the advertised offerings, products or services. PassivePockets, LLC disclaims all liability for direct, indirect, consequential or other damages arising out of reliance on information and advertisements presented in this podcast. Contact Us At: jimpfeifer@biggerpockets.com
Send us a textThere is a lot of confusion about Class B Plus RVs and how they compare to Class C RVs.So this podcast clears up that confusion and also covers the pros and cons of both types of RVs. Then you can decide which one you feel will work best for you and your style of travel and camping.Here is the link to the Class C suspension upgrade video mentioned in this podcast - https://youtu.be/Dfue7PRy9rQ
Episode 364 Show Notes Topic of the show: What is Your On-course Heading? From Patron AS On this week's show, AG and RH discuss “on course heading”. What does it mean and why does ATC need to know? We also discuss our opinions on the latest developments in New York airspace, Class C redesigns, and more of your awesome aviation feedback. Merry Christmas! Links: https://reason.org/aviation-policy-news/newark-air-traffic-control-shifted-to-philadelphia-tracon/#:~:text=The%20long%2Dplanned%20move%20shrinks,of%2085%25%20fully%20certified%20controllers. Timely Feedback: 1. Listener IP sent an article about the issues at N90 and PHL approach. 2. SGAC Patron SE shared their driveway Christmas light redesign and RDU airspace redesign proposal. 3. Patron CL discusses spin training Feedback 1. Patron JH talks about flight following vs advisory frequencies 2. Patron RJI shares about a recent trip to the local tower. Have a great week and thanks for listening! Visit our website at OpposingBases.com You can support our show using Patreon or visiting our support page on the website. Keep the feedback coming, it drives the show! Don't be shy, use the “Send Audio to AG and RH” button on the website and record an audio message. Or you can send us comments or questions to feedback@opposingbases.com. Music bumpers by audionautix.com. Third party audio provided by liveatc.net. Holiday/Christmas audio used during this special episode is from https://www.youtube.com/@audiolibrary_ no copyright music in library for creators. Music: Deck the Halls - Jingle Punks https://www.youtube.com/watch?v=5VO3w8na3CA Legal Notice The views and opinions expressed on Opposing Bases Air Traffic Talk are for entertainment purposes only and do not represent the views, opinions, or official positions of the FAA, Penguin Airlines, or the United States Army. Episodes shall not be recorded or transcribed without express written consent. For official guidance on laws, rules, and regulations, consult an aviation attorney or certified flight instructor.
How to Trade Stocks and Options Podcast by 10minutestocktrader.com
Welcome to today's deep dive into the stock market! In this video, we uncover the key differences between common stocks and preferred stocks—two critical investment options that can shape your portfolio's performance. Whether you're a beginner trader or an experienced investor, understanding these distinctions is crucial. You'll also learn how to sharpen your trading psychology, apply actionable strategies, and make more informed trading decisions. We explore common stocks vs. preferred stocks, breaking down their similarities and differences, including their risk profiles, return potential, and voting rights. You'll discover how common stocks can generate both capital gains and dividends, while preferred stocks focus on steady dividend income, offering lower risk but less upside potential. Using tools like Outlier's data, we analyze how these stock types behave in real-world market conditions and provide practical trading tips, such as leveraging the 10/20/50 moving average rule to analyze charts, identify trends, and set up effective stop-loss strategies. We'll also dive into trading psychology, discussing how to manage emotions, avoid common mistakes, and develop systems that give you a competitive edge in the market. Highlighted stocks in this video include Google (GOOG vs. GOOGL), where we discuss the differences between Class A and Class C shares, and case studies of Amazon, Facebook, and Apple to demonstrate actionable insights and strategies for strong uptrends. If you're ready to enhance your trading edge and gain a deeper understanding of these important concepts, stick around. Don't miss out on these valuable insights that could transform the way you approach the stock market. #StockMarket #CommonStocks #PreferredStocks #CapitalGains #DividendInvesting #MarketAnalysis #TradingPsychology #OutlierTrading #SmartTrading #InvestmentTips Subscribe to OVTLYR for more videos on stock analysis, trading strategies, and tools that help you save time, make money, and win with less risk. Don't forget to hit the like button and share this video to spread the knowledge! See you in the next one!
On the Big Dog 7 Sports Show, we are joined by Nick Gable from Duke. We talk girls and boys basketball. Then Coach White calls in to discuss their bye week and upcoming game against Tyrone in the Class C 8 Man Semifinals
We have announced our first speaker, friend of the show Dylan Patel, and topic slates for Latent Space LIVE! at NeurIPS. Sign up for IRL/Livestream and to debate!We are still taking questions for our next big recap episode! Submit questions and messages on Speakpipe here for a chance to appear on the show!The vibe shift we observed in July - in favor of Claude 3.5 Sonnet, first introduced in June — has been remarkably long lived and persistent, surviving multiple subsequent updates of 4o, o1 and Gemini versions, for Anthropic's Claude to end 2024 as the preferred model for AI Engineers and even being the exclusive choice for new code agents like bolt.new (our next guest on the pod!), which unlocked so much performance from Claude Sonnet that it went from $0 to $4m ARR in 4 weeks when it launched last month.Anthropic has now raised an additional $4b from Amazon and made an incredibly well received update of Claude 3.5 Sonnet (and Haiku), making significant improvements in performance over its predecessors:Solving SWE-BenchAs part of the October Sonnet release, Anthropic teased a blink-and-you'll miss it result:The updated Claude 3.5 Sonnet shows wide-ranging improvements on industry benchmarks, with particularly strong gains in agentic coding and tool use tasks. On coding, it improves performance on SWE-bench Verified from 33.4% to 49.0%, scoring higher than all publicly available models—including reasoning models like OpenAI o1-preview and specialized systems designed for agentic coding. It also improves performance on TAU-bench, an agentic tool use task, from 62.6% to 69.2% in the retail domain, and from 36.0% to 46.0% in the more challenging airline domain. The new Claude 3.5 Sonnet offers these advancements at the same price and speed as its predecessor.This was followed up by a blogpost a week later from today's guest, Erik Schluntz, the engineer who implemented and scored this SOTA result using a simple, non-overengineered version of the SWE-Agent framework (you can see the submissions here). We have previously covered the SWE-Bench story extensively:* Speaking with SWEBench/SWEAgent authors at ICLR* Speaking with Cosine Genie, the previous SOTA (43.8%) on SWEBench Verified (with brief update at DevDay 2024)* Speaking with Shunyu Yao on SWEBench and the ReAct paradigm driving SWE-AgentOne of the notable inclusions in this blogpost are the tools that Erik decided to give Claude, e.g. the “Edit Tool”:The tools teased in the SWEBench submission/blogpost were then polished up and released with Computer Use…And you can also see even more computer use tools given in the new Model Context Protocol servers:Claude Computer UseBecause it is one of the best received AI releases of the year, we recommend watching the 2 minute Computer Use intro (and related demos) in its entirety:Eric also worked on Claude's function calling, tool use, and computer use APIs, so we discuss that in the episode.Erik [00:53:39]: With computer use, just give the thing a browser that's logged into what you want to integrate with, and it's going to work immediately. And I see that reduction in friction as being incredibly exciting. Imagine a customer support team where, okay, hey, you got this customer support bot, but you need to go integrate it with all these things. And you don't have any engineers on your customer support team. But if you can just give the thing a browser that's logged into your systems that you need it to have access to, now, suddenly, in one day, you could be up and rolling with a fully integrated customer service bot that could go do all the actions you care about. So I think that's the most exciting thing for me about computer use, is reducing that friction of integrations to almost zero.As you'll see, this is very top of mind for Erik as a former Robotics founder who's company basically used robots to interface with human physical systems like elevators.Full Video episodePlease like and subscribe!Show Notes* Eric Schluntz* “Raising the bar on SWE-Bench Verified”* Cobalt Robotics* SWE-Bench* SWE-Bench Verified* Human Eval & other benchmarks* Anthropic Workbench* Aider* Cursor* Fireworks AI* E2B* Amanda Askell* Toyota Research* Physical Intelligence (Pi)* Chelsea Finn* Josh Albrecht* Eric Jang* 1X* Dust* Cosine Episode* Bolt* Adept Episode* TauBench* LMSys EpisodeTimestamps* [00:00:00] Introductions* [00:03:39] What is SWE-Bench?* [00:12:22] SWE-Bench vs HumanEval vs others* [00:15:21] SWE-Agent architecture and runtime* [00:21:18] Do you need code indexing?* [00:24:50] Giving the agent tools* [00:27:47] Sandboxing for coding agents* [00:29:16] Why not write tests?* [00:30:31] Redesigning engineering tools for LLMs* [00:35:53] Multi-agent systems* [00:37:52] Why XML so good?* [00:42:57] Thoughts on agent frameworks* [00:45:12] How many turns can an agent do?* [00:47:12] Using multiple model types* [00:51:40] Computer use and agent use cases* [00:59:04] State of AI robotics* [01:04:24] Robotics in manufacturing* [01:05:01] Hardware challenges in robotics* [01:09:21] Is self-driving a good business?TranscriptAlessio [00:00:00]: Hey everyone, welcome to the Latent Space Podcast. This is Alessio, partner and CTO at Decibel Partners. And today we're in the new studio with my usual co-host, Shawn from Smol AI.Swyx [00:00:14]: Hey, and today we're very blessed to have Erik Schluntz from Anthropic with us. Welcome.Erik [00:00:19]: Hi, thanks very much. I'm Erik Schluntz. I'm a member of technical staff at Anthropic, working on tool use, computer use, and Swebench.Swyx [00:00:27]: Yeah. Well, how did you get into just the whole AI journey? I think you spent some time at SpaceX as well? Yeah. And robotics. Yeah. There's a lot of overlap between like the robotics people and the AI people, and maybe like there's some interlap or interest between language models for robots right now. Maybe just a little bit of background on how you got to where you are. Yeah, sure.Erik [00:00:50]: I was at SpaceX a long time ago, but before joining Anthropic, I was the CTO and co-founder of Cobalt Robotics. We built security and inspection robots. These are sort of five foot tall robots that would patrol through an office building or a warehouse looking for anything out of the ordinary. Very friendly, no tasers or anything. We would just sort of call a remote operator if we saw anything. We have about 100 of those out in the world, and had a team of about 100. We actually got acquired about six months ago, but I had left Cobalt about a year ago now, because I was starting to get a lot more excited about AI. I had been writing a lot of my code with things like Copilot, and I was like, wow, this is actually really cool. If you had told me 10 years ago that AI would be writing a lot of my code, I would say, hey, I think that's AGI. And so I kind of realized that we had passed this level, like, wow, this is actually really useful for engineering work. That got me a lot more excited about AI and learning about large language models. So I ended up taking a sabbatical and then doing a lot of reading and research myself and decided, hey, I want to go be at the core of this and joined Anthropic.Alessio [00:01:53]: And why Anthropic? Did you consider other labs? Did you consider maybe some of the robotics companies?Erik [00:02:00]: So I think at the time I was a little burnt out of robotics, and so also for the rest of this, any sort of negative things I say about robotics or hardware is coming from a place of burnout, and I reserve my right to change my opinion in a few years. Yeah, I looked around, but ultimately I knew a lot of people that I really trusted and I thought were incredibly smart at Anthropic, and I think that was the big deciding factor to come there. I was like, hey, this team's amazing. They're not just brilliant, but sort of like the most nice and kind people that I know, and so I just felt like I could be a really good culture fit. And ultimately, I do care a lot about AI safety and making sure that I don't want to build something that's used for bad purposes, and I felt like the best chance of that was joining Anthropic.Alessio [00:02:39]: And from the outside, these labs kind of look like huge organizations that have these obscureSwyx [00:02:44]: ways to organize.Alessio [00:02:45]: How did you get, you joined Anthropic, did you already know you were going to work on of the stuff you publish or you kind of join and then you figure out where you land? I think people are always curious to learn more.Erik [00:02:57]: Yeah, I've been very happy that Anthropic is very bottoms up and sort of very sort of receptive to whatever your interests are. And so I joined sort of being very transparent of like, hey, I'm most excited about code generation and AI that can actually go out and sort of touch the world or sort of help people build things. And, you know, those weren't my initial initial projects. I also came in and said, hey, I want to do the most valuable possible thing for this company and help Anthropic succeed. And, you know, like, let me find the balance of those. So I was working on lots of things at the beginning, you know, function calling, tool use. And then sort of as it became more and more relevant, I was like, oh, hey, like, let's it's time to go work on encoding agents and sort of started looking at SWE-Bench as sort of a really good benchmark for that.Swyx [00:03:39]: So let's get right into SWE-Bench. That's one of the many claims to fame. I feel like there's just been a series of releases related with Cloud 3.5 Sonnet around about two or three months ago, 3.5 Sonnet came out and it was it was a step ahead in terms of a lot of people immediately fell in love with it for coding. And then last month you released a new updated version of Cloud Sonnet. We're not going to talk about the training for that because that's still confidential. But I think Anthropic's done a really good job, like applying the model to different things. So you took the lead on SWE-Bench, but then also we're going to talk a little bit about computer use later on. So maybe just give us a context about why you looked at SWE-Bench Verified and you actually came up with a whole system for building agents that would maximally use the model well. Yeah.Erik [00:04:28]: So I'm on a sub team called Product Research. And basically the idea of product research is to really understand what end customers care about and want in the models and then work to try to make that happen. So we're not focused on sort of these more abstract general benchmarks like math problems or MMLU, but we really care about finding the things that are really valuable and making sure the models are great at those. And so because I've been interested in coding agents, I knew that this would be a really valuable thing. And I knew there were a lot of startups and our customers trying to build coding agents with our models. And so I said, hey, this is going to be a really good benchmark to be able to measure that and do well on it. And I wasn't the first person at Anthropic to find SWE-Bench, and there are lots of people that already knew about it and had done some internal efforts on it. It fell to me to sort of both implement the benchmark, which is very tricky, and then also to sort of make sure we had an agent and basically like a reference agent, maybe I'd call it, that could do very well on it. Ultimately, we want to provide how we implemented that reference agent so that people can build their own agents on top of our system and get sort of the most out of it as possible. So with this blog post we released on SWE-Bench, we released the exact tools and the prompt that we gave the model to be able to do well.Swyx [00:05:46]: For people who don't know, who maybe haven't dived into SWE-Bench, I think the general perception is they're like tasks that a software engineer could do. I feel like that's an inaccurate description because it is basically, one, it's a subset of like 12 repos. It's everything they could find that every issue with like a matching commit that could be tested. So that's not every commit. And then SWE-Bench verified is further manually filtered by OpenAI. Is that an accurate description and anything you'd change about that? Yes.Erik [00:06:14]: SWE-Bench is, it certainly is a subset of all tasks. It's first of all, it's only Python repos, so already fairly limited there. And it's just 12 of these popular open source repos. And yes, it's only ones where there were tests that passed at the beginning and also new tests that were introduced that test the new feature that's added. So it is, I think, a very limited subset of real engineering tasks. But I think it's also very valuable because even though it's a subset, it is true engineering tasks. And I think a lot of other benchmarks are really kind of these much more artificial setups of even if they're related to coding, they're more like coding interview style questions or puzzles that I think are very different from day-to-day what you end up doing. I don't know how frequently you all get to use recursion in your day-to-day job, but whenever I do, it's like a treat. And I think it's almost comical, and a lot of people joke about this in the industry, is how different interview questions are.Swyx [00:07:13]: Dynamic programming. Yeah, exactly.Erik [00:07:15]: Like, you code. From the day-to-day job. But I think one of the most interesting things about SWE-Bench is that all these other benchmarks are usually just isolated puzzles, and you're starting from scratch. Whereas SWE-Bench, you're starting in the context of an entire repository. And so it adds this entirely new dimension to the problem of finding the relevant files. And this is a huge part of real engineering, is it's actually pretty rare that you're starting something totally greenfield. You need to go and figure out where in a codebase you're going to make a change and understand how your work is going to interact with the rest of the systems. And I think SWE-Bench does a really good job of presenting that problem.Alessio [00:07:51]: Why do we still use human eval? It's like 92%, I think. I don't even know if you can actually get to 100% because some of the data is not actuallySwyx [00:07:59]: solvable.Alessio [00:08:00]: Do you see benchmarks like that, they should just get sunsetted? Because when you look at the model releases, it's like, oh, it's like 92% instead of like 89%, 90% on human eval versus, you know, SWE-Bench verified is you have 49%, right? Which is like, before 45% was state of the art, but maybe like six months ago it was like 30%, something like that. So is that a benchmark that you think is going to replace human eval, or do you think they're just going to run in parallel?Erik [00:08:27]: I think there's still need for sort of many different varied evals. Like sometimes you do really care about just sort of greenfield code generation. And so I don't think that everything needs to go to sort of an agentic setup.Swyx [00:08:39]: It would be very expensive to implement.Erik [00:08:41]: The other thing I was going to say is that SWE-Bench is certainly hard to implement and expensive to run because each task, you have to parse, you know, a lot of the repo to understand where to put your code. And a lot of times you take many tries of writing code, running it, editing it. It can use a lot of tokens compared to something like human eval. So I think there's definitely a space for these more traditional coding evals that are sort of easy to implement, quick to run, and do get you some signal. Maybe hopefully there's just sort of harder versions of human eval that get created.Alessio [00:09:14]: How do we get SWE-Bench verified to 92%? Do you think that's something where it's like line of sight to it, or it's like, you know, we need a whole lot of things to go right? Yeah, yeah.Erik [00:09:23]: And actually, maybe I'll start with SWE-Bench versus SWE-Bench verified, which is I think something I missed earlier. So SWE-Bench is, as we described, this big set of tasks that were scraped.Swyx [00:09:33]: Like 12,000 or something?Erik [00:09:34]: Yeah, I think it's 2,000 in the final set. But a lot of those, even though a human did them, they're actually impossible given the information that comes with the task. The most classic example of this is the test looks for a very specific error string. You know, like assert message equals error, something, something, something. And unless you know that's exactly what you're looking for, there's no way the model is going to write that exact same error message, and so the tests are going to fail. So SWE-Bench verified was actually made in partnership with OpenAI, and they hired humans to go review all these tasks and pick out a subset to try to remove any obstacle like this that would make the tasks impossible. So in theory, all of these tasks should be fully doable by the model. And they also had humans grade how difficult they thought the problems would be. Between less than 15 minutes, I think 15 minutes to an hour, an hour to four hours, and greater than four hours. So that's kind of this interesting sort of how big the problem is as well. To get to SWE-Bench verified to 90%, actually, maybe I'll also start off with some of the remaining failures that I see when running our model on SWE-Bench. I'd say the biggest cases are the model sort of operates at the wrong level of abstraction. And what I mean by that is the model puts in maybe a smaller band-aid when really the task is asking for a bigger refactor. And some of those, you know, is the model's fault, but a lot of times if you're just sort of seeing the GitHub issue, it's not exactly clear which way you should do. So even though these tasks are possible, there's still some ambiguity in how the tasks are described. That being said, I think in general, language models frequently will produce a smaller diff when possible, rather than trying to do a big refactor. I think another area, at least the agent we created, didn't have any multimodal abilities, even though our models are very good at vision. So I think that's just a missed opportunity. And if I read through some of the traces, there's some funny things where, especially the tasks on matplotlib, which is a graphing library, the test script will save an image and the model will just say, okay, it looks great, you know, without looking at it. So there's certainly extra juice to squeeze there of just making sure the model really understands all the sides of the input that it's given, including multimodal. But yeah, I think like getting to 92%. So this is something that I have not looked at, but I'm very curious about. I want someone to look at, like, what is the union of all of the different tasks that have been solved by at least one attempt at SWE-Bench Verified. There's a ton of submissions to the benchmark, and so I'd be really curious to see how many of those 500 tasks at least someone has solved. And I think, you know, there's probably a bunch that none of the attempts have ever solved. And I think it'd be interesting to look at those and say, hey, is there some problem with these? Like, are these impossible? Or are they just really hard and only a human could do them?Swyx [00:12:22]: Yeah, like specifically, is there a category of problems that are still unreachable by any LLM agent? Yeah, yeah. And I think there definitely are.Erik [00:12:28]: The question is, are those fairly inaccessible or are they just impossible because of the descriptions? But I think certainly some of the tasks, especially the ones that the human graders reviewed as like taking longer than four hours are extremely difficult. I think we got a few of them right, but not very many at all in the benchmark.Swyx [00:12:49]: And did those take less than four hours?Erik [00:12:51]: They certainly did less than, yeah, than four hours.Swyx [00:12:54]: Is there a correlation of length of time with like human estimated time? You know what I mean? Or do we have sort of more of X paradox type situations where it's something super easy for a model, but hard for a human?Erik [00:13:06]: I actually haven't done the stats on that, but I think that'd be really interesting to see of like how many tokens does it take and how is that correlated with difficulty? What is the likelihood of success with difficulty? I think actually a really interesting thing that I saw, one of my coworkers who was also working on this named Simon, he was focusing just specifically on the very hard problems, the ones that are said to take longer than four hours. And he ended up sort of creating a much more detailed prompt than I used. And he got a higher score on the most difficult subset of problems, but a lower score overall on the whole benchmark. And the prompt that I made, which is sort of much more simple and bare bones, got a higher score on the overall benchmark, but lower score on the really hard problems. And I think some of that is the really detailed prompt made the model sort of overcomplicate a lot of the easy problems, because honestly, a lot of the suite bench problems, they really do just ask for a bandaid where it's like, hey, this crashes if this is none, and really all you need to do is put a check if none. And so sometimes trying to make the model think really deeply, it'll think in circles and overcomplicate something, which certainly human engineers are capable of as well. But I think there's some interesting thing of the best prompt for hard problems might not be the best prompt for easy problems.Alessio [00:14:19]: How do we fix that? Are you supposed to fix it at the model level? How do I know what prompt I'm supposed to use?Swyx [00:14:25]: Yeah.Erik [00:14:26]: And I'll say this was a very small effect size, and so I think this isn't worth obsessing over. I would say that as people are building systems around agents, I think the more you can separate out the different kinds of work the agent needs to do, the better you can tailor a prompt for that task. And I think that also creates a lot of like, for instance, if you were trying to make an agent that could both solve hard programming tasks, and it could just write quick test files for something that someone else had already made, the best way to do those two tasks might be very different prompts. I see a lot of people build systems where they first sort of have a classification, and then route the problem to two different prompts. And that's sort of a very effective thing, because one, it makes the two different prompts much simpler and smaller, and it means you can have someone work on one of the prompts without any risk of affecting the other tasks. So it creates like a nice separation of concerns. Yeah.Alessio [00:15:21]: And the other model behavior thing you mentioned, they prefer to generate like shorter diffs. Why is that? Like, is there a way? I think that's maybe like the lazy model question that people have is like, why are you not just generating the whole code instead of telling me to implement it?Swyx [00:15:36]: Are you saving tokens? Yeah, exactly. It's like conspiracy theory. Yeah. Yeah.Erik [00:15:41]: Yeah. So there's two different things there. One is like the, I'd say maybe like doing the easier solution rather than the hard solution. And I'd say the second one, I think what you're talking about is like the lazy model is like when the model says like dot, dot, dot, code remains the same.Swyx [00:15:52]: Code goes here. Yeah. I'm like, thanks, dude.Erik [00:15:55]: But honestly, like that just comes as like people on the internet will do stuff like that. And like, dude, if you're talking to a friend and you ask them like to give you some example code, they would definitely do that. They're not going to reroll the whole thing. And so I think that's just a matter of like, you know, sometimes you actually do just, just want like the relevant changes. And so I think it's, this is something where a lot of times like, you know, the models aren't good at mind reading of like which one you want. So I think that like the more explicit you can be in prompting to say, Hey, you know, give me the entire thing, no, no elisions versus just give me the relevant changes. And that's something, you know, we want to make the models always better at following those kinds of instructions.Swyx [00:16:32]: I'll drop a couple of references here. We're recording this like a day after Dario, Lex Friedman just dropped his five hour pod with Dario and Amanda and the rest of the crew. And Dario actually made this interesting observation that like, we actually don't want, we complain about models being too chatty in text and then not chatty enough in code. And so like getting that right is kind of a awkward bar because, you know, you, you don't want it to yap in its responses, but then you also want it to be complete in, in code. And then sometimes it's not complete. Sometimes you just want it to diff, which is something that Enthopic has also released with a, you know, like the, the fast edit stuff that you guys did. And then the other thing I wanted to also double back on is the prompting stuff. You said, you said it was a small effect, but it was a noticeable effect in terms of like picking a prompt. I think we'll go into suite agent in a little bit, but I kind of reject the fact that, you know, you need to choose one prompt and like have your whole performance be predicated on that one prompt. I think something that Enthopic has done really well is meta prompting, prompting for a prompt. And so why can't you just develop a meta prompt for, for all the other prompts? And you know, if it's a simple task, make a simple prompt, if it's a hard task, make a hard prompt. Obviously I'm probably hand-waving a little bit, but I will definitely ask people to try the Enthopic Workbench meta prompting system if they haven't tried it yet. I went to the Build Day recently at Enthopic HQ, and it's the closest I've felt to an AGI, like learning how to operate itself that, yeah, it's, it's, it's really magical.Erik [00:17:57]: Yeah, no, Claude is great at writing prompts for Claude.Swyx [00:18:00]: Right, so meta prompting. Yeah, yeah.Erik [00:18:02]: The way I think about this is that humans, even like very smart humans still use sort of checklists and use sort of scaffolding for themselves. Surgeons will still have checklists, even though they're incredible experts. And certainly, you know, a very senior engineer needs less structure than a junior engineer, but there still is some of that structure that you want to keep. And so I always try to anthropomorphize the models and try to think about for a human sort of what is the equivalent. And that's sort of, you know, how I think about these things is how much instruction would you give a human with the same task? And do you, would you need to give them a lot of instruction or a little bit of instruction?Alessio [00:18:36]: Let's talk about the agent architecture maybe. So first, runtime, you let it run until it thinks it's done or it reaches 200k context window.Swyx [00:18:45]: How did you come up? What's up with that?Erik [00:18:47]: Yeah.Swyx [00:18:48]: Yeah.Erik [00:18:49]: I mean, this, so I'd say that a lot of previous agent work built sort of these very hard coded and rigid workflows where the model is sort of pushed through certain flows of steps. And I think to some extent, you know, that's needed with smaller models and models that are less smart. But one of the things that we really wanted to explore was like, let's really give Claude the reins here and not force Claude to do anything, but let Claude decide, you know, how it should approach the problem, what steps it should do. And so really, you know, what we did is like the most extreme version of this is just give it some tools that it can call and it's able to keep calling the tools, keep thinking, and then yeah, keep doing that until it thinks it's done. And that's sort of the most, the most minimal agent framework that we came up with. And I think that works very well. I think especially the new Sonnet 3.5 is very, very good at self-correction, has a lot of like grit. Claude will try things that fail and then try, you know, come back and sort of try different approaches. And I think that's something that you didn't see in a lot of previous models. Some of the existing agent frameworks that I looked at, they had whole systems built to try to detect loops and see, oh, is the model doing the same thing, you know, more than three times, then we have to pull it out. And I think like the smarter the models are, the less you need that kind of extra scaffolding. So yeah, just giving the model tools and letting it keep sample and call tools until it thinks it's done was the most minimal framework that we could think of. And so that's what we did.Alessio [00:20:18]: So you're not pruning like bad paths from the context. If it tries to do something, it fails. You just burn all these tokens.Swyx [00:20:25]: Yes.Erik [00:20:26]: I would say the downside of this is that this is sort of a very token expensive way to doSwyx [00:20:29]: this. But still, it's very common to prune bad paths because models get stuck. Yeah.Erik [00:20:35]: But I'd say that, yeah, 3.5 is not getting stuck as much as previous models. And so, yeah, we wanted to at least just try the most minimal thing. Now, I would say that, you know, this is definitely an area of future research, especially if we talk about these problems that are going to take a human more than four hours. Those might be things where we're going to need to go prune bad paths to let the model be able to accomplish this task within 200k tokens. So certainly I think there's like future research to be done in that area, but it's not necessary to do well on these benchmarks.Swyx [00:21:06]: Another thing I always have questions about on context window things, there's a mini cottage industry of code indexers that have sprung up for large code bases, like the ones in SweetBench. You didn't need them? We didn't.Erik [00:21:18]: And I think I'd say there's like two reasons for this. One is like SweetBench specific and the other is a more general thing. The more general thing is that I think Sonnet is very good at what we call agentic search. And what this basically means is letting the model decide how to search for something. It gets the results and then it can decide, should it keep searching or is it done? Does it have everything it needs? So if you read through a lot of the traces of the SweetBench, the model is calling tools to view directories, list out things, view files. And it will do a few of those until it feels like it's found the file where the bug is. And then it will start working on that file. And I think like, again, this is all, everything we did was about just giving Claude the full reins. So there's no hard-coded system. There's no search system that you're relying on getting the correct files into context. This just totally lets Claude do it.Swyx [00:22:11]: Or embedding things into a vector database. Exactly. Oops. No, no.Erik [00:22:17]: This is very, very token expensive. And so certainly, and it also takes many, many turns. And so certainly if you want to do something in a single turn, you need to do RAG and just push stuff into the first prompt.Alessio [00:22:28]: And just to make it clear, it's using the Bash tool, basically doing LS, looking at files and then doing CAD for the following context. It can do that.Erik [00:22:35]: But it's file editing tool also has a command in it called view that can view a directory. It's very similar to LS, but it just sort of has some nice sort of quality of life improvements. So I think it'll only do an LS sort of two directories deep so that the model doesn't get overwhelmed if it does this on a huge file. I would say actually we did more engineering of the tools than the overall prompt. But the one other thing I want to say about this agentic search is that for SWE-Bench specifically, a lot of the tasks are bug reports, which means they have a stack trace in them. And that means right in that first prompt, it tells you where to go. And so I think this is a very easy case for the model to find the right files versus if you're using this as a general coding assistant where there isn't a stack trace or you're asking it to insert a new feature, I think there it's much harder to know which files to look at. And that might be an area where you would need to do more of this exhaustive search where an agentic search would take way too long.Swyx [00:23:33]: As someone who spent the last few years in the JS world, it'd be interesting to see SWE-Bench JS because these stack traces are useless because of so much virtualization that we do. So they're very, very disconnected with where the code problems are actually appearing.Erik [00:23:50]: That makes me feel better about my limited front-end experience, as I've always struggled with that problem.Swyx [00:23:55]: It's not your fault. We've gotten ourselves into a very, very complicated situation. And I'm not sure it's entirely needed. But if you talk to our friends at Vercel, they will say it is.Erik [00:24:04]: I will say SWE-Bench just released SWE-Bench Multimodal, which I believe is either entirely JavaScript or largely JavaScript. And it's entirely things that have visual components of them.Swyx [00:24:15]: Are you going to tackle that? We will see.Erik [00:24:17]: I think it's on the list and there's interest, but no guarantees yet.Swyx [00:24:20]: Just as a side note, it occurs to me that every model lab, including Enthopic, but the others as well, you should have your own SWE-Bench, whatever your bug tracker tool. This is a general methodology that you can use to track progress, I guess.Erik [00:24:34]: Yeah, sort of running on our own internal code base.Swyx [00:24:36]: Yeah, that's a fun idea.Alessio [00:24:37]: Since you spend so much time on the tool design, so you have this edit tool that can make changes and whatnot. Any learnings from that that you wish the AI IDEs would take in? Is there some special way to look at files, feed them in?Erik [00:24:50]: I would say the core of that tool is string replace. And so we did a few different experiments with different ways to specify how to edit a file. And string replace, basically, the model has to write out the existing version of the string and then a new version, and that just gets swapped in. We found that to be the most reliable way to do these edits. Other things that we tried were having the model directly write a diff, having the model fully regenerate files. That one is actually the most accurate, but it takes so many tokens, and if you're in a very big file, it's cost prohibitive. There's basically a lot of different ways to represent the same task. And they actually have pretty big differences in terms of model accuracy. I think Eider, they have a really good blog where they explore some of these different methods for editing files, and they post results about them, which I think is interesting. But I think this is a really good example of the broader idea that you need to iterate on tools rather than just a prompt. And I think a lot of people, when they make tools for an LLM, they kind of treat it like they're just writing an API for a computer, and it's sort of very minimal. It's sort of just the bare bones of what you'd need, and honestly, it's so hard for the models to use those. Again, I come back to anthropomorphizing these models. Imagine you're a developer, and you just read this for the very first time, and you're trying to use it. You can do so much better than just sort of the bare API spec of what you'd often see. Include examples in the description. Include really detailed explanations of how things work. And I think that, again, also think about what is the easiest way for the model to represent the change that it wants to make. For file editing, as an example, writing a diff is actually... Let's take the most extreme example. You want the model to literally write a patch file. I think patch files have at the very beginning numbers of how many total lines change. That means before the model has actually written the edit, it needs to decide how many numbers or how many lines are going to change.Swyx [00:26:52]: Don't quote me on that.Erik [00:26:54]: I think it's something like that, but I don't know if that's exactly the diff format. But you can certainly have formats that are much easier to express without messing up than others. And I like to think about how much human effort goes into designing human interfaces for things. It's incredible. This is entirely what FrontEnd is about, is creating better interfaces to kind of do the same things. And I think that same amount of attention and effort needs to go into creating agent computer interfaces.Swyx [00:27:19]: It's a topic we've discussed, ACI or whatever that looks like. I would also shout out that I think you released some of these toolings as part of computer use as well. And people really liked it. It's all open source if people want to check it out. I'm curious if there's an environment element that complements the tools. So how do you... Do you have a sandbox? Is it just Docker? Because that can be slow or resource intensive. Do you have anything else that you would recommend?Erik [00:27:47]: I don't think I can talk about sort of public details or about private details about how we implement our sandboxing. But obviously, we need to have sort of safe, secure, and fast sandboxes for training for the models to be able to practice writing code and working in an environment.Swyx [00:28:03]: I'm aware of a few startups working on agent sandboxing. E2B is a close friend of ours that Alessio has led around in, but also I think there's others where they're focusing on snapshotting memory so that it can do time travel for debugging. Computer use where you can control the mouse or keyboard or something like that. Whereas here, I think that the kinds of tools that we offer are very, very limited to coding agent work cases like bash, edit, you know, stuff like that. Yeah.Erik [00:28:30]: I think the computer use demo that we released is an extension of that. It has the same bash and edit tools, but it also has the computer tool that lets it get screenshots and move the mouse and keyboard. Yeah. So I definitely think there's sort of more general tools there. And again, the tools we released as part of SweetBench were, I'd say they're very specific for like editing files and doing bash, but at the same time, that's actually very general if you think about it. Like anything that you would do on a command line or like editing files, you can do with those tools. And so we do want those tools to feel like any sort of computer terminal work could be done with those same tools rather than making tools that were like very specific for SweetBench like run tests as its own tool, for instance. Yeah.Swyx [00:29:15]: You had a question about tests.Alessio [00:29:16]: Yeah, exactly. I saw there's no test writer tool. Is it because it generates the code and then you're running it against SweetBench anyway, so it doesn't really need to write the test or?Swyx [00:29:26]: Yeah.Erik [00:29:27]: So this is one of the interesting things about SweetBench is that the tests that the model's output is graded on are hidden from it. That's basically so that the model can't cheat by looking at the tests and writing the exact solution. And I'd say typically the model, the first thing it does is it usually writes a little script to reproduce the error. And again, most SweetBench tasks are like, hey, here's a bug that I found. I run this and I get this error. So the first thing the model does is try to reproduce that. So it's kind of been rerunning that script as a mini test. But yeah, sometimes the model will like accidentally introduce a bug that breaks some other tests and it doesn't know about that.Alessio [00:30:05]: And should we be redesigning any tools? We kind of talked about this and like having more examples, but I'm thinking even things of like Q as a query parameter in many APIs, it's like easier for the model to like re-query than read the Q. I'm sure it learned the Q by this point, but like, is there anything you've seen like building this where it's like, hey, if I were to redesign some CLI tools, some API tool, I would like change the way structure to make it better for LLMs?Erik [00:30:31]: I don't think I've thought enough about that off the top of my head, but certainly like just making everything more human friendly, like having like more detailed documentation and examples. I think examples are really good in things like descriptions, like so many, like just using the Linux command line, like how many times I do like dash dash help or look at the man page or something. It's like, just give me one example of like how I actually use this. Like I don't want to go read through a hundred flags. Just give me the most common example. But again, so you know, things that would be useful for a human, I think are also very useful for a model.Swyx [00:31:03]: Yeah. I mean, there's one thing that you cannot give to code agents that is useful for human is this access to the internet. I wonder how to design that in, because one of the issues that I also had with just the idea of a suite bench is that you can't do follow up questions. You can't like look around for similar implementations. These are all things that I do when I try to fix code and we don't do that. It's not, it wouldn't be fair, like it'd be too easy to cheat, but then also it's kind of not being fair to these agents because they're not operating in a real world situation. Like if I had a real world agent, of course I'm giving it access to the internet because I'm not trying to pass a benchmark. I don't have a question in there more, more just like, I feel like the most obvious tool access to the internet is not being used.Erik [00:31:47]: I think that that's really important for humans, but honestly the models have so much general knowledge from pre-training that it's, it's like less important for them. I feel like versioning, you know, if you're working on a newer thing that was like, they came after the knowledge cutoff, then yes, I think that's very important. I think actually this, this is like a broader problem that there is a divergence between Sweebench and like what customers will actually care about who are working on a coding agent for real use. And I think one of those there is like internet access and being able to like, how do you pull in outside information? I think another one is like, if you have a real coding agent, you don't want to have it start on a task and like spin its wheels for hours because you gave it a bad prompt. You want it to come back immediately and ask follow up questions and like really make sure it has a very detailed understanding of what to do, then go off for a few hours and do work. So I think that like real tasks are going to be much more interactive with the agent rather than this kind of like one shot system. And right now there's no benchmark that, that measures that. And maybe I think it'd be interesting to have some benchmark that is more interactive. I don't know if you're familiar with TauBench, but it's a, it's a customer service benchmark where there's basically one LLM that's playing the user or the customer that's getting support and another LLM that's playing the support agent and they interact and try to resolve the issue.Swyx [00:33:08]: Yeah. We talked to the LMSIS guys. Awesome. And they also did MTBench for people listening along. So maybe we need MTSWE-Bench. Sure. Yeah.Erik [00:33:16]: So maybe, you know, you could have something where like before the SWE-Bench task starts, you have like a few back and forths with kind of like the, the author who can answer follow up questions about what they want the task to do. And of course you'd need to do that where it doesn't cheat and like just get the exact, the exact thing out of the human or out of the sort of user. But I think that would be a really interesting thing to see. If you look at sort of existing agent work, like a Repl.it's coding agent, I think one of the really great UX things they do is like first having the agent create a plan and then having the human approve that plan or give feedback. I think for agents in general, like having a planning step at the beginning, one, just having that plan will improve performance on the downstream task just because it's kind of like a bigger chain of thought, but also it's just such a better UX. It's way easier for a human to iterate on a plan with a model rather than iterating on the full task that sort of has a much slower time through each loop. If the human has approved this implementation plan, I think it makes the end result a lot more sort of auditable and trustable. So I think there's a lot of things sort of outside of SweetBench that will be very important for real agent usage in the world. Yeah.Swyx [00:34:27]: I will say also, there's a couple of comments on names that you dropped. Copilot also does the plan stage before it writes code. I feel like those approaches have generally been less Twitter successful because it's not prompt to code, it's prompt plan code. You know, so there's a little bit of friction in there, but it's not much. Like it's, it actually, it's, it, you get a lot for what it's worth. I also like the way that Devin does it, where you can sort of edit the plan as it goes along. And then the other thing with Repl.it, we had a, we hosted a sort of dev day pregame with Repl.it and they also commented about multi-agents. So like having two agents kind of bounce off of each other. I think it's a similar approach to what you're talking about with kind of the few shot example, just as in the prompts of clarifying what the agent wants. But typically I think this would be implemented as a tool calling another agent, like a sub-agent I don't know if you explored that, do you like that idea?Erik [00:35:20]: I haven't explored this enough, but I've definitely heard of people having good success with this. Of almost like basically having a few different sort of personas of agents, even if they're all the same LLM. I think this is one thing with multi-agent that a lot of people will kind of get confused by is they think it has to be different models behind each thing. But really it's sort of usually the same, the same model with different prompts. And yet having one, having them have different personas to kind of bring different sort of thoughts and priorities to the table. I've seen that work very well and sort of create a much more thorough and thought outSwyx [00:35:53]: response.Erik [00:35:53]: I think the downside is just that it adds a lot of complexity and it adds a lot of extra tokens. So I think it depends what you care about. If you want a plan that's very thorough and detailed, I think it's great. If you want a really quick, just like write this function, you know, you probably don't want to do that and have like a bunch of different calls before it does this.Alessio [00:36:11]: And just talking about the prompt, why are XML tags so good in Cloud? I think initially people were like, oh, maybe you're just getting lucky with XML. But I saw obviously you use them in your own agent prompts, so they must work. And why is it so model specific to your family?Erik [00:36:26]: Yeah, I think that there's, again, I'm not sure how much I can say, but I think there's historical reasons that internally we've preferred XML. I think also the one broader thing I'll say is that if you look at certain kinds of outputs, there is overhead to outputting in JSON. If you're trying to output code in JSON, there's a lot of extra escaping that needs to be done, and that actually hurts model performance across the board. Versus if you're in just a single XML tag, there's none of that sort of escaping thatSwyx [00:36:58]: needs to happen.Erik [00:36:58]: That being said, I haven't tried having it write HTML and XML, which maybe then you start running into weird escaping things there. I'm not sure. But yeah, I'd say that's some historical reasons, and there's less overhead of escaping.Swyx [00:37:12]: I use XML in other models as well, and it's just a really nice way to make sure that the thing that ends is tied to the thing that starts. That's the only way to do code fences where you're pretty sure example one start, example one end, that is one cohesive unit.Alessio [00:37:30]: Because the braces are nondescriptive. Yeah, exactly.Swyx [00:37:33]: That would be my simple reason. XML is good for everyone, not just Cloud. Cloud was just the first one to popularize it, I think.Erik [00:37:39]: I do definitely prefer to read XML than read JSON.Alessio [00:37:43]: Any other details that are maybe underappreciated? I know, for example, you had the absolute paths versus relative. Any other fun nuggets?Erik [00:37:52]: I think that's a good sort of anecdote to mention about iterating on tools. Like I said, spend time prompt engineering your tools, and don't just write the prompt, but write the tool, and then actually give it to the model and read a bunch of transcripts about how the model tries to use the tool. I think by doing that, you will find areas where the model misunderstands a tool or makes mistakes, and then basically change the tool to make it foolproof. There's this Japanese term, pokayoke, about making tools mistake-proof. You know, the classic idea is you can have a plug that can fit either way, and that's dangerous, or you can make it asymmetric so that it can't fit this way, it has to go like this, and that's a better tool because you can't use it the wrong way. So for this example of absolute paths, one of the things that we saw while testing these tools is, oh, if the model has done CD and moved to a different directory, it would often get confused when trying to use the tool because it's now in a different directory, and so the paths aren't lining up. So we said, oh, well, let's just force the tool to always require an absolute path, and then that's easy for the model to understand. It knows sort of where it is. It knows where the files are. And then once we have it always giving absolute paths, it never messes up even, like, no matter where it is because it just, if you're using an absolute path, it doesn't matter whereSwyx [00:39:13]: you are.Erik [00:39:13]: So iterations like that, you know, let us make the tool foolproof for the model. I'd say there's other categories of things where we see, oh, if the model, you know, opens vim, like, you know, it's never going to return. And so the tool is stuck.Swyx [00:39:28]: Did it get stuck? Yeah. Get out of vim. What?Erik [00:39:31]: Well, because the tool is, like, it just text in, text out. It's not interactive. So it's not like the model doesn't know how to get out of vim. It's that the way that the tool is, like, hooked up to the computer is not interactive. Yes, I mean, there is the meme of no one knows how to get out of vim. You know, basically, we just added instructions in the tool of, like, hey, don't launch commands that don't return.Swyx [00:39:54]: Yeah, like, don't launch vim.Erik [00:39:55]: Don't launch whatever. If you do need to do something, you know, put an ampersand after it to launch it in the background. And so, like, just, you know, putting kind of instructions like that just right in the description for the tool really helps the model. And I think, like, that's an underutilized space of prompt engineering, where, like, people might try to do that in the overall prompt, but just put that in the tool itself so the model knows that it's, like, for this tool, this is what's relevant.Swyx [00:40:20]: You said you worked on the function calling and tool use before you actually started this vBench work, right? Was there any surprises? Because you basically went from creator of that API to user of that API. Any surprises or changes you would make now that you have extensively dog-fooded in a state-of-the-art agent?Erik [00:40:39]: I want us to make, like, maybe, like, a little bit less verbose SDK. I think some way, like, right now, it just takes, I think we sort of force people to do the best practices of writing out sort of these full JSON schemas, but it would be really nice if you could just pass in a Python function as a tool. I think that could be something nice.Swyx [00:40:58]: I think that there's a lot of, like, Python- There's helper libraries. ... structure, you know. I don't know if there's anyone else that is specializing for Anthropic. Maybe Jeremy Howard's and Simon Willis's stuff. They all have Cloud-specific stuff that they are working on. Cloudette. Cloudette, exactly. I also wanted to spend a little bit of time with SuiteAgent. It seems like a very general framework. Like, is there a reason you picked it apart from it's the same authors as vBench, or?Erik [00:41:21]: The main thing we wanted to go with was the same authors as vBench, so it just felt sort of like the safest, most neutral option. And it was, you know, very high quality. It was very easy to modify, to work with. I would say it also actually, their underlying framework is sort of this, it's like, youSwyx [00:41:39]: know, think, act, observe.Erik [00:41:40]: That they kind of go through this loop, which is like a little bit more hard-coded than what we wanted to do, but it's still very close. That's still very general. So it felt like a good match as sort of the starting point for our agent. And we had already sort of worked with and talked with the SWE-Bench people directly, so it felt nice to just have, you know, we already know the authors. This will be easy to work with.Swyx [00:42:00]: I'll share a little bit of like, this all seems disconnected, but once you figure out the people and where they go to school, it all makes sense. So it's all Princeton. Yeah, the SWE-Bench and SuiteAgent.Erik [00:42:11]: It's a group out of Princeton.Swyx [00:42:12]: Yeah, and we had Shun Yu on the pod, and he came up with the React paradigm, and that's think, act, observe. That's all React. So they're all friends. Yep, yeah, exactly.Erik [00:42:22]: And you know, if you actually read our traces of our submission, you can actually see like think, act, observe in our logs. And we just didn't even change the printing code. So it's like doing still function calls under the hood, and the model can do sort of multiple function calls in a row without thinking in between if it wants to. But yeah, so a lot of similarities and a lot of things we inherited from SuiteAgent just as a starting point for the framework.Alessio [00:42:47]: Any thoughts about other agent frameworks? I think there's, you know, the whole gamut from very simple to like very complex.Swyx [00:42:53]: Autogen, CooEI, LandGraph. Yeah, yeah.Erik [00:42:56]: I think I haven't explored a lot of them in detail. I would say with agent frameworks in general, they can certainly save you some like boilerplate. But I think there's actually this like downside of making agents too easy, where you end up very quickly like building a much more complex system than you need. And suddenly, you know, instead of having one prompt, you have five agents that are talking to each other and doing a dialogue. And it's like, because the framework made that 10 lines to do, you end up building something that's way too complex. So I think I would actually caution people to like try to start without these frameworks if you can, because you'll be closer to the raw prompts and be able to sort of directly understand what's going on. I think a lot of times these frameworks also, by trying to make everything feel really magical, you end up sort of really hiding what the actual prompt and output of the model is, and that can make it much harder to debug. So certainly these things have a place, and I think they do really help at getting rid of boilerplate, but they come with this cost of obfuscating what's really happening and making it too easy to very quickly add a lot of complexity. So yeah, I would recommend people to like try it from scratch, and it's like not that bad.Alessio [00:44:08]: Would you rather have like a framework of tools? Do you almost see like, hey, it's maybe easier to get tools that are already well curated, like the ones that you build, if I had an easy way to get the best tool from you, andSwyx [00:44:21]: like you maintain the definition?Alessio [00:44:22]: Or yeah, any thoughts on how you want to formalize tool sharing?Erik [00:44:26]: Yeah, I think that's something that we're certainly interested in exploring, and I think there is space for sort of these general tools that will be very broadly applicable. But at the same time, most people that are building on these, they do have much more specific things that they're trying to do. You know, I think that might be useful for hobbyists and demos, but the ultimate end applications are going to be bespoke. And so we just want to make sure that the model's great at any tool that it uses. But certainly something we're exploring.Alessio [00:44:52]: So everything bespoke, no frameworks, no anything.Swyx [00:44:55]: Just for now, for now.Erik [00:44:56]: Yeah, I would say that like the best thing I've seen is people building up from like, build some good util functions, and then you can use those as building blocks. Yeah, yeah.Alessio [00:45:05]: I have a utils folder, or like all these scripts. My framework is like def, call, and tropic. And then I just put all the defaults.Swyx [00:45:12]: Yeah, exactly. There's a startup hidden in every utils folder, you know? No, totally not. Like, if you use it enough, like it's a startup, you know? At some point. I'm kind of curious, is there a maximum length of turns that it took? Like, what was the longest run? I actually don't.Erik [00:45:27]: I mean, it had basically infinite turns until it ran into a 200k context. I should have looked this up. I don't know. And so for some of those failed cases where it eventually ran out of context, I mean, it was over 100 turns. I'm trying to remember like the longest successful run, but I think it was definitely over 100 turns that some of the times.Swyx [00:45:48]: Which is not that much. It's a coffee break. Yeah.Erik [00:45:52]: But certainly, you know, these things can be a lot of turns. And I think that's because some of these things are really hard, where it's going to take, you know, many tries to do it. And if you think about like, think about a task that takes a human four hours to do. Think about how many different files you read, and like times you edit a file in four hours. That's a lot more than 100.Alessio [00:46:10]: How many times you open Twitter because you get distracted. But if you had a lot more compute, what's kind of like the return on the extra compute now? So like, you know, if you had thousands of turns or like whatever, like how much better would it get?Erik [00:46:23]: Yeah, this I don't know. And I think this is, I think sort of one of the open areas of research in general with agents is memory and sort of how do you have something that can do work beyond its context length where you're just purely appending. So you mentioned earlier things like pruning bad paths. I think there's a lot of interesting work around there. Can you just roll back but summarize, hey, don't go down this path? There be dragons. Yeah, I think that's very interesting that you could have something that that uses way more tokens without ever using at a time more than 200k. So I think that's very interesting. I think the biggest thing is like, can you make the model sort of losslessly summarize what it's learned from trying different approaches and bring things back? I think that's sort of the big challenge.Swyx [00:47:11]: What about different models?Alessio [00:47:12]: So you have Haiku, which is like, you know, cheaper. So you're like, well, what if I have a Haiku to do a lot of these smaller things and then put it back up?Erik [00:47:20]: I think Cursor might have said that they actually have a separate model for file editing.Swyx [00:47:25]: I'm trying to remember.Erik [00:47:25]: I think they were on maybe the Lex Fridman podcast where they said they have a bigger model, like write what the code should be and then a different model, like apply it. So I think there's a lot of interesting room for stuff like that. Yeah, fast supply.Swyx [00:47:37]: We actually did a pod with Fireworks that they worked with on. It's speculative decoding.Erik [00:47:41]: But I think there's also really interesting things about like, you know, paring down input tokens as well, especially sometimes the models trying to read like a 10,000 line file. That's a lot of tokens. And most of it is actually not going to be relevant. I think it'd be really interesting to like delegate that to Haiku. Haiku read this file and just pull out the most relevant functions. And then, you know, Sonnet reads just those and you save 90% on tokens. I think there's a lot of really interesting room for things like that. And again, we were just trying to do sort of the simplest, most minimal thing and show that it works. I'm really hoping that people, sort of the agent community builds things like that on top of our models. That's, again, why we released these tools. We're not going to go and do lots more submissions to SWE-Bench and try to prompt engineer this and build a bigger system. We want people to like the ecosystem to do that on top of our models. But yeah, so I think that's a really interesting one.Swyx [00:48:32]: It turns out, I think you did do 3.5 Haiku with your tools and it scored a 40.6. Yes.Erik [00:48:38]: So it did very well. It itself is actually very smart, which is great. But we haven't done any experiments with this combination of the two models. But yeah, I think that's one of the exciting things is that how well Haiku 3.5 did on SWE-Bench shows that sort of even our smallest, fastest model is very good at sort of thinking agentically and working on hard problems. Like it's not just sort of for writing simple text anymore.Alessio [00:49:02]: And I know you're not going to talk about it, but like Sonnet is not even supposed to be the best model, you know? Like Opus, it's kind of like we left it at three back in the corner intro. At some point, I'm sure the new Opus will come out. And if you had Opus Plus on it, that sounds very, very good.Swyx [00:49:19]: There's a run with SuiteAgent plus Opus, but that's the official SWE-Bench guys doing it.Erik [00:49:24]: That was the older, you know, 3.0.Swyx [00:49:25]: You didn't do yours. Yeah. Okay. Did you want to? I mean, you could just change the model name.Erik [00:49:31]: I think we didn't submit it, but I think we included it in our model card.Swyx [00:49:35]: Okay.Erik [00:49:35]: We included the score as a comparison. Yeah.Swyx [00:49:38]: Yeah.Erik [00:49:38]: And Sonnet and Haiku, actually, I think the new ones, they both outperformed the original Opus. Yeah. I did see that.Swyx [00:49:44]: Yeah. It's a little bit hard to find. Yeah.Erik [00:49:47]: It's not an exciting score, so we didn't feel like they need to submit it to the benchmark.Swyx [00:49:52]: We can cut over to computer use if we're okay with moving on to topics on this, if anything else. I think we're good.Erik [00:49:58]: I'm trying to think if there's anything else SWE-Bench related.Swyx [00:50:02]: It doesn't have to be also just specifically SWE-Bench, but just your thoughts on building agents, because you are one of the few people that have reached this leaderboard on building a coding agent. This is the state of the art. It's surprisingly not that hard to reach with some good principles. Right. There's obviously a ton of low-hanging fruit that we covered. Your thoughts on if you were to build a coding agent startup, what next?Erik [00:50:24]: I think the really interesting question for me, for all the startups out there, is this kind of divergence between the benchmarks and what real customers will want. So I'm curious, maybe the next time you have a coding agent startup on the podcast, you should ask them that. What are the differences that they're starting to make? Tomorrow.Swyx [00:50:40]: Oh, perfect, perfect. Yeah.Erik [00:50:41]: I'm actually very curious what they will see, because I also have seen, I feel like it's slowed down a little bit if I don't see the startups submitting to SWE-Bench that much anymore.Swyx [00:50:52]: Because of the traces, the trace. So we had Cosign on, they had a 50-something on full, on SWE-Bench full, which is the hardest one, and they were rejected because they didn't want to submit their traces. Yep. IP, you know? Yeah, that makes sense, that makes sense. Actually, tomorrow we're talking to Bolt, which is a cloud customer. You guys actually published a case study with them. I assume you weren't involved with that, but they were very happy with Cloud. Cool. One of the biggest launches of the year. Yeah, totally. We actually happened to b
Over the past two years, multifamily has faced major challenges that's resulted in price reductions of 25-35%. Class C in particular has taken a major hit in several markets, but Inflation has recently been tamed and expenses have been mostly stabilized. Solid operators are improving their daily operations and increasing occupancy and collections. Class C also still presents the best pricing value, and upside opportunity. Craig Berger, Founder and CEO of Avid Realty Partners, is successfully optimizing leasing efforts, maintenance, and other aspects of his operations. He's also patiently searching for opportunistic acquisitions in all classes.
Send us a textNew Class C RVs are getting more expensive every year. And maybe you simply can't afford to buy a new one.If so, there are lots of older used Class C motorhomes that could be a very good choice instead. And this podcast explains my recommended list of the better RV brands from the years 2010 - 2019.Here is the link to my video on improving the ride and handling on used Class C RVs - https://youtu.be/Dfue7PRy9rQHere is the link to my video on fluid analysis for RVs - https://youtu.be/abNq3Z8HUJo
Episode 357 Show Notes Topic of the show: Not Getting Flight Following and Why It's Bad. On this week's show, AG and RH discuss how a flight following request would have prevented a near midair collision at a busy Class C airport. Why is remaining outside the Charlie legal but not necessarily safe? Can pilots get better service by simply calling ATC? This incident got a lot of attention and we want to reiterate the controller did a great job! We had a lot of fun recording this episode and you don't want to miss it! Links: https://youtu.be/4vOySpGgEdY https://ops.group/blog/400-increase-in-gps-spoofing-workgroup-established/ Timely Feedback: 1. Patron ES talks about a suggestion for putting on foggles if disoriented in IMC, very interesting! 2. Patron MK comments on the controller that assisted a pilot in trouble in IMC and talks about CYA culture. 3. SGAC TR says thanks and mentions DPE RH's role in getting into OB Feedback 1. SGAC AK has an ODP and diverse vector area question 2. Patron GH discusses GPS spoofing Have a great week and thanks for listening! Visit our website at OpposingBases.com You can support our show using Patreon or visiting our support page on the website. Keep the feedback coming, it drives the show! Don't be shy, use the “Send Audio to AG and RH” button on the website and record an audio message. Or you can send us comments or questions to feedback@opposingbases.com. Music bumpers by audionautix.com. Third party audio provided by liveatc.net. Legal Notice The views and opinions expressed on Opposing Bases Air Traffic Talk are for entertainment purposes only and do not represent the views, opinions, or official positions of the FAA, Penguin Airlines, or the United States Army. Episodes shall not be recorded or transcribed without express written consent. For official guidance on laws, rules, and regulations, consult an aviation attorney or certified flight instructor.
Getting the right price and the right terms is the ultimate hedge against the inevitable unknowns and challenges of operating multifamily properties. Class C properties, in particular, can present great buying opportunities, but they have a lot of day-to-day operational challenges, from collecting rents to perpetual maintenance issues. Steven Weinstock, co-founder of WE Capital in Brooklyn, operates C and B class properties in Cleveland and Louisville. Steve is acquiring these properties from forty to eighty thousand dollars/per door from long-term owners.
Are we on the brink of a multifamily rental boom? Discover the surprising data points that could reshape your investment strategy in the coming years!In this week's episode, I dive into three critical data points that reveal the current state of the multifamily real estate market. I go into the year-over-year rent growth trends, the unprecedented supply of new apartments hitting the market, and the underlying demand for housing that continues to surge despite flatlining rents. Here's a sneak peek of what you'll discover: - What are the key trends in year-over-year rent growth across different U.S. markets, and how do they impact multifamily investing? - Why is there a significant gap between current rent growth and wage growth, and what does this mean for the future of rental affordability? - What factors are driving the considerable demand for housing despite flat or falling rents in many areas? - How does the concept of net absorption illustrate the current state of the multifamily housing market, and what does it predict for the future? - Why might Class C apartments be uniquely positioned to benefit from these market dynamics compared to Class A and B properties?Additionally, I'm thrilled to announce our newest investment opportunity: a 72-unit property in Barrington, New Hampshire. This is a direct-to-seller deal with a compelling business plan and minimal execution risk. If you want to learn more, click here to access the deal room.Are you a new multifamily investor looking to grow your portfolio but don't know where to start? Are you an existing multifamily investor looking to scale your business and master advanced topics such as capital structure, finding off-market deals, and establishing JV partnerships? Click here to learn more about 7-Day Multifamily, a program in which I teach investors the foundational skills they need to start and scale a multifamily portfolio rapidly.Are you looking to invest in real estate, but don't want to deal with the hassle of finding great deals, signing on debt, and managing tenants? Aligned Real Estate Partners provides investment opportunities to passive investors looking for the returns, stability, and tax benefits multifamily real estate offers, but without the work - join our investor club to be notified of future investment opportunities.Connect with Axel:Follow him on InstagramConnect with him on LinkedInSubscribe to our YouTube channelLearn more about Aligned Real Estate Partners
In this episode, Caitlin Costello, MD, discusses important topics related to relapsed/refractory (R/R) multiple myeloma (MM), including:3 bispecific antibodies approved for the treatment of R/R MM that target BCMA or GPRC5DThe role of bispecific antibodies in R/R MMSafety considerations for patients while receiving a bispecific antibodyEmerging data and clinical trials with bispecific antibodiesKey clinical pearls for optimal use of bispecific antibodiesPresenter:Caitlin Costello, MDClinical Professor of MedicineDirector, Multiple Myeloma ProgramDivision of Blood and Marrow TransplantationMoores Cancer CenterUC San DiegoLa Jolla, CaliforniaLink to full program: https://bit.ly/40bjFCZ
Hey, it's Alex Coffman, and in this episode of The Real enTREpreneur™ Podcast, I'm diving deep into how we're navigating today's shifting real estate market and finding opportunities in all the right places. We're actively hunting for new deals, including a potential 228-unit property in Irving, Texas, with massive value-add opportunities. I'll break down the creative financing strategy we're using to minimize upfront capital and keep our existing investors in the game—something you don't want to miss if you're looking to scale your own portfolio. Here's what you can expect: 228 Units in Irving: Why this Class C property, fully occupied and ready for rent bumps, is a prime investment. Interest Rate Insights: How recent rate changes are impacting the market and what it means for your next deal. Creative Financing: A behind-the-scenes look at how we're refinancing with the seller to make this deal happen. New Deals on the Horizon: We're also eyeing a 220-unit property in Saginaw, plus opportunities in Houston and the DFW area. Political and Market Outlook: A quick chat about how the upcoming election might shake things up, and why I'm keeping an eye on the competition if rates drop. If you're ready to learn how to stay ahead in a changing market, this episode is packed with strategies you can apply right now.
In this episode, Patrick McKenzie (patio11) is joined by Moses Kagan, co-founder of Adaptive Realty, ReSeed, and Reconvene. Their deep dive into real estate investing and property management covers the different classes of apartment buildings, the challenges of property management, and the complexities of financing structures in the industry. They examine how the internet has transformed capital raising, the significance of cap rates, the effects of supply and demand on property values, and a comparison of the real estate markets in different major cities. The episode is in many ways a follow up to Patrick's conversation with Jim McKenzie and offers a window into the opaque world of real estate investment.–Full transcript available here: https://www.complexsystemspodcast.com/episodes/real-estate-moses-kagan/–Sponsor: CheckCheck is the leading payroll infrastructure provider and pioneer of embedded payroll. Check makes it easy for any SaaS platform to build a payroll business, and already powers 60+ popular platforms. Head to checkhq.com/complex and tell them patio11 sent you.–Links:Moses Kagan's blog: https://kagansblog.com/Reconvene Conference: https://www.reconvene.com/Seth Godin's book Permission Marketing: https://www.amazon.com/Permission-Marketing-Strangers-Friends-Customers/dp/0684856360Bits About Money: https://www.bitsaboutmoney.com/Jim McKenzie on Complex Systems: https://open.spotify.com/episode/6ocJirzGTStuf0K9ITM21X–Timestamps:(00:00) Intro(00:25) Understanding the stigma of the maligned landlord(04:07) Landlord spectrum: from mom-and-pops to institutional players(05:29) Inside Adaptive Realty(06:13) Owner vs. property manager(07:34) Challenges and complexities of property management(15:00) Capital stacks and loans(18:17) Sponsor: Check(26:25) The role of banks and underwriting in real estate(40:28) Federal subsidies and small scale landlords(44:26) Understanding commercial real estate classes(46:20) Challenges of Class C assets(47:13) Explaining cap rates(52:20) Raising equity for real estate deals(54:16) The syndication process(56:30) The role of brokers and execution risk(01:00:52) Legal structures and documentation(01:10:52) The power of networking and reputation(01:23:14) The impact of supply and demand on rents(01:28:03) Wrap
"Send me a text message and let me know what you think of the Cover IV Podcast."Today I will analyze a Class C, Division V game between the Lansing Bobcats and Schuyler Storm. Thank you to one of our Cover IV Podcast Football Analysts, Ryan Gineo of ESPN Ithaca, for sharing his analysis.During the Ask “Coach” Smith segment, I will explain the overtime procedure used by Section IV.This podcast was established to maximize your Section IV Football experience, regardless of your role, past or present. The goal, with your help, was to maintain a family-friendly, informative, entertaining weekly podcast with an occasional dose of appropriate humor.This podcast takes you beyond the microphone, with in-depth analysis and insight, bringing all resources together for your benefit. This podcast complements those who cover, report, support and enjoy Section IV Football. Thank you Everyone Section IV Football.The Cover IV Podcast is made possible by TDS Performance Improvement.Leading people is the most important responsibility in the world, yet 60% of first-time leaders fail. TDS Performance Improvement prevents these failures. Are you prepared to lead people? Click this link to determine if you have what it takes to lead people.Support the show"Coach" T.D. SmithCover IV Podcast Host(607) 221-6191www.CoverIV.comCoverIVPodcast@stny.rr.comListen to Podcast EpisodesSubscribe so you don't miss the latest Section IV Football News“May your football games and life, go into overtime.”
Send us a textDiscover how Randy Langenderfer made the bold leap from the corporate world to thriving in the realm of real estate investment, focusing on multifamily properties in the Sunbelt region of the U.S. Randy, from InvestArk, shares his unique strategies for achieving impressive cash-on-cash returns and internal rates of return. Through compelling stories of transforming a mismanaged Class A property in Houston and a Class C property in Tucson, listeners will gain insights into the importance of effective management and recognizing market potential.As we examine the intricate landscape of real estate investing, we confront the thorny issues of escalating insurance costs and property taxes that plague investors, especially in areas like Houston. Learn about techniques for navigating these challenges, from implementing master policies to contesting taxes annually. Plus, Randy introduces Multifamily Maestros, an educational series that arms investors with essential knowledge and strategies honed over a decade in the business.Beyond the spreadsheets, Randy shares a heartwarming perspective on success, emphasizing faith, family, and a purposeful life. He reflects on personal growth and the profound impact of community service, such as volunteering with Meals on Wheels. For those eager to learn more, Randy offers opportunities for mentorship and deeper discussions on his journey and insights, encouraging listeners to reach out through social media or his platforms, InvestArk and Multifamily Maestros.New outro for Season 4 (2024) Additional Resources: Website: https://www.clarkst.com Phone: (860) 675-5800 YouTube: https://www.youtube.com/@clarkstcapital Podcast: https://bit.ly/3LzZdDx LinkedIn: https://www.linkedin.com/company/clark-st-capital Twitter: https://twitter.com/clarkstcapital1 Facebook: https://www.facebook.com/ClarkStCapital Instagram: https://www.instagram.com/clarkstcapital
A lot of gas powered motorhome owners are not happy with the ride and handling they experience while traveling in their RV.So Liquid Spring is a unique product that claims that it resolves all of those issues in Class A and Class C gas powered motorhomes. But does it really work as well as they claim? This podcast answers that question.Here is the link to the video I made about motorhome suspensions last year - https://youtu.be/Dfue7PRy9rQ
Financial Freedom for Physicians with Dr. Christopher H. Loo, MD-PhD
In this episode, we chat with Brian Grimes, CFP and founder of 24/7 Cash Flow University. Brian shares his journey from financial planning to real estate, focusing on affordable housing solutions, co-living strategies, and investing in Class C neighborhoods. He offers insights into the current real estate market, interest rate trends, and practical advice for investors looking to thrive in 2023 and beyond. Learn how to create cash flow, manage rental properties, and tackle the challenges of real estate investing while contributing to community development. Disclaimer: Not advice. Educational purposes only. Not an endorsement for or against. Results not vetted. Views of the guests do not represent those of the host or show. Do your due diligence. Click here to join PodMatch (the "AirBNB" of Podcasting): https://www.joinpodmatch.com/drchrisloomdphd We couldn't do it without the support of our listeners. To help support the show: CashApp- https://cash.app/$drchrisloomdphd Venmo- https://account.venmo.com/u/Chris-Loo-4 Spotify- https://podcasters.spotify.com/pod/show/christopher-loo/support Buy Me a Coffee- https://www.buymeacoffee.com/chrisJx Click here to schedule a 1-on-1 private coaching call: https://www.drchrisloomdphd.com/book-online Click here to purchase my books on Amazon: https://amzn.to/2PaQn4p Follow our YouTube channel: https://www.youtube.com/chL1357 Follow us on Twitter: https://www.twitter.com/drchrisloomdphd Follow us on Instagram: https://www.instagram.com/thereal_drchrisloo Follow us on Threads: https://www.threads.net/@thereal_drchrisloo Follow us on TikTok: https://www.tiktok.com/@drchrisloomddphd Follow our Blog: https://www.drchrisloomdphd.com/blog Follow the podcast on Spotify: https://open.spotify.com/show/3NkM6US7cjsiAYTBjWGdx6?si=1da9d0a17be14d18 Subscribe to our Substack newsletter: https://substack.com/@drchrisloomdphd1 Subscribe to our Medium newsletter: https://medium.com/@drchrisloomdphd Subscribe to our email newsletter: https://financial-freedom-for-physicians.ck.page/b4622e816d Subscribe to our LinkedIn newsletter: https://www.linkedin.com/build-relation/newsletter-follow?entityUrn=6992935013231071233 Thank you to our advertisers on Spotify. Financial Freedom for Physicians, Copyright 2024 --- Support this podcast: https://podcasters.spotify.com/pod/show/christopher-loo/support
Show Date: 9/3/24 Andy and Dan give insight on the Class C Minnesota State Amateur Baseball tournament title game yesterday. Excellent event and even better weather. They also chat about WNBA, NASCAR, PWHL, NHL, Vikings' Season Opener on Sunday and MLB. Also, the NDSU Bison vs Colorado Buffaloes college football game were discussed. Sports and Songs Podcast Links: https://www.facebook.com/sportsandsongs1 https://twitter.com/SportsandSongs1 https://www.instagram.com/sportsandsongs/ https://www.sportsandsongspodcast.com/
Show Date: 8/29/24 Dan and Andy preview the upcoming Labor Day Weekend Minnesota State Amateur Baseball Tournament. We are down to the final 16 teams in the Class C. We discuss the matchups for the weekend. Thanks to the MN Baseball Association for use of their graphics for this show. Sports and Songs Podcast Links: https://www.facebook.com/sportsandsongs1 https://twitter.com/SportsandSongs1 https://www.instagram.com/sportsandsongs/ https://www.sportsandsongspodcast.com/
Show Date: 8/12/24 Andy and Dan preview the upcoming Class C State Baseball Tournament. Host sites are: Belle Plaine, Jordan and Green Isle. 48 teams, single elimination format, and 16 teams get first-round byes. This is the 101st Annual Tournament for "Town Ball" in the State of Minnesota. Sports and Songs Podcast Links: https://www.facebook.com/sportsandsongs1 https://twitter.com/SportsandSongs1 https://www.instagram.com/sportsandsongs/ https://www.sportsandsongspodcast.com/
Since mid-2022, multifamily prices have plummeted over 30% and transaction volume is down 80%. Class C, in particular, has taken a beating. In the Class A space, sales volume is starting to pick up as owners are being forced to sell by lenders or institutional partners in advance of impending loan maturities. In most markets, rents have stopped their decline and beginning to stabilize. In addition, rates may be plateauing and ready to decline. As these factors come into play, and as new inventory gets absorbed, we may be near the bottom and on our way back up to a full recovery. Brian Burke, President and CEO of Praxis Capital, has been through several cycles, and believes multifamily will rebound in 2025 and 2026.
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Here's how AI is directly driving up real estate values. My YouTube show/podcast guest this week is Derek Daniels, Regional Research Director for Colliers in the Bay Area. Derek is a San Francisco office market expert and see first-hand the significant impact of AI on San Francisco's commercial real estate market. This is a great episode if you are anywhere near an AI hub of activity (San Francisco and environs, of course, Seattle, Boston, NYC, and Austin). You'll learn about the evolving dynamics of the commercial real estate market driven by AI and get insights into opportunities for adaptation, growth, and investment. Get this. In San Francisco along, AI companies have leased (at time of recoding) 1.5 million square feet of office space, representing 25% of new leases amidst a backdrop of 35 million square feet of vacant space. Might not seem like a huge proportion – but for the owners of those office building…! Listen in to learn about the variety of spaces AI companies are leasing, from Class C to high-end Class A offices, light industrial spaces, and why flexibility and hybrid work models are crucial for these companies. And, as always, Derek was the proud recipient of my weekly three questions I ask of all guests. Here are his answers: Why should real estate professionals pay attention to AI today? AI tools can significantly enhance efficiency by automating routine tasks, allowing professionals to focus on high-impact activities. AI will create efficiencies and drive changes, some positive and some challenging, influencing the broader economy. Practical AI use for real estate professionals: Use AI to consolidate notes, generate report outlines, and craft social media posts. AI can also assist in writing emails by organizing thoughts and adjusting formality levels. Here are some easy win uses of AI that listeners can immediately try. Use AI tools to help write emails. Generate messaging for clients or prospects with paraphrasing models or text generators. Input your thoughts and let AI rearrange them for clarity and effectiveness. Adjust formality levels with AI to match the context [love this one. AG] ***** The only Podcast you need on real estate and AI. Learn how other real estate pros are using AI to get ahead of their competition. Get early notice of hot new game-changing AI real estate apps. Walk away with something you can actually use in every episode. PLUS, subscribe to my free newsletter and get: • practical guides, • how-to's, and • news updates All exclusively for real estate investors that make learning AI fun and easy and insanely productive, for free. EasyWin.AI
In this episode, we dive into the highly discussed prediction of a "Housing Bloodbath 2025" with insights from Melody Wright. We examine the potential causes and effects of a severe market downturn, comparing it to past real estate crashes and analyzing current economic indicators. With a focus on how landlords and investors can protect themselves and capitalize on opportunities, this episode provides a comprehensive look at what may lie ahead. Whether you're a seasoned investor or new to real estate, this discussion is crucial for understanding the potential shifts in the market. [00:00:00] Introduction to the concept of a Housing Bloodbath in 2025 and the background of the viral video. [00:01:03] Discussion on the repeated predictions of a housing crash since 2012 and the importance of understanding historical context. [00:02:33] Insights from Melody Wright on the potential for a significant market downturn and her background in the industry. [00:04:11] The impact of rising interest rates on home prices and transactions, and the comparison to historical data. [00:05:36] Analysis of the potential risks in the current lending environment, particularly with Debt Service Coverage Ratio (DSCR) loans. [00:08:00] Discussion on the importance of understanding market fundamentals and avoiding speculation. [00:10:00] The role of foreclosure timelines and forbearance in mitigating a rapid market decline. [00:11:08] Examination of FHA delinquency rates and their historical context. [00:12:28] Predictions on the most affected sectors of the market, particularly Class B and Class C multifamily properties. [00:13:57] Strategies for investors to prepare for and navigate potential market disruptions, including focusing on operations and maintaining liquidity. One Rental at a Time 54-Year Spreadsheet Mortgage Bankers Association Thank you for tuning into this important episode on the potential Housing Bloodbath of 2025. If you found this discussion insightful, please rate, follow, share, and leave a review. Your feedback helps us bring you more valuable content. For more detailed discussions and to connect with industry experts, join the One Rental at a Time school community. Stay informed, stay prepared, and see you next time!
Jon Weiskopf, CEO of Blue Eyed Capital, shares his journey from a high-flying corporate job to real estate investing, focusing on affordable housing in the Midwest. He discusses his first deal, challenges with tenants, and the importance of redefining affordable housing.
Join us as we sit down with Brian Burke, author of "The Hands-Off Investor," to uncover the secrets behind his acquisition of over 4000 multifamily apartments and raising over $300M. From hands-off investing to strategic acquisitions and capital raising, Brian shares invaluable insights to elevate your real estate investment game. Tune in and unlock the keys to success in multifamily investments! Key Takeaways to Listen ForStart Small, Build Big: Burke advises starting small in real estate investment to lay a solid foundation for future growth.Preparation is Key: Utilize downtime in the market to build systems, networks, and software tools for smoother operations later.Trust and Performance: Trust in the investment type and consistent performance are crucial for attracting passive investors.Avoid Class C Properties: Burke warns against Class C properties due to their higher risk and lower returns compared to Class A and B.Personal Referrals Over Marketing: Rather than active marketing, Burke relies on investor referrals, emphasizing trust and performance to attract new investors.About Tim MaiTim Mai is a real estate investor, fund manager, mentor, and founder of HERO Mastermind for REI coaches. He has helped many real estate investors and coaches become millionaires. Tim continues to help busy professionals earn income and build wealth through passive investing. He is also a creative marketer and promoter with incredible knowledge and experience, which he freely shares. He has lifted himself from the aftermath of war, achieving technical expertise in computers, followed by investment success in real estate, management skills, and a lofty position among real estate educators and internet marketers. Tim is an industry leader who has acquired and exited well over $50 million worth of real estate and is currently an investor in over 2700 units of multifamily apartments.Connect with TimWebsite: Capital Raising PartyFacebook: Tim Mai | Capital Raising Nation Instagram: @timmaicomTwitter: @timmaiLinkedin: Tim MaiYouTube: Tim MaiConnect with UsTo learn more about partnering with us, visit our website at https://javierhinojo.com/ and www.allstatescapitalgroup.com, or send an email to admin@allstateseg.com. Sign up to get our Free Apartment Due Diligence Checklist Template and Multifamily Calculator by visiting https://javierhinojo.com/free-tools/.To join Javier's Mastermind, go to https://javierhinojo.com/mastermind/ and to apply to his BDB Mastermind, see https://javierhinojo.com/mastermind/#apply_form and answer the form.
This week on the RV Podcast: The chain of Love's Travel Centers is opening up more and more space for RV camping at a truck stop, not just overnighting, but multiple night stays if you want. We'll share the details in our Interview of the Week! What's up with this? Crackerbarrel is closing some if its restaurants where RVers like to overnight. Where can you get the oil changed on your Class C motorhomes? Our RV Community has some practical suggestions. And answering one of our questions of the week, we tell you just how strong the wind has to be to flip an RV. All this, plus the RV News of the Week and much more coming up in Episode #494 of the RV Podcast
Follow Mike and Shawn on Instagram! Shawn: @shawn_dimartile Mike: @miketighe_ In this episode, our host Shawn DiMartile interviews Rob Beardsley, co-founder of Lone Star Capital, about the current state of the multifamily industry and how to underwrite deals in today's market. Rob shares insights on the changing landscape of rent increases, the impact of the supply pipeline on rent growth, and the importance of being strategic with capital expenditures. He also discusses the shift in cap rates and the opportunities for investing in higher-quality assets. Rob emphasizes the importance of overcoming imposter syndrome and offers advice on networking and building valuable relationships in the industry. Here's what you can expect from this episode: Rent increases can no longer be taken for granted in today's market, and a more selective and careful approach is needed when underwriting business plans The supply pipeline in the multifamily space is robust, which will keep a lid on rent growth in the near term. However, there will be solid rent growth on the back end once the supply glut is resolved Underwriting cap rate compression is possible in today's market, despite the general rule of expanding exit cap rates Class C assets pose higher risks in a recession than Class A assets, as Class C tenants are more income insecure and have less savings Overcoming imposter syndrome and being authentic in networking can lead to valuable connections and opportunities in the industry How to connect with Rob: Website: www.lscre.com Learn more about Mike and Shawn! Shawn: www.investorshawn.com Mike: www.investormike.com
Welcome to the Best Ever midweek news brief, a new series where we will highlight the top headlines CRE investors should be paying attention to this week, followed by a deep dive on a larger news topic or trend alongside a CRE expert. Today's Headlines: Self-Storage Boom Set to Peak: A recent report from Yardi Matrix predicts a surge in supply for 2024 and 25, followed by a decline in later years, signaling a major shift in what's become an attractive asset class for investors. ‘Cause for Optimism' in NNN?: Triple-net-lease average closing cap rates declined in January while inventory dropped for a second consecutive month, to signs that Chris Lomuto of Northmarq says could be “cause for optimism.” Rents Are Cooling … Sort of: New “luxury” Class A supply is putting downward pressure on rents at all price points. It's a phenomenon called “filtering,” and there are 12 U.S. markets where Class C rents are falling at least 6% year-over-year. All 12 of those markets have supply expansion rates ABOVE the U.S. average. Today's Guest: Joining host Paul Mueller on the Best Ever Show today is Jay Parsons. Jay is Head of Economics and Industry Principals at RealPage. As a rental housing economist, Jay is one of the leading voices in multifamily real estate. He's an author, speaker, and an expert in market trends and forecasts, rental housing policy issues, property management, and more. If you want to read more from Jay on this story, he's posted on Twitter and LinkedIn about it recently. You can also follow him on LinkedIn and on Twitter @JayParsons. Sponsors: Monarch Money My1031Pros
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