A newsletter about modern entrepreneurship, AI, business, and meaningful success. <br/><br/><a href="https://www.vladsnewsletter.com?utm_medium=podcast">www.vladsnewsletter.com</a>
"Not me" | Vlad's Newsletter Podcast
Claim This Podcastby Vladyslav Podoliako
10 episodes
Updated Daily
Accepts GuestsHas Sponsors
9
Podcast Authority
BetaPoorBased on show quality, social media presence, reviews, charts, and more
Quality18
Social0
YouTube0
Engagement0
Podcast Overview
A newsletter about modern entrepreneurship, AI, business, and meaningful success. <br/><br/><a href="https://www.vladsnewsletter.com?utm_medium=podcast">www.vladsnewsletter.com</a>
Language
🇺🇲
Publishing Since
4/18/2025
Unlock The Full Podcast Authority Score Report
See how your podcast performs across key metrics
9
Podcast Authority
BetaPoorBased on show quality, social media presence, reviews, charts, and more
Quality18
Social0
YouTube0
Engagement0
6
Excellent Areas
1
Good Performance
12
Growth Opportunities
excellent
Episode Length
40 minutes
Performing excellently!
good
iTunes Tags
6.5/10
Recommendations available
Unlock the full report to see detailed tips
poor
Publishing Consistency
Every 34 days
Recommendations available
Unlock the full report to see detailed tips
+16 More Metrics
Unlock comprehensive insights including:
- • YouTube presence analysis
- • Social media reach metrics
- • RSS compliance scoring
- • Podcast 2.0 features
- • Technical standards
What's Included in Your Full Report
Detailed Analytics
- Complete breakdown of all 19 authority metrics
- Personalized recommendations for each metric
- Industry benchmarks and comparisons
- Technical RSS feed analysis and compliance scoring
Growth Strategies
- Step-by-step action plans for improvement
- Quick wins to boost your score immediately
- Pro tips from successful podcasters
Get your free podcast insights report
See how your show performs across every key metric
Instant delivery
No spam
Attract Better Guests
High authority scores make your podcast more attractive to industry leaders and influencers who want to appear on credible shows.
Secure Sponsorships
Sponsors look for podcasts with proven authority and engagement. Your score demonstrates your podcast's value to potential partners.
Grow Your Audience
Understanding your strengths and weaknesses helps you make data-driven decisions to expand your listener base effectively.
1 verified contact email on file for "Not me" | Vlad's Newsletter Podcast
Pitch yourself as a guest, propose sponsorships, or reach out directly to the host.
Recent Episodes
June 19, 2026
"Not Me" Podcast Episode #11: The Founder's Playbook: Building an AI-Native Startup
<p>Hey friends, new episode is live. I know, I know, it’s been a while.</p><p>I spent few days with one of those documents most people skim and forward without reading. A major lab’s full playbook for building an AI-native startup. Idea to Scale, mapped for 2026.</p><p>Fifty-odd pages on how to move faster than ever.</p><p>I read it three times. The third time, I found the opposite lesson hiding underneath all the speed.</p><p><strong>Building just became free. Being wrong didn’t. It only got faster, and better dressed.</strong></p><p>That’s the episode. Grab a coffee, and wishing you a great listing.</p><p>Here’s the short version.</p><p><p>Vlad's Newsletter is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber.</p></p><p>The Wall Came Down</p><p>For most of startup history there were two camps. People who could build, and people with ideas worth building. A wall ran between them.</p><p>That wall is gone. You describe what you want in plain language, and real software assembles itself. The founder stops being the one who types the code and becomes the one who <a target="_blank" href="https://www.vladsnewsletter.com/p/sub-agents">directs the agents</a> that do.</p><p>The <a target="_blank" href="https://www.vladsnewsletter.com/p/time-for-idea-people">idea person’s moment</a> finally arrived. Not as a feeling. As a tool.</p><p>The Part Nobody Quotes</p><p>Even before any of this, more than 40% of startups died for one reason: they built something nobody wanted.</p><p>That was the rate when building was hard. When a prototype cost months and money. Painful. And also a filter.</p><p>A constraint is a riverbank. Remove every bank and you do not get a faster river. You get a flood.</p><p>AI removed the banks. The model will build a beautiful product around a wrong idea with the same enthusiasm it brings to a right one. A working prototype feels like proof. It is a stage prop. The conversation you have while holding it is the evidence.</p><p>The Yes-Machine Problem</p><p>Ask the model to validate your idea, it finds the evidence. Ask it to size your market, it finds the fundable number.</p><p>Confirmation bias now ships with its own research department.</p><p>The machine says yes by default. Which leaves exactly one reliable source of no in the building.</p><p>You.</p><p><strong>When everyone can build anything, the rarest skill is knowing what not to. Call it the Discernment Premium.</strong></p><p>What Gets Overlooked</p><p>The lean-team dream has a hidden tax.</p><p>In a normal company, judgment is spread across a dozen people. In a team of five, or one, all of it lands on you. Every agent output is a decision waiting for a human.</p><p>You do not burn out from doing too much. You burn out from deciding too much.</p><p>The Only Moat Left</p><p>“We built it first” is dead. Someone rebuilds it next month.</p><p>So what is left to defend? Domain depth. The data your users leave behind. The workflows they build on top of you, until leaving becomes a project instead of a choice.</p><p>Notice what none of those are. The code. The code was never the moat.</p><p>My Take</p><p>In the episode, I walk through all four stages- Idea, MVP, Launch, and Scale- and what to refuse at each one.</p><p>But it comes down to this. The machine will do almost all of the building now, instantly, in whatever direction you point it. So the whole job quietly folded into a single act.</p><p>Choosing the direction.</p><p><strong>The tools got the power. You kept the responsibility. The bottleneck was never what you could build. It is what you are willing to choose.</strong></p><p>One more thing before the picks….</p><p><p>The podcast just crossed <strong>41.6K downloads.</strong> I started “<strong>Not Me</strong>” half expecting an empty room. A few people thinking out loud into a microphone. Now there are thousands of you, pressing play every week. In a world drowning in free, auto-generated content, attention is the one thing the machine cannot manufacture for me. And you keep spending yours here. <strong>Thank you.</strong></p><p>Point the machine. Be the no. </p></p><p><strong>Stay curious. Stay deciding. Stay building.</strong></p><p>Post-Credit Scene</p><p>A few things worth your time this week:</p><p><a target="_blank" href="https://store.hbr.org/product/power-and-prediction-the-disruptive-economics-of-artificial-intelligence/10580">📘</a><a target="_blank" href="https://store.hbr.org/product/power-and-prediction-the-disruptive-economics-of-artificial-intelligence/10580"><strong>Power and Prediction: The Disruptive Economics of Artificial Intelligence</strong></a> (Harvard Business Review Press) – The economics under this whole episode: AI makes prediction cheap, which makes judgment expensive. Their line, not mine: AI “decouples human prediction from human judgment.”</p><p><a target="_blank" href="https://creators.spotify.com/pod/profile/lightconepodcast/episodes/How-AI-Is-Changing-Enterprise-e2v30h0">🎧</a><a target="_blank" href="https://creators.spotify.com/pod/profile/lightconepodcast/episodes/How-AI-Is-Changing-Enterprise-e2v30h0"><strong>The Lightcone: How AI Is Changing Enterprise</strong></a> – A viral report said 95% of enterprise AI projects fail. The YC partners’ read is the founder’s whole opening: it is not that AI does not work, it is that big companies cannot build with it. That is the gap you walk through.</p><p><a target="_blank" href="https://fortune.com/2026/05/18/solo-founders-ai-automation-entire-teams-entrepreneurs/">📝</a><a target="_blank" href="https://fortune.com/2026/05/18/solo-founders-ai-automation-entire-teams-entrepreneurs/"><strong>Solo founders are using AI to do the work of entire teams, but going it alone has limits</strong></a> (Fortune, May 18, 2026) – The honest footnote to the lean dream. The agents handle the tasks. The judgment, the bill, and the loneliness do not delegate.</p><p><a target="_blank" href="https://www.anthropic.com/product/claude-cowork">🛠️</a><a target="_blank" href="https://www.anthropic.com/product/claude-cowork"><strong>Claude Cowork</strong></a> (Anthropic) – The “ops team” from the playbook, made real. Hand it the assembly, keep the decisions. The clearest live example of the split this episode is about.</p><p><a target="_blank" href="https://www.youtube.com/watch?v=ojjCvICC86c">📺</a><a target="_blank" href="https://www.youtube.com/watch?v=ojjCvICC86c"><strong>The Bear, Season 5</strong></a> (FX, premieres June 25) – The most honest show about building anything. No money, a storm at the door, a founder who walked away, a crew chasing one star. The lesson they land on is the lesson above: it is not the equipment, it is the people, and the taste. Final season.</p><p>Thanks for listening,</p><p>Vlad</p><p></p><p></p><p></p><p></p><p></p> <br/><br/>This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit <a href="https://www.vladsnewsletter.com/subscribe?utm_medium=podcast&utm_campaign=CTA_2">www.vladsnewsletter.com/subscribe</a>
February 12, 2026
"Not Me" Podcast Episode #10: The End of Context Windows
<p>Hey, it’s Vlad.</p><p>Everyone’s obsessed with building bigger AI brains.</p><p>More parameters. Longer context windows. Better reasoning.</p><p>But here’s what MIT just figured out: you don’t need a bigger brain.</p><p>You need a smarter one.</p><p>Researchers Alex Zhang, Tim Kraska, and Omar Khattab from MIT CSAIL dropped a paper that’s getting way less attention than it deserves. It’s called Recursive Language Models, or RLMs.</p><p>And it flips everything we know about AI limitations on its head.</p><p>The Problem Nobody Solved</p><p>Let’s start with the ugly truth.</p><p>Every AI model you use has a memory problem.</p><p>GPT-5? It chokes after 272,000 tokens. Claude? Same ballpark. Even with these “massive” context windows, the models get dumber the more you feed them.</p><p>It’s called <strong>context rot</strong>.</p><p>Think about it. You paste a 50-page document and ask a simple question. The model starts hallucinating. Missing obvious facts. Getting confused.</p><p>Why?</p><p>Because cramming everything into the context window is like forcing someone to read a 10,000-page encyclopedia cover-to-cover before answering your question.</p><p>It’s absurd.</p><p>We’ve been treating AI like a student with a strict word limit on their exam. No wonder it struggles.</p><p>The MIT Breakthrough</p><p>Here’s where it gets interesting.</p><p>MIT asked a different question: What if the AI didn’t have to read everything at once?</p><p>What if it could treat the prompt as an external environment? A workspace. A filing cabinet can be explored strategically.</p><p>That’s RLM.</p><p>Instead of feeding GPT-5 your entire 10-million-token corpus directly, you store it as a Python variable. The model never sees it in the prompt. Instead, it writes code to peek at specific sections. Grep through for patterns. Chunk it up. And here’s the kicker: <strong>it can spawn sub-models to investigate specific parts.</strong></p><p>It’s recursion. The model calls itself. Over and over. Each layer handles a smaller, more manageable piece.</p><p>Like hiring a research team instead of forcing one person to do everything.</p><p>Sound familiar? It’s the same philosophy behind sub-agents I wrote about recently. Stop making one AI do everything. Orchestrate.</p><p>The Numbers Don’t Lie</p><p>Let’s talk results.</p><p>On the OOLONG benchmark, which is designed to torture AI with long context tasks, here’s what happened:</p><p>* <strong>Base GPT-5?</strong> Crashed and burned. Near zero performance.</p><p>* <strong>GPT-5 with RLM?</strong> 58% F1 score. From essentially nothing to majority correct.</p><p>That’s not an improvement. That’s a resurrection.</p><p>On the BrowseComp-Plus benchmark, RLM handled over <strong>10 million tokens</strong>. Two orders of magnitude beyond the context window. And it did it for roughly the same cost as running the base model. Sometimes cheaper.</p><p><strong>91.33% accuracy</strong> on a task where the base model literally couldn’t fit the input.</p><p>This isn’t incremental progress. This is a paradigm shift.</p><p>Why Programmatic Decomposition Beats Everything</p><p>You might ask: Why not just summarize the context? Compress it?</p><p>They tried that. It’s called context compaction.</p><p>Here’s the problem. Every time you summarize, you lose information. It’s entropy. Irreversible.</p><p>Summarization agents on the same benchmarks? 70% at best. Often worse.</p><p><strong>RLM doesn’t summarize. It delegates.</strong> Big difference.</p><p>The model actively decides what to look at. Uses regex filters. Keyword searches. Strategic sampling. It behaves less like a student cramming for an exam and more like a senior researcher with a team of assistants.</p><p>And because each sub-call runs with a fresh context window, there’s no pollution. No context rot. Each recursive agent stays sharp.</p><p>What Most People Overlook</p><p>Here’s the thing that’s flying under the radar.</p><p><strong>This approach is model-agnostic.</strong></p><p>RLM works with GPT-5. With Qwen. With Claude. Open-source, closed-source, doesn’t matter.</p><p>It’s an inference strategy, not an architecture change. You don’t need to retrain anything.</p><p>And the cost structure is fascinating. Using GPT-5-mini for recursive calls while GPT-5 handles the final synthesis? Cheaper than running GPT-5 on truncated input. Better results. Lower price.</p><p>That’s the arbitrage nobody’s talking about.</p><p>The Bitter Lesson, Again</p><p>Alex Zhang called this a “bitter-lesson-pilled approach.”</p><p>If you don’t know Rich Sutton’s Bitter Lesson, it’s simple: general methods that leverage computation beat specialized hand-engineered solutions. Every time.</p><p>RLM fits perfectly.</p><p>Instead of designing clever compression schemes or specialized architectures, you give the model tools and let it figure out the strategy.</p><p>The model learns to peek first. Scan for relevant sections. Delegate the hard parts. Build up answers iteratively.</p><p>No human had to specify these behaviors. They emerge naturally when you give the model the right environment.</p><p>That’s the meta-lesson here.</p><p><p><strong>Stop constraining AI. Start enabling it.</strong></p></p><p>Practical Implications</p><p>So what does this mean for you?</p><p>If you’re building with AI, pay attention.</p><p>Long-horizon agents, the ones that need to process weeks or months of data, suddenly become viable. Legal document analysis? Entire codebase understanding? Research synthesis across hundreds of papers?</p><p>All unlocked.</p><p>Prime Intellect is already building RLMEnv, a training environment for this paradigm. They’re betting this is the next major breakthrough after reasoning scaling.</p><p>My prediction? Within 12 months, every serious AI infrastructure will support RLM-style inference.</p><p>The teams building this capability today will be the ones dominating tomorrow.</p><p><p>Vlad's Newsletter is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber.</p></p><p>The Overlooked Angle</p><p>What most coverage misses is the philosophical shift.</p><p>We’ve been treating context windows as hard limits. Physical constraints. Like asking “how do we fit more data in this box?”</p><p>MIT asked: <strong>“What if we don’t put the data in the box at all?”</strong></p><p>That reframing is everything.</p><p>It’s not about bigger models. It’s about smarter orchestration.</p><p>Sound familiar?</p><p>It’s the same pattern we’re seeing with sub-agents. With MCP. With agentic workflows.</p><p>The future isn’t monolithic AI. It’s distributed intelligence. Each piece specialized. Each piece coordinated.</p><p>RLM is just another proof point.</p><p>Takeaway</p><p>The context window problem everyone complained about? Solved.</p><p>Not through brute force. Through elegance.</p><p>The AI doesn’t need to see everything at once. It needs the right tools to explore strategically.</p><p>That’s RLM.</p><p>MIT just gave us the blueprint. Now it’s on us to build with it.</p><p>The code is open source. The paper is public. The opportunity is sitting there.</p><p>Question is: are you going to use it?</p><p>Worth Reading While the Episode Downloads</p><p>* <a target="_blank" href="https://www.vladsnewsletter.com/p/sub-agents"><strong>Sub Agents</strong></a> – The frontier of tech just shifted again, and most people haven’t noticed yet.</p><p>* <a target="_blank" href="https://www.vladsnewsletter.com/p/ideation"><strong>Ideation</strong></a> – Forget validation. Build what no search result can show you.</p><p>* <a target="_blank" href="https://www.vladsnewsletter.com/p/ai-generalist"><strong>AI Generalist</strong></a> – Playbook on How to Make $300K+ While Everyone Else Fights for Scraps</p><p>Post-Credit Scene</p><p>A few things worth your time this week:</p><p><strong>📄 Read</strong>: <a target="_blank" href="https://levelup.gitconnected.com/why-i-believe-recursive-language-models-are-the-future-of-long-context-reasoning-8aff1738cbc6"><strong>“Why I Believe Recursive Language Models Are the Future of Long-Context Reasoning”</strong></a> – A developer’s breakdown of the RLM paper that goes beyond summary. Published this month.</p><p><strong>🎧 Listen</strong>: <a target="_blank" href="https://www.lennysnewsletter.com/p/we-replaced-our-sales-team-with-20-ai-agents"><strong>Lenny’s Podcast: “We replaced our sales team with 20 AI agents”</strong></a> with Jason Lemkin. 1.2 humans managing 20 AI agents doing the work of 10 SDRs and AEs. This is happening now. (January 2026)</p><p><strong>🔬 Deep Dive</strong>: <a target="_blank" href="https://www.primeintellect.ai/blog/rlm"><strong>Prime Intellect’s “Recursive Language Models: the paradigm of 2026”</strong></a> – They’re betting their entire research agenda on this. Worth understanding why.</p><p><strong>🛠 Tool</strong>: The <a target="_blank" href="https://github.com/alexzhang13/rlm"><strong>RLM GitHub repo</strong></a> is live. Supports OpenAI, Anthropic, local models. If you’re technical, start experimenting today.</p><p><strong>🎙 Podcast</strong>: <a target="_blank" href="https://player.fm/series/practical-ai/ep-2025-was-the-year-of-agents-whats-coming-in-2026"><strong>Practical AI: “2025 Was The Year Of Agents, What’s Coming In 2026?”</strong></a> – Chris and Daniel break down what actually mattered and what’s next. Grounded predictions, not hype.</p><p>Thank you for listening and reading. See you in the next edition.</p><p>Vlad</p> <br/><br/>This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit <a href="https://www.vladsnewsletter.com/subscribe?utm_medium=podcast&utm_campaign=CTA_2">www.vladsnewsletter.com/subscribe</a>
February 5, 2026
"Not Me" Podcast Episode #9: Boring Bet
<p>Hey friends, new podcast episode arrived.</p><p>I spent the weekend going through one of those dense institutional reports that most people skip.</p><p>You know the type. Fifty pages of charts, footnotes, macro projections.</p><p>But buried in all that noise was something worth your attention.</p><p><strong>The 2026 ISG Outlook makes one argument very clearly: American preeminence isn’t going anywhere.</strong></p><p>And here’s the thing.</p><p>This isn’t blind optimism. It’s not flag-waving patriotism dressed up as investment advice.</p><p>It’s math.</p><p>The Case They’re Making</p><p>Let’s break it down.</p><p>The U.S. has three structural advantages that no other economy can replicate right now:</p><p><strong>1. Labor Productivity</strong></p><p>American workers produce more output per hour than almost any other developed nation. This isn’t about working harder. It’s about working smarter, with better tools, better systems, better technology.</p><p>When AI accelerates this, you get compounding.</p><p><strong>2. Natural Resources</strong></p><p>Energy independence changed everything. The shale revolution wasn’t just about oil prices. It was about leverage. When Europe froze, America negotiated.</p><p><strong>3. Innovation Ecosystem</strong></p><p>Here’s what gets overlooked: the U.S. doesn’t just lead in AI. It leads in the <strong>commercialization</strong> of AI.</p><p>Ideas are cheap. Turning ideas into products that scale globally? That’s the hard part.</p><p>And that pipeline, from university labs to venture capital to public markets, is still uniquely American.</p><p>But What About the Problems?</p><p>The report doesn’t ignore the risks. And neither should you.</p><p><strong>Federal debt</strong> is a real concern. The numbers are ugly. But here’s the contrarian take: debt matters less when you’re the world’s reserve currency and your economy is growing faster than your debt service.</p><p>Is it sustainable forever? No.</p><p>Is it sustainable for the next decade? Probably.</p><p><strong>Tariff policies</strong> create friction. They slow things down. But they also force reshoring and diversification that might be strategically smart in a world where supply chains are weapons.</p><p><strong>China friction</strong> is the wildcard. Nobody knows how this plays out. But the ISG argument is that American institutional checks and balances, messy as they are, provide more stability than any alternative.</p><p>Democracy is inefficient. But it’s also self-correcting.</p><p>The Hedge Question</p><p>Here’s where it gets interesting.</p><p>A lot of people think gold is the answer to uncertainty.</p><p>Others are betting on bitcoin.</p><p>The report’s take? Neither offers the same reliable long-term protection as a diversified equity portfolio.</p><p>Why?</p><p><strong>Gold</strong> is a fear trade. It spikes during panic and flatlines during growth. Over long time horizons, it underperforms.</p><p><strong>Bitcoin</strong> is still too young, too volatile, too correlated with risk-on sentiment to function as a true hedge.</p><p>The boring answer, diversified American equities, keeps outperforming the exciting alternatives.</p><p>Nobody wants to hear that. But it’s true.</p><p>What Gets Overlooked</p><p>Here’s what most people miss when reading reports like this:</p><p><strong>The opportunity cost of sitting out.</strong></p><p>Every year you wait for the “perfect entry point,” you’re losing compounding.</p><p>The ISG projects mid-single-digit returns and sturdy global growth.</p><p>That sounds boring. Five percent. Six percent.</p><p>But compounded over a decade? That’s wealth.</p><p>The people who got rich in American markets didn’t time the bottom. They stayed invested through the noise.</p><p>The Real Advantage Nobody Talks About</p><p>Think of it like a startup.</p><p>Every country has bugs. Political instability. Debt problems. Social tensions.</p><p>America has all of these. Loudly. Publicly. On Twitter.</p><p>But here’s the difference: <strong>America debugs in real time.</strong></p><p>The courts push back. The press investigates. Elections happen. Power transfers.</p><p>Compare that to systems where problems compound in silence until they explode.</p><p>Which one would you bet on for the next 20 years?</p><p>My Take</p><p>Look, I’m not a financial advisor. This isn’t investment advice.</p><p>But here’s how I think about it.</p><p>If you’re building something, if you’re running companies, if you’re betting on the future, you need to understand where the wind is blowing.</p><p>And right now, despite everything, despite the debt, despite the politics, despite the geopolitical chaos, the wind is still blowing toward America.</p><p>Not because America is perfect.</p><p>Because America is <strong>resilient</strong>.</p><p>And resilience, over long time horizons, beats everything else.</p><p><strong>The institutions that make democracy feel slow are the same institutions that make it stable. That’s the trade-off. And it’s a good one.</strong></p><p>Stay invested. Stay patient. Stay building.</p><p>Vlad</p><p><strong>Post-Credit Scene</strong></p><p>A few things worth your time this week:</p><p><a target="_blank" href="https://hbr.org/podcast/2026/01/ray-dalio-on-economic-trends-investing-and-making-decisions-amid-uncertainty">🎧 </a><a target="_blank" href="https://hbr.org/podcast/2026/01/ray-dalio-on-economic-trends-investing-and-making-decisions-amid-uncertainty"><strong>HBR IdeaCast: Ray Dalio on Economic Trends, Investing, and Making Decisions Amid Uncertainty</strong></a> (January 20, 2026) – Dalio breaks down his five big forces framework and where the U.S. sits in the current cycle. Essential listening if you want to understand the macro picture. </p><p><a target="_blank" href="https://www.amazon.com/Principles-Investment-Economic-Ray-Dalio/dp/1501124064">📘 </a><a target="_blank" href="https://www.amazon.com/Principles-Investment-Economic-Ray-Dalio/dp/1501124064"><strong>“How Countries Go Broke: The Big Cycle” by Ray Dalio</strong></a> – The #1 NYT bestseller that Washington insiders are passing around. Dense but rewarding. If you want to understand why debt cycles matter and what the warning signs look like, start here.</p><p><a target="_blank" href="https://open.spotify.com/show/1te7oSFyRVekxMBJUSethH">🎧 </a><a target="_blank" href="https://open.spotify.com/show/1te7oSFyRVekxMBJUSethH"><strong>Odd Lots: Goldman’s Hatzius and Snider on the Outlook for 2026</strong></a> (December 29, 2025) – Joe and Tracy sit down with Goldman’s chief economist and chief US equity strategist to dissect what happened in 2025 and whether it can repeat. Spoiler: AI and tariffs are the two forces shaping everything. </p><p><a target="_blank" href="https://www.goldmansachs.com/insights/articles/us-gdp-growth-is-projected-to-outperform-economist-forecasts-in-2026">📊 </a><a target="_blank" href="https://www.goldmansachs.com/insights/articles/us-gdp-growth-is-projected-to-outperform-economist-forecasts-in-2026"><strong>Goldman Sachs: US GDP Growth Is Projected to Outperform Economist Forecasts in 2026</strong></a> (January 11, 2026) – Goldman projects 2.5% GDP growth versus the consensus 2.1%. Tax cuts, real wage gains, and AI investment are the drivers. Quick read, worth bookmarking. </p><p><a target="_blank" href="https://www.deloitte.com/us/en/insights/topics/economy/global-economic-outlook-2026.html">🌍 </a><a target="_blank" href="https://www.deloitte.com/us/en/insights/topics/economy/global-economic-outlook-2026.html"><strong>Deloitte: Global Economic Outlook 2026</strong></a><a target="_blank" href="https://www.deloitte.com/us/en/insights/topics/economy/global-economic-outlook-2026.html"> </a>– For the full global picture. The U.S. section is particularly strong on why “resilient” remains the best one-word description of the American economy. </p><p>Thanks for listing </p><p>Vlad</p> <br/><br/>This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit <a href="https://www.vladsnewsletter.com/subscribe?utm_medium=podcast&utm_campaign=CTA_2">www.vladsnewsletter.com/subscribe</a>
10 total episodes available
Deep-dive analytics for "Not me" | Vlad's Newsletter Podcast
Frequently asked questions
Have a different question and can't find the answer you're looking for? Reach out to our support team by sending us an email and we'll get back to you as soon as we can.
- What is "Not me" | Vlad's Newsletter Podcast?
- How often does this podcast release new episodes?
This podcast updates daily.
- Where can I listen to this podcast?
This podcast is available on 4 platforms including Apple Podcasts, Spotify, and more. You can also use the RSS feed directly.
- Does this podcast accept guests?
Information about guest appearances is not available.
Legal Disclaimer
Pod Engine is not affiliated with, endorsed by, or officially connected with any of the podcasts displayed on this platform. We operate independently as a podcast discovery and analytics service.
All podcast artwork, thumbnails, and content displayed on this page are the property of their respective owners and are protected by applicable copyright laws. This includes, but is not limited to, podcast cover art, episode artwork, show descriptions, episode titles, transcripts, audio snippets, and any other content originating from the podcast creators or their licensors.
We display this content under fair use principles and/or implied license for the purpose of podcast discovery, information, and commentary. We make no claim of ownership over any podcast content, artwork, or related materials shown on this platform. All trademarks, service marks, and trade names are the property of their respective owners.
While we strive to ensure all content usage is properly authorized, if you are a rights holder and believe your content is being used inappropriately or without proper authorization, please contact us immediately at hey@podengine.ai for prompt review and appropriate action, which may include content removal or proper attribution.
By accessing and using this platform, you acknowledge and agree to respect all applicable copyright laws and intellectual property rights of content owners. Any unauthorized reproduction, distribution, or commercial use of the content displayed on this platform is strictly prohibited.