Podcasts about 2X

From the archive - This episode was originally recorded and published in 2022. Our interviews on Entrepreneurs On Fire are meant to be evergreen, and we do our best to confirm that all offers and URL's in these archive episodes are still relevant. Austin Netzley is the founder of 2X and author of the updated book, From 6 to 7 Figures. Top 3 Value Bombs 1. A big key to success is not as sexy as a lot of gurus out there talk about. Think about operational excellence, turning your business into a machine that can thrive without you. If you take that perspective, it's going to lead to a very healthy business. 2. Make the strategic decisions on how you're going to be different, how you're going to solve real problems, and who your customer is. It will make your entrepreneur life much easier. 3. Systems make things much more repeatable, consistent, and not reliant on you. Get a FREE copy of the updated & expanded book for a limited-time only - From 6 to 7 Figures Sponsors HighLevel - The ultimate all-in-one platform for entrepreneurs, marketers, coaches, and agencies. Learn more at HighLevelFire.com. Freedom Circle - A powerful community of entrepreneurs led by JLD. Are you ready to go from idea to income in 90-days? Visit Freedom-Circle.com to learn more.

Welcome back to Fitness Stuff for Normal People. On this episode, Marianna and Tony walk through seven things you can do to make a calorie deficit suck less because while “eat less than you burn” is simple on paper, it's much harder to execute in real life. They break down why fat loss feels so difficult and the practical adjustments that make it easier to stick with, from managing hunger and sleep to setting up your environment so willpower isn't doing all the work. If you're in a deficit and feeling like it's starting to wear on you, this episode helps you focus on what actually matters and make the process more sustainable.⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Sign up for Fitness Stuff PREMIUM here!!⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ALL of our complete 12-week training programsBonus episodes every FridayJust $5 /month⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Legion Athletics⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠BOGO 50% off for your first order + 2X points on every order after thatuse code “FSPOD” at checkoutTimestamps(2:16) Map vs territory(5:39) Protect sleep like it's part of your diet(10:33) Eat a high-protein diet(20:28) Engineer your environment so willpower barely matters(26:14) Don't cut out foods you enjoy(34:58) Learn how to cook and understand your way around the kitchen(40:51) Play with meal timing(44:55) Mini cut vs normal cut

On this episode of Fitness Stuff for Normal People, Tony and Marianna walk through a complete, evidence-based guide to setting up a lean bulk. They explain how to maximize muscle growth while minimizing fat gain during a bulking or muscle-building phase, covering how to properly set calories and macros and what actually matters in training. The conversation focuses on how to build workouts that support muscle growth without unnecessary extremes or confusion. By the end of the episode, listeners will have everything they need to confidently take themselves through a lean bulk or muscle-building phase.⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Sign up for Fitness Stuff PREMIUM here!!⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ALL of our complete 12-week training programsBonus episodes every FridayJust $5 /month⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Legion Athletics⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠BOGO 50% off for your first order + 2X points on every order after thatuse code “FSPOD” at checkoutTimestamps(6:15) Lean vs Dirty Bulk(12:20) How To Train(24:25) Calorie Goals(33:29) Protein Goals(37:36) Misc. Questions

Last year, you may have stumbled across a press story or social media post about a 40-year-old man who decided to play college baseball at the JUCO level. Well, that man is Aaron Rouselle, and he is our special guest on this joint episode of In the Booth hosted by Flobo Boyce and the Black Baseball Mixtape podcast. Coach Rouselle is a true inspiration to anyone with a dream. Yes, he played college baseball at an advanced age, but he is also a 2X liver transplant survivor, a cancer survivor, he had shingles, and he even had mold growing in his lungs. The fact that Aaron is with us today is indeed a miracle. He now leads young men in the game and teaches them more than baseball. He teaches his players about life. This episode is in partnership with the Players Alliance, Numbers Game Scorebooks, and Minority Prospects.

On this episode of Fitness Stuff for Normal People, Marianna and Tony rank the biggest fitness and health trends of 2025 using a tier list format, from S Tier trends that are actually worth paying attention to to F Tier trends you can safely ignore. They talk through what's helpful, what's overhyped, and what's just confusing online, covering everything from supplements and diets to wearables, recovery tools, and popular wellness trends. If you've ever wondered which trends are worth trying and which ones you don't need to stress about, this episode helps you sort through the noise.⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Sign up for Fitness Stuff PREMIUM here!!⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ALL of our complete 12-week training programsBonus episodes every FridayJust $5 /month⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Legion Athletics⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠BOGO 50% off for your first order + 2X points on every order after thatuse code “FSPOD” at checkout

Send us a textOn the latest episode of The Lost In The Sauce Podcast, Sauce is joined by Grammy-nominated and 2X-time Dove Award winner Aaron Cole. On this episode, Sauce and Aaron sit down to discuss his journey through life and music, from growing up in Bristol, VA, to moving to Nashville to make the album “Sorry I Changed.” They also talk about the new EP “Where Do We Go From Here,” marriage, fatherhood, and much more. More! Links For Aaron Cole | https://aaroncole.lnk.to/wdwgfhIG | https://www.instagram.com/iamaaroncole?igsh=b3pxOW5yOXJwZm9nIntro | Aaron Cole - Refuge / Aaron Cole & nobigdyl - MAN ABOVEPass The Aux Segment | Aaron Cole - I Love ItPodcast Platforms | https://linktr.ee/Lostinthesauce5Sauce IG | https://www.instagram.com/sauceville_615/

Happy New Year! You may have noticed that in 2025 we had moved toward YouTube as our primary podcasting platform. As we'll explain in the next State of Latent Space post, we'll be doubling down on Substack again and improving the experience for the over 100,000 of you who look out for our emails and website updates!We first mentioned Artificial Analysis in 2024, when it was still a side project in a Sydney basement. They then were one of the few Nat Friedman and Daniel Gross' AIGrant companies to raise a full seed round from them and have now become the independent gold standard for AI benchmarking—trusted by developers, enterprises, and every major lab to navigate the exploding landscape of models, providers, and capabilities.We have chatted with both Clementine Fourrier of HuggingFace's OpenLLM Leaderboard and (the freshly valued at $1.7B) Anastasios Angelopoulos of LMArena on their approaches to LLM evals and trendspotting, but Artificial Analysis have staked out an enduring and important place in the toolkit of the modern AI Engineer by doing the best job of independently running the most comprehensive set of evals across the widest range of open and closed models, and charting their progress for broad industry analyst use.George Cameron and Micah-Hill Smith have spent two years building Artificial Analysis into the platform that answers the questions no one else will: Which model is actually best for your use case? What are the real speed-cost trade-offs? And how open is “open” really?We discuss:* The origin story: built as a side project in 2023 while Micah was building a legal AI assistant, launched publicly in January 2024, and went viral after Swyx's retweet* Why they run evals themselves: labs prompt models differently, cherry-pick chain-of-thought examples (Google Gemini 1.0 Ultra used 32-shot prompts to beat GPT-4 on MMLU), and self-report inflated numbers* The mystery shopper policy: they register accounts not on their own domain and run intelligence + performance benchmarks incognito to prevent labs from serving different models on private endpoints* How they make money: enterprise benchmarking insights subscription (standardized reports on model deployment, serverless vs. managed vs. leasing chips) and private custom benchmarking for AI companies (no one pays to be on the public leaderboard)* The Intelligence Index (V3): synthesizes 10 eval datasets (MMLU, GPQA, agentic benchmarks, long-context reasoning) into a single score, with 95% confidence intervals via repeated runs* Omissions Index (hallucination rate): scores models from -100 to +100 (penalizing incorrect answers, rewarding ”I don't know”), and Claude models lead with the lowest hallucination rates despite not always being the smartest* GDP Val AA: their version of OpenAI's GDP-bench (44 white-collar tasks with spreadsheets, PDFs, PowerPoints), run through their Stirrup agent harness (up to 100 turns, code execution, web search, file system), graded by Gemini 3 Pro as an LLM judge (tested extensively, no self-preference bias)* The Openness Index: scores models 0-18 on transparency of pre-training data, post-training data, methodology, training code, and licensing (AI2 OLMo 2 leads, followed by Nous Hermes and NVIDIA Nemotron)* The smiling curve of AI costs: GPT-4-level intelligence is 100-1000x cheaper than at launch (thanks to smaller models like Amazon Nova), but frontier reasoning models in agentic workflows cost more than ever (sparsity, long context, multi-turn agents)* Why sparsity might go way lower than 5%: GPT-4.5 is ~5% active, Gemini models might be ~3%, and Omissions Index accuracy correlates with total parameters (not active), suggesting massive sparse models are the future* Token efficiency vs. turn efficiency: GPT-5 costs more per token but solves Tau-bench in fewer turns (cheaper overall), and models are getting better at using more tokens only when needed (5.1 Codex has tighter token distributions)* V4 of the Intelligence Index coming soon: adding GDP Val AA, Critical Point, hallucination rate, and dropping some saturated benchmarks (human-eval-style coding is now trivial for small models)Links to Artificial Analysis* Website: https://artificialanalysis.ai* George Cameron on X: https://x.com/georgecameron* Micah-Hill Smith on X: https://x.com/micahhsmithFull Episode on YouTubeTimestamps* 00:00 Introduction: Full Circle Moment and Artificial Analysis Origins* 01:19 Business Model: Independence and Revenue Streams* 04:33 Origin Story: From Legal AI to Benchmarking Need* 16:22 AI Grant and Moving to San Francisco* 19:21 Intelligence Index Evolution: From V1 to V3* 11:47 Benchmarking Challenges: Variance, Contamination, and Methodology* 13:52 Mystery Shopper Policy and Maintaining Independence* 28:01 New Benchmarks: Omissions Index for Hallucination Detection* 33:36 Critical Point: Hard Physics Problems and Research-Level Reasoning* 23:01 GDP Val AA: Agentic Benchmark for Real Work Tasks* 50:19 Stirrup Agent Harness: Open Source Agentic Framework* 52:43 Openness Index: Measuring Model Transparency Beyond Licenses* 58:25 The Smiling Curve: Cost Falling While Spend Rising* 1:02:32 Hardware Efficiency: Blackwell Gains and Sparsity Limits* 1:06:23 Reasoning Models and Token Efficiency: The Spectrum Emerges* 1:11:00 Multimodal Benchmarking: Image, Video, and Speech Arenas* 1:15:05 Looking Ahead: Intelligence Index V4 and Future Directions* 1:16:50 Closing: The Insatiable Demand for IntelligenceTranscriptMicah [00:00:06]: This is kind of a full circle moment for us in a way, because the first time artificial analysis got mentioned on a podcast was you and Alessio on Latent Space. Amazing.swyx [00:00:17]: Which was January 2024. I don't even remember doing that, but yeah, it was very influential to me. Yeah, I'm looking at AI News for Jan 17, or Jan 16, 2024. I said, this gem of a models and host comparison site was just launched. And then I put in a few screenshots, and I said, it's an independent third party. It clearly outlines the quality versus throughput trade-off, and it breaks out by model and hosting provider. I did give you s**t for missing fireworks, and how do you have a model benchmarking thing without fireworks? But you had together, you had perplexity, and I think we just started chatting there. Welcome, George and Micah, to Latent Space. I've been following your progress. Congrats on... It's been an amazing year. You guys have really come together to be the presumptive new gardener of AI, right? Which is something that...George [00:01:09]: Yeah, but you can't pay us for better results.swyx [00:01:12]: Yes, exactly.George [00:01:13]: Very important.Micah [00:01:14]: Start off with a spicy take.swyx [00:01:18]: Okay, how do I pay you?Micah [00:01:20]: Let's get right into that.swyx [00:01:21]: How do you make money?Micah [00:01:24]: Well, very happy to talk about that. So it's been a big journey the last couple of years. Artificial analysis is going to be two years old in January 2026. Which is pretty soon now. We first run the website for free, obviously, and give away a ton of data to help developers and companies navigate AI and make decisions about models, providers, technologies across the AI stack for building stuff. We're very committed to doing that and tend to keep doing that. We have, along the way, built a business that is working out pretty sustainably. We've got just over 20 people now and two main customer groups. So we want to be... We want to be who enterprise look to for data and insights on AI, so we want to help them with their decisions about models and technologies for building stuff. And then on the other side, we do private benchmarking for companies throughout the AI stack who build AI stuff. So no one pays to be on the website. We've been very clear about that from the very start because there's no use doing what we do unless it's independent AI benchmarking. Yeah. But turns out a bunch of our stuff can be pretty useful to companies building AI stuff.swyx [00:02:38]: And is it like, I am a Fortune 500, I need advisors on objective analysis, and I call you guys and you pull up a custom report for me, you come into my office and give me a workshop? What kind of engagement is that?George [00:02:53]: So we have a benchmarking and insight subscription, which looks like standardized reports that cover key topics or key challenges enterprises face when looking to understand AI and choose between all the technologies. And so, for instance, one of the report is a model deployment report, how to think about choosing between serverless inference, managed deployment solutions, or leasing chips. And running inference yourself is an example kind of decision that big enterprises face, and it's hard to reason through, like this AI stuff is really new to everybody. And so we try and help with our reports and insight subscription. Companies navigate that. We also do custom private benchmarking. And so that's very different from the public benchmarking that we publicize, and there's no commercial model around that. For private benchmarking, we'll at times create benchmarks, run benchmarks to specs that enterprises want. And we'll also do that sometimes for AI companies who have built things, and we help them understand what they've built with private benchmarking. Yeah. So that's a piece mainly that we've developed through trying to support everybody publicly with our public benchmarks. Yeah.swyx [00:04:09]: Let's talk about TechStack behind that. But okay, I'm going to rewind all the way to when you guys started this project. You were all the way in Sydney? Yeah. Well, Sydney, Australia for me.Micah [00:04:19]: George was an SF, but he's Australian, but he moved here already. Yeah.swyx [00:04:22]: And I remember I had the Zoom call with you. What was the impetus for starting artificial analysis in the first place? You know, you started with public benchmarks. And so let's start there. We'll go to the private benchmark. Yeah.George [00:04:33]: Why don't we even go back a little bit to like why we, you know, thought that it was needed? Yeah.Micah [00:04:40]: The story kind of begins like in 2022, 2023, like both George and I have been into AI stuff for quite a while. In 2023 specifically, I was trying to build a legal AI research assistant. So it actually worked pretty well for its era, I would say. Yeah. Yeah. So I was finding that the more you go into building something using LLMs, the more each bit of what you're doing ends up being a benchmarking problem. So had like this multistage algorithm thing, trying to figure out what the minimum viable model for each bit was, trying to optimize every bit of it as you build that out, right? Like you're trying to think about accuracy, a bunch of other metrics and performance and cost. And mostly just no one was doing anything to independently evaluate all the models. And certainly not to look at the trade-offs for speed and cost. So we basically set out just to build a thing that developers could look at to see the trade-offs between all of those things measured independently across all the models and providers. Honestly, it was probably meant to be a side project when we first started doing it.swyx [00:05:49]: Like we didn't like get together and say like, Hey, like we're going to stop working on all this stuff. I'm like, this is going to be our main thing. When I first called you, I think you hadn't decided on starting a company yet.Micah [00:05:58]: That's actually true. I don't even think we'd pause like, like George had an acquittance job. I didn't quit working on my legal AI thing. Like it was genuinely a side project.George [00:06:05]: We built it because we needed it as people building in the space and thought, Oh, other people might find it useful too. So we'll buy domain and link it to the Vercel deployment that we had and tweet about it. And, but very quickly it started getting attention. Thank you, Swyx for, I think doing an initial retweet and spotlighting it there. This project that we released. And then very quickly though, it was useful to others, but very quickly it became more useful as the number of models released accelerated. We had Mixtrel 8x7B and it was a key. That's a fun one. Yeah. Like a open source model that really changed the landscape and opened up people's eyes to other serverless inference providers and thinking about speed, thinking about cost. And so that was a key. And so it became more useful quite quickly. Yeah.swyx [00:07:02]: What I love talking to people like you who sit across the ecosystem is, well, I have theories about what people want, but you have data and that's obviously more relevant. But I want to stay on the origin story a little bit more. When you started out, I would say, I think the status quo at the time was every paper would come out and they would report their numbers versus competitor numbers. And that's basically it. And I remember I did the legwork. I think everyone has some knowledge. I think there's some version of Excel sheet or a Google sheet where you just like copy and paste the numbers from every paper and just post it up there. And then sometimes they don't line up because they're independently run. And so your numbers are going to look better than... Your reproductions of other people's numbers are going to look worse because you don't hold their models correctly or whatever the excuse is. I think then Stanford Helm, Percy Liang's project would also have some of these numbers. And I don't know if there's any other source that you can cite. The way that if I were to start artificial analysis at the same time you guys started, I would have used the Luther AI's eval framework harness. Yup.Micah [00:08:06]: Yup. That was some cool stuff. At the end of the day, running these evals, it's like if it's a simple Q&A eval, all you're doing is asking a list of questions and checking if the answers are right, which shouldn't be that crazy. But it turns out there are an enormous number of things that you've got control for. And I mean, back when we started the website. Yeah. Yeah. Like one of the reasons why we realized that we had to run the evals ourselves and couldn't just take rules from the labs was just that they would all prompt the models differently. And when you're competing over a few points, then you can pretty easily get- You can put the answer into the model. Yeah. That in the extreme. And like you get crazy cases like back when I'm Googled a Gemini 1.0 Ultra and needed a number that would say it was better than GPT-4 and like constructed, I think never published like chain of thought examples. 32 of them in every topic in MLU to run it, to get the score, like there are so many things that you- They never shipped Ultra, right? That's the one that never made it up. Not widely. Yeah. Yeah. Yeah. I mean, I'm sure it existed, but yeah. So we were pretty sure that we needed to run them ourselves and just run them in the same way across all the models. Yeah. And we were, we also did certain from the start that you couldn't look at those in isolation. You needed to look at them alongside the cost and performance stuff. Yeah.swyx [00:09:24]: Okay. A couple of technical questions. I mean, so obviously I also thought about this and I didn't do it because of cost. Yep. Did you not worry about costs? Were you funded already? Clearly not, but you know. No. Well, we definitely weren't at the start.Micah [00:09:36]: So like, I mean, we're paying for it personally at the start. There's a lot of money. Well, the numbers weren't nearly as bad a couple of years ago. So we certainly incurred some costs, but we were probably in the order of like hundreds of dollars of spend across all the benchmarking that we were doing. Yeah. So nothing. Yeah. It was like kind of fine. Yeah. Yeah. These days that's gone up an enormous amount for a bunch of reasons that we can talk about. But yeah, it wasn't that bad because you can also remember that like the number of models we were dealing with was hardly any and the complexity of the stuff that we wanted to do to evaluate them was a lot less. Like we were just asking some Q&A type questions and then one specific thing was for a lot of evals initially, we were just like sampling an answer. You know, like, what's the answer for this? Like, we didn't want to go into the answer directly without letting the models think. We weren't even doing chain of thought stuff initially. And that was the most useful way to get some results initially. Yeah.swyx [00:10:33]: And so for people who haven't done this work, literally parsing the responses is a whole thing, right? Like because sometimes the models, the models can answer any way they feel fit and sometimes they actually do have the right answer, but they just returned the wrong format and they will get a zero for that unless you work it into your parser. And that involves more work. And so, I mean, but there's an open question whether you should give it points for not following your instructions on the format.Micah [00:11:00]: It depends what you're looking at, right? Because you can, if you're trying to see whether or not it can solve a particular type of reasoning problem, and you don't want to test it on its ability to do answer formatting at the same time, then you might want to use an LLM as answer extractor approach to make sure that you get the answer out no matter how unanswered. But these days, it's mostly less of a problem. Like, if you instruct a model and give it examples of what the answers should look like, it can get the answers in your format, and then you can do, like, a simple regex.swyx [00:11:28]: Yeah, yeah. And then there's other questions around, I guess, sometimes if you have a multiple choice question, sometimes there's a bias towards the first answer, so you have to randomize the responses. All these nuances, like, once you dig into benchmarks, you're like, I don't know how anyone believes the numbers on all these things. It's so dark magic.Micah [00:11:47]: You've also got, like… You've got, like, the different degrees of variance in different benchmarks, right? Yeah. So, if you run four-question multi-choice on a modern reasoning model at the temperatures suggested by the labs for their own models, the variance that you can see on a four-question multi-choice eval is pretty enormous if you only do a single run of it and it has a small number of questions, especially. So, like, one of the things that we do is run an enormous number of all of our evals when we're developing new ones and doing upgrades to our intelligence index to bring in new things. Yeah. So, that we can dial in the right number of repeats so that we can get to the 95% confidence intervals that we're comfortable with so that when we pull that together, we can be confident in intelligence index to at least as tight as, like, a plus or minus one at a 95% confidence. Yeah.swyx [00:12:32]: And, again, that just adds a straight multiple to the cost. Oh, yeah. Yeah, yeah.George [00:12:37]: So, that's one of many reasons that cost has gone up a lot more than linearly over the last couple of years. We report a cost to run the artificial analysis. We report a cost to run the artificial analysis intelligence index on our website, and currently that's assuming one repeat in terms of how we report it because we want to reflect a bit about the weighting of the index. But our cost is actually a lot higher than what we report there because of the repeats.swyx [00:13:03]: Yeah, yeah, yeah. And probably this is true, but just checking, you don't have any special deals with the labs. They don't discount it. You just pay out of pocket or out of your sort of customer funds. Oh, there is a mix. So, the issue is that sometimes they may give you a special end point, which is… Ah, 100%.Micah [00:13:21]: Yeah, yeah, yeah. Exactly. So, we laser focus, like, on everything we do on having the best independent metrics and making sure that no one can manipulate them in any way. There are quite a lot of processes we've developed over the last couple of years to make that true for, like, the one you bring up, like, right here of the fact that if we're working with a lab, if they're giving us a private endpoint to evaluate a model, that it is totally possible. That what's sitting behind that black box is not the same as they serve on a public endpoint. We're very aware of that. We have what we call a mystery shopper policy. And so, and we're totally transparent with all the labs we work with about this, that we will register accounts not on our own domain and run both intelligence evals and performance benchmarks… Yeah, that's the job. …without them being able to identify it. And no one's ever had a problem with that. Because, like, a thing that turns out to actually be quite a good… …good factor in the industry is that they all want to believe that none of their competitors could manipulate what we're doing either.swyx [00:14:23]: That's true. I never thought about that. I've been in the database data industry prior, and there's a lot of shenanigans around benchmarking, right? So I'm just kind of going through the mental laundry list. Did I miss anything else in this category of shenanigans? Oh, potential shenanigans.Micah [00:14:36]: I mean, okay, the biggest one, like, that I'll bring up, like, is more of a conceptual one, actually, than, like, direct shenanigans. It's that the things that get measured become things that get targeted by labs that they're trying to build, right? Exactly. So that doesn't mean anything that we should really call shenanigans. Like, I'm not talking about training on test set. But if you know that you're going to be great at another particular thing, if you're a researcher, there are a whole bunch of things that you can do to try to get better at that thing that preferably are going to be helpful for a wide range of how actual users want to use the thing that you're building. But will not necessarily work. Will not necessarily do that. So, for instance, the models are exceptional now at answering competition maths problems. There is some relevance of that type of reasoning, that type of work, to, like, how we might use modern coding agents and stuff. But it's clearly not one for one. So the thing that we have to be aware of is that once an eval becomes the thing that everyone's looking at, scores can get better on it without there being a reflection of overall generalized intelligence of these models. Getting better. That has been true for the last couple of years. It'll be true for the next couple of years. There's no silver bullet to defeat that other than building new stuff to stay relevant and measure the capabilities that matter most to real users. Yeah.swyx [00:15:58]: And we'll cover some of the new stuff that you guys are building as well, which is cool. Like, you used to just run other people's evals, but now you're coming up with your own. And I think, obviously, that is a necessary path once you're at the frontier. You've exhausted all the existing evals. I think the next point in history that I have for you is AI Grant that you guys decided to join and move here. What was it like? I think you were in, like, batch two? Batch four. Batch four. Okay.Micah [00:16:26]: I mean, it was great. Nat and Daniel are obviously great. And it's a really cool group of companies that we were in AI Grant alongside. It was really great to get Nat and Daniel on board. Obviously, they've done a whole lot of great work in the space with a lot of leading companies and were extremely aligned. With the mission of what we were trying to do. Like, we're not quite typical of, like, a lot of the other AI startups that they've invested in.swyx [00:16:53]: And they were very much here for the mission of what we want to do. Did they say any advice that really affected you in some way or, like, were one of the events very impactful? That's an interesting question.Micah [00:17:03]: I mean, I remember fondly a bunch of the speakers who came and did fireside chats at AI Grant.swyx [00:17:09]: Which is also, like, a crazy list. Yeah.George [00:17:11]: Oh, totally. Yeah, yeah, yeah. There was something about, you know, speaking to Nat and Daniel about the challenges of working through a startup and just working through the questions that don't have, like, clear answers and how to work through those kind of methodically and just, like, work through the hard decisions. And they've been great mentors to us as we've built artificial analysis. Another benefit for us was that other companies in the batch and other companies in AI Grant are pushing the capabilities. Yeah. And I think that's a big part of what AI can do at this time. And so being in contact with them, making sure that artificial analysis is useful to them has been fantastic for supporting us in working out how should we build out artificial analysis to continue to being useful to those, like, you know, building on AI.swyx [00:17:59]: I think to some extent, I'm mixed opinion on that one because to some extent, your target audience is not people in AI Grants who are obviously at the frontier. Yeah. Do you disagree?Micah [00:18:09]: To some extent. To some extent. But then, so a lot of what the AI Grant companies are doing is taking capabilities coming out of the labs and trying to push the limits of what they can do across the entire stack for building great applications, which actually makes some of them pretty archetypical power users of artificial analysis. Some of the people with the strongest opinions about what we're doing well and what we're not doing well and what they want to see next from us. Yeah. Yeah. Because when you're building any kind of AI application now, chances are you're using a whole bunch of different models. You're maybe switching reasonably frequently for different models and different parts of your application to optimize what you're able to do with them at an accuracy level and to get better speed and cost characteristics. So for many of them, no, they're like not commercial customers of ours, like we don't charge for all our data on the website. Yeah. They are absolutely some of our power users.swyx [00:19:07]: So let's talk about just the evals as well. So you start out from the general like MMU and GPQA stuff. What's next? How do you sort of build up to the overall index? What was in V1 and how did you evolve it? Okay.Micah [00:19:22]: So first, just like background, like we're talking about the artificial analysis intelligence index, which is our synthesis metric that we pulled together currently from 10 different eval data sets to give what? We're pretty much the same as that. Pretty confident is the best single number to look at for how smart the models are. Obviously, it doesn't tell the whole story. That's why we published the whole website of all the charts to dive into every part of it and look at the trade-offs. But best single number. So right now, it's got a bunch of Q&A type data sets that have been very important to the industry, like a couple that you just mentioned. It's also got a couple of agentic data sets. It's got our own long context reasoning data set and some other use case focused stuff. As time goes on. The things that we're most interested in that are going to be important to the capabilities that are becoming more important for AI, what developers are caring about, are going to be first around agentic capabilities. So surprise, surprise. We're all loving our coding agents and how the model is going to perform like that and then do similar things for different types of work are really important to us. The linking to use cases to economically valuable use cases are extremely important to us. And then we've got some of the. Yeah. These things that the models still struggle with, like working really well over long contexts that are not going to go away as specific capabilities and use cases that we need to keep evaluating.swyx [00:20:46]: But I guess one thing I was driving was like the V1 versus the V2 and how bad it was over time.Micah [00:20:53]: Like how we've changed the index to where we are.swyx [00:20:55]: And I think that reflects on the change in the industry. Right. So that's a nice way to tell that story.Micah [00:21:00]: Well, V1 would be completely saturated right now. Almost every model coming out because doing things like writing the Python functions and human evil is now pretty trivial. It's easy to forget, actually, I think how much progress has been made in the last two years. Like we obviously play the game constantly of like the today's version versus last week's version and the week before and all of the small changes in the horse race between the current frontier and who has the best like smaller than 10B model like right now this week. Right. And that's very important to a lot of developers and people and especially in this particular city of San Francisco. But when you zoom out a couple of years ago, literally most of what we were doing to evaluate the models then would all be 100% solved by even pretty small models today. And that's been one of the key things, by the way, that's driven down the cost of intelligence at every tier of intelligence. We can talk about more in a bit. So V1, V2, V3, we made things harder. We covered a wider range of use cases. And we tried to get closer to things developers care about as opposed to like just the Q&A type stuff that MMLU and GPQA represented. Yeah.swyx [00:22:12]: I don't know if you have anything to add there. Or we could just go right into showing people the benchmark and like looking around and asking questions about it. Yeah.Micah [00:22:21]: Let's do it. Okay. This would be a pretty good way to chat about a few of the new things we've launched recently. Yeah.George [00:22:26]: And I think a little bit about the direction that we want to take it. And we want to push benchmarks. Currently, the intelligence index and evals focus a lot on kind of raw intelligence. But we kind of want to diversify how we think about intelligence. And we can talk about it. But kind of new evals that we've kind of built and partnered on focus on topics like hallucination. And we've got a lot of topics that I think are not covered by the current eval set that should be. And so we want to bring that forth. But before we get into that.swyx [00:23:01]: And so for listeners, just as a timestamp, right now, number one is Gemini 3 Pro High. Then followed by Cloud Opus at 70. Just 5.1 high. You don't have 5.2 yet. And Kimi K2 Thinking. Wow. Still hanging in there. So those are the top four. That will date this podcast quickly. Yeah. Yeah. I mean, I love it. I love it. No, no. 100%. Look back this time next year and go, how cute. Yep.George [00:23:25]: Totally. A quick view of that is, okay, there's a lot. I love it. I love this chart. Yeah.Micah [00:23:30]: This is such a favorite, right? Yeah. And almost every talk that George or I give at conferences and stuff, we always put this one up first to just talk about situating where we are in this moment in history. This, I think, is the visual version of what I was saying before about the zooming out and remembering how much progress there's been. If we go back to just over a year ago, before 01, before Cloud Sonnet 3.5, we didn't have reasoning models or coding agents as a thing. And the game was very, very different. If we go back even a little bit before then, we're in the era where, when you look at this chart, open AI was untouchable for well over a year. And, I mean, you would remember that time period well of there being very open questions about whether or not AI was going to be competitive, like full stop, whether or not open AI would just run away with it, whether we would have a few frontier labs and no one else would really be able to do anything other than consume their APIs. I am quite happy overall that the world that we have ended up in is one where... Multi-model. Absolutely. And strictly more competitive every quarter over the last few years. Yeah. This year has been insane. Yeah.George [00:24:42]: You can see it. This chart with everything added is hard to read currently. There's so many dots on it, but I think it reflects a little bit what we felt, like how crazy it's been.swyx [00:24:54]: Why 14 as the default? Is that a manual choice? Because you've got service now in there that are less traditional names. Yeah.George [00:25:01]: It's models that we're kind of highlighting by default in our charts, in our intelligence index. Okay.swyx [00:25:07]: You just have a manually curated list of stuff.George [00:25:10]: Yeah, that's right. But something that I actually don't think every artificial analysis user knows is that you can customize our charts and choose what models are highlighted. Yeah. And so if we take off a few names, it gets a little easier to read.swyx [00:25:25]: Yeah, yeah. A little easier to read. Totally. Yeah. But I love that you can see the all one jump. Look at that. September 2024. And the DeepSeek jump. Yeah.George [00:25:34]: Which got close to OpenAI's leadership. They were so close. I think, yeah, we remember that moment. Around this time last year, actually.Micah [00:25:44]: Yeah, yeah, yeah. I agree. Yeah, well, a couple of weeks. It was Boxing Day in New Zealand when DeepSeek v3 came out. And we'd been tracking DeepSeek and a bunch of the other global players that were less known over the second half of 2024 and had run evals on the earlier ones and stuff. I very distinctly remember Boxing Day in New Zealand, because I was with family for Christmas and stuff, running the evals and getting back result by result on DeepSeek v3. So this was the first of their v3 architecture, the 671b MOE.Micah [00:26:19]: And we were very, very impressed. That was the moment where we were sure that DeepSeek was no longer just one of many players, but had jumped up to be a thing. The world really noticed when they followed that up with the RL working on top of v3 and R1 succeeding a few weeks later. But the groundwork for that absolutely was laid with just extremely strong base model, completely open weights that we had as the best open weights model. So, yeah, that's the thing that you really see in the game. But I think that we got a lot of good feedback on Boxing Day. us on Boxing Day last year.George [00:26:48]: Boxing Day is the day after Christmas for those not familiar.George [00:26:54]: I'm from Singapore.swyx [00:26:55]: A lot of us remember Boxing Day for a different reason, for the tsunami that happened. Oh, of course. Yeah, but that was a long time ago. So yeah. So this is the rough pitch of AAQI. Is it A-A-Q-I or A-A-I-I? I-I. Okay. Good memory, though.Micah [00:27:11]: I don't know. I'm not used to it. Once upon a time, we did call it Quality Index, and we would talk about quality, performance, and price, but we changed it to intelligence.George [00:27:20]: There's been a few naming changes. We added hardware benchmarking to the site, and so benchmarks at a kind of system level. And so then we changed our throughput metric to, we now call it output speed, and thenswyx [00:27:32]: throughput makes sense at a system level, so we took that name. Take me through more charts. What should people know? Obviously, the way you look at the site is probably different than how a beginner might look at it.Micah [00:27:42]: Yeah, that's fair. There's a lot of fun stuff to dive into. Maybe so we can hit past all the, like, we have lots and lots of emails and stuff. The interesting ones to talk about today that would be great to bring up are a few of our recent things, I think, that probably not many people will be familiar with yet. So first one of those is our omniscience index. So this one is a little bit different to most of the intelligence evils that we've run. We built it specifically to look at the embedded knowledge in the models and to test hallucination by looking at when the model doesn't know the answer, so not able to get it correct, what's its probability of saying, I don't know, or giving an incorrect answer. So the metric that we use for omniscience goes from negative 100 to positive 100. Because we're simply taking off a point if you give an incorrect answer to the question. We're pretty convinced that this is an example of where it makes most sense to do that, because it's strictly more helpful to say, I don't know, instead of giving a wrong answer to factual knowledge question. And one of our goals is to shift the incentive that evils create for models and the labs creating them to get higher scores. And almost every evil across all of AI up until this point, it's been graded by simple percentage correct as the main metric, the main thing that gets hyped. And so you should take a shot at everything. There's no incentive to say, I don't know. So we did that for this one here.swyx [00:29:22]: I think there's a general field of calibration as well, like the confidence in your answer versus the rightness of the answer. Yeah, we completely agree. Yeah. Yeah.George [00:29:31]: On that. And one reason that we didn't do that is because. Or put that into this index is that we think that the, the way to do that is not to ask the models how confident they are.swyx [00:29:43]: I don't know. Maybe it might be though. You put it like a JSON field, say, say confidence and maybe it spits out something. Yeah. You know, we have done a few evils podcasts over the, over the years. And when we did one with Clementine of hugging face, who maintains the open source leaderboard, and this was one of her top requests, which is some kind of hallucination slash lack of confidence calibration thing. And so, Hey, this is one of them.Micah [00:30:05]: And I mean, like anything that we do, it's not a perfect metric or the whole story of everything that you think about as hallucination. But yeah, it's pretty useful and has some interesting results. Like one of the things that we saw in the hallucination rate is that anthropics Claude models at the, the, the very left-hand side here with the lowest hallucination rates out of the models that we've evaluated amnesty is on. That is an interesting fact. I think it probably correlates with a lot of the previously, not really measured vibes stuff that people like about some of the Claude models. Is the dataset public or what's is it, is there a held out set? There's a hell of a set for this one. So we, we have published a public test set, but we we've only published 10% of it. The reason is that for this one here specifically, it would be very, very easy to like have data contamination because it is just factual knowledge questions. We would. We'll update it at a time to also prevent that, but with yeah, kept most of it held out so that we can keep it reliable for a long time. It leads us to a bunch of really cool things, including breakdown quite granularly by topic. And so we've got some of that disclosed on the website publicly right now, and there's lots more coming in terms of our ability to break out very specific topics. Yeah.swyx [00:31:23]: I would be interested. Let's, let's dwell a little bit on this hallucination one. I noticed that Haiku hallucinates less than Sonnet hallucinates less than Opus. And yeah. Would that be the other way around in a normal capability environments? I don't know. What's, what do you make of that?George [00:31:37]: One interesting aspect is that we've found that there's not really a, not a strong correlation between intelligence and hallucination, right? That's to say that the smarter the models are in a general sense, isn't correlated with their ability to, when they don't know something, say that they don't know. It's interesting that Gemini three pro preview was a big leap over here. Gemini 2.5. Flash and, and, and 2.5 pro, but, and if I add pro quickly here.swyx [00:32:07]: I bet pro's really good. Uh, actually no, I meant, I meant, uh, the GPT pros.George [00:32:12]: Oh yeah.swyx [00:32:13]: Cause GPT pros are rumored. We don't know for a fact that it's like eight runs and then with the LM judge on top. Yeah.George [00:32:20]: So we saw a big jump in, this is accuracy. So this is just percent that they get, uh, correct and Gemini three pro knew a lot more than the other models. And so big jump in accuracy. But relatively no change between the Google Gemini models, between releases. And the hallucination rate. Exactly. And so it's likely due to just kind of different post-training recipe, between the, the Claude models. Yeah.Micah [00:32:45]: Um, there's, there's driven this. Yeah. You can, uh, you can partially blame us and how we define intelligence having until now not defined hallucination as a negative in the way that we think about intelligence.swyx [00:32:56]: And so that's what we're changing. Uh, I know many smart people who are confidently incorrect.George [00:33:02]: Uh, look, look at that. That, that, that is very humans. Very true. And there's times and a place for that. I think our view is that hallucination rate makes sense in this context where it's around knowledge, but in many cases, people want the models to hallucinate, to have a go. Often that's the case in coding or when you're trying to generate newer ideas. One eval that we added to artificial analysis is, is, is critical point and it's really hard, uh, physics problems. Okay.swyx [00:33:32]: And is it sort of like a human eval type or something different or like a frontier math type?George [00:33:37]: It's not dissimilar to frontier frontier math. So these are kind of research questions that kind of academics in the physics physics world would be able to answer, but models really struggled to answer. So the top score here is not 9%.swyx [00:33:51]: And when the people that, that created this like Minway and, and, and actually off via who was kind of behind sweep and what organization is this? Oh, is this, it's Princeton.George [00:34:01]: Kind of range of academics from, from, uh, different academic institutions, really smart people. They talked about how they turn the models up in terms of the temperature as high temperature as they can, where they're trying to explore kind of new ideas in physics as a, as a thought partner, just because they, they want the models to hallucinate. Um, yeah, sometimes it's something new. Yeah, exactly.swyx [00:34:21]: Um, so not right in every situation, but, um, I think it makes sense, you know, to test hallucination in scenarios where it makes sense. Also, the obvious question is, uh, this is one of. Many that there is there, every lab has a system card that shows some kind of hallucination number, and you've chosen to not, uh, endorse that and you've made your own. And I think that's a, that's a choice. Um, totally in some sense, the rest of artificial analysis is public benchmarks that other people can independently rerun. You provide it as a service here. You have to fight the, well, who are we to, to like do this? And your, your answer is that we have a lot of customers and, you know, but like, I guess, how do you converge the individual?Micah [00:35:08]: I mean, I think, I think for hallucinations specifically, there are a bunch of different things that you might care about reasonably, and that you'd measure quite differently, like we've called this a amnesty and solutionation rate, not trying to declare the, like, it's humanity's last hallucination. You could, uh, you could have some interesting naming conventions and all this stuff. Um, the biggest picture answer to that. It's something that I actually wanted to mention. Just as George was explaining, critical point as well is, so as we go forward, we are building evals internally. We're partnering with academia and partnering with AI companies to build great evals. We have pretty strong views on, in various ways for different parts of the AI stack, where there are things that are not being measured well, or things that developers care about that should be measured more and better. And we intend to be doing that. We're not obsessed necessarily with that. Everything we do, we have to do entirely within our own team. Critical point. As a cool example of where we were a launch partner for it, working with academia, we've got some partnerships coming up with a couple of leading companies. Those ones, obviously we have to be careful with on some of the independent stuff, but with the right disclosure, like we're completely comfortable with that. A lot of the labs have released great data sets in the past that we've used to great success independently. And so it's between all of those techniques, we're going to be releasing more stuff in the future. Cool.swyx [00:36:26]: Let's cover the last couple. And then we'll, I want to talk about your trends analysis stuff, you know? Totally.Micah [00:36:31]: So that actually, I have one like little factoid on omniscience. If you go back up to accuracy on omniscience, an interesting thing about this accuracy metric is that it tracks more closely than anything else that we measure. The total parameter count of models makes a lot of sense intuitively, right? Because this is a knowledge eval. This is the pure knowledge metric. We're not looking at the index and the hallucination rate stuff that we think is much more about how the models are trained. This is just what facts did they recall? And yeah, it tracks parameter count extremely closely. Okay.swyx [00:37:05]: What's the rumored size of GPT-3 Pro? And to be clear, not confirmed for any official source, just rumors. But rumors do fly around. Rumors. I get, I hear all sorts of numbers. I don't know what to trust.Micah [00:37:17]: So if you, if you draw the line on omniscience accuracy versus total parameters, we've got all the open ways models, you can squint and see that likely the leading frontier models right now are quite a lot bigger than the ones that we're seeing right now. And the one trillion parameters that the open weights models cap out at, and the ones that we're looking at here, there's an interesting extra data point that Elon Musk revealed recently about XAI that for three trillion parameters for GROK 3 and 4, 6 trillion for GROK 5, but that's not out yet. Take those together, have a look. You might reasonably form a view that there's a pretty good chance that Gemini 3 Pro is bigger than that, that it could be in the 5 to 10 trillion parameters. To be clear, I have absolutely no idea, but just based on this chart, like that's where you would, you would land if you have a look at it. Yeah.swyx [00:38:07]: And to some extent, I actually kind of discourage people from guessing too much because what does it really matter? Like as long as they can serve it as a sustainable cost, that's about it. Like, yeah, totally.George [00:38:17]: They've also got different incentives in play compared to like open weights models who are thinking to supporting others in self-deployment for the labs who are doing inference at scale. It's I think less about total parameters in many cases. When thinking about inference costs and more around number of active parameters. And so there's a bit of an incentive towards larger sparser models. Agreed.Micah [00:38:38]: Understood. Yeah. Great. I mean, obviously if you're a developer or company using these things, not exactly as you say, it doesn't matter. You should be looking at all the different ways that we measure intelligence. You should be looking at cost to run index number and the different ways of thinking about token efficiency and cost efficiency based on the list prices, because that's all it matters.swyx [00:38:56]: It's not as good for the content creator rumor mill where I can say. Oh, GPT-4 is this small circle. Look at GPT-5 is this big circle. And then there used to be a thing for a while. Yeah.Micah [00:39:07]: But that is like on its own, actually a very interesting one, right? That is it just purely that chances are the last couple of years haven't seen a dramatic scaling up in the total size of these models. And so there's a lot of room to go up properly in total size of the models, especially with the upcoming hardware generations. Yes.swyx [00:39:29]: So, you know. Taking off my shitposting face for a minute. Yes. Yes. At the same time, I do feel like, you know, especially coming back from Europe, people do feel like Ilya is probably right that the paradigm is doesn't have many more orders of magnitude to scale out more. And therefore we need to start exploring at least a different path. GDPVal, I think it's like only like a month or so old. I was also very positive when it first came out. I actually talked to Tejo, who was the lead researcher on that. Oh, cool. And you have your own version.George [00:39:59]: It's a fantastic. It's a fantastic data set. Yeah.swyx [00:40:01]: And maybe it will recap for people who are still out of it. It's like 44 tasks based on some kind of GDP cutoff that's like meant to represent broad white collar work that is not just coding. Yeah.Micah [00:40:12]: Each of the tasks have a whole bunch of detailed instructions, some input files for a lot of them. It's within the 44 is divided into like two hundred and twenty two to five, maybe subtasks that are the level of that we run through the agenda. And yeah, they're really interesting. I will say that it doesn't. It doesn't necessarily capture like all the stuff that people do at work. No avail is perfect is always going to be more things to look at, largely because in order to make the tasks well enough to find that you can run them, they need to only have a handful of input files and very specific instructions for that task. And so I think the easiest way to think about them are that they're like quite hard take home exam tasks that you might do in an interview process.swyx [00:40:56]: Yeah, for listeners, it is not no longer like a long prompt. It is like, well, here's a zip file with like a spreadsheet or a PowerPoint deck or a PDF and go nuts and answer this question.George [00:41:06]: OpenAI released a great data set and they released a good paper which looks at performance across the different web chat bots on the data set. It's a great paper, encourage people to read it. What we've done is taken that data set and turned it into an eval that can be run on any model. So we created a reference agentic harness that can run. Run the models on the data set, and then we developed evaluator approach to compare outputs. That's kind of AI enabled, so it uses Gemini 3 Pro Preview to compare results, which we tested pretty comprehensively to ensure that it's aligned to human preferences. One data point there is that even as an evaluator, Gemini 3 Pro, interestingly, doesn't do actually that well. So that's kind of a good example of what we've done in GDPVal AA.swyx [00:42:01]: Yeah, the thing that you have to watch out for with LLM judge is self-preference that models usually prefer their own output, and in this case, it was not. Totally.Micah [00:42:08]: I think the way that we're thinking about the places where it makes sense to use an LLM as judge approach now, like quite different to some of the early LLM as judge stuff a couple of years ago, because some of that and MTV was a great project that was a good example of some of this a while ago was about judging conversations and like a lot of style type stuff. Here, we've got the task that the grader and grading model is doing is quite different to the task of taking the test. When you're taking the test, you've got all of the agentic tools you're working with, the code interpreter and web search, the file system to go through many, many turns to try to create the documents. Then on the other side, when we're grading it, we're running it through a pipeline to extract visual and text versions of the files and be able to provide that to Gemini, and we're providing the criteria for the task and getting it to pick which one more effectively meets the criteria of the task. Yeah. So we've got the task out of two potential outcomes. It turns out that we proved that it's just very, very good at getting that right, matched with human preference a lot of the time, because I think it's got the raw intelligence, but it's combined with the correct representation of the outputs, the fact that the outputs were created with an agentic task that is quite different to the way the grading model works, and we're comparing it against criteria, not just kind of zero shot trying to ask the model to pick which one is better.swyx [00:43:26]: Got it. Why is this an ELO? And not a percentage, like GDP-VAL?George [00:43:31]: So the outputs look like documents, and there's video outputs or audio outputs from some of the tasks. It has to make a video? Yeah, for some of the tasks. Some of the tasks.swyx [00:43:43]: What task is that?George [00:43:45]: I mean, it's in the data set. Like be a YouTuber? It's a marketing video.Micah [00:43:49]: Oh, wow. What? Like model has to go find clips on the internet and try to put it together. The models are not that good at doing that one, for now, to be clear. It's pretty hard to do that with a code editor. I mean, the computer stuff doesn't work quite well enough and so on and so on, but yeah.George [00:44:02]: And so there's no kind of ground truth, necessarily, to compare against, to work out percentage correct. It's hard to come up with correct or incorrect there. And so it's on a relative basis. And so we use an ELO approach to compare outputs from each of the models between the task.swyx [00:44:23]: You know what you should do? You should pay a contractor, a human, to do the same task. And then give it an ELO and then so you have, you have human there. It's just, I think what's helpful about GDPVal, the OpenAI one, is that 50% is meant to be normal human and maybe Domain Expert is higher than that, but 50% was the bar for like, well, if you've crossed 50, you are superhuman. Yeah.Micah [00:44:47]: So we like, haven't grounded this score in that exactly. I agree that it can be helpful, but we wanted to generalize this to a very large number. It's one of the reasons that presenting it as ELO is quite helpful and allows us to add models and it'll stay relevant for quite a long time. I also think it, it can be tricky looking at these exact tasks compared to the human performance, because the way that you would go about it as a human is quite different to how the models would go about it. Yeah.swyx [00:45:15]: I also liked that you included Lama 4 Maverick in there. Is that like just one last, like...Micah [00:45:20]: Well, no, no, no, no, no, no, it is the, it is the best model released by Meta. And... So it makes it into the homepage default set, still for now.George [00:45:31]: Other inclusion that's quite interesting is we also ran it across the latest versions of the web chatbots. And so we have...swyx [00:45:39]: Oh, that's right.George [00:45:40]: Oh, sorry.swyx [00:45:41]: I, yeah, I completely missed that. Okay.George [00:45:43]: No, not at all. So that, which has a checkered pattern. So that is their harness, not yours, is what you're saying. Exactly. And what's really interesting is that if you compare, for instance, Claude 4.5 Opus using the Claude web chatbot, it performs worse than the model in our agentic harness. And so in every case, the model performs better in our agentic harness than its web chatbot counterpart, the harness that they created.swyx [00:46:13]: Oh, my backwards explanation for that would be that, well, it's meant for consumer use cases and here you're pushing it for something.Micah [00:46:19]: The constraints are different and the amount of freedom that you can give the model is different. Also, you like have a cost goal. We let the models work as long as they want, basically. Yeah. Do you copy paste manually into the chatbot? Yeah. Yeah. That's, that was how we got the chatbot reference. We're not going to be keeping those updated at like quite the same scale as hundreds of models.swyx [00:46:38]: Well, so I don't know, talk to a browser base. They'll, they'll automate it for you. You know, like I have thought about like, well, we should turn these chatbot versions into an API because they are legitimately different agents in themselves. Yes. Right. Yeah.Micah [00:46:53]: And that's grown a huge amount of the last year, right? Like the tools. The tools that are available have actually diverged in my opinion, a fair bit across the major chatbot apps and the amount of data sources that you can connect them to have gone up a lot, meaning that your experience and the way you're using the model is more different than ever.swyx [00:47:10]: What tools and what data connections come to mind when you say what's interesting, what's notable work that people have done?Micah [00:47:15]: Oh, okay. So my favorite example on this is that until very recently, I would argue that it was basically impossible to get an LLM to draft an email for me in any useful way. Because most times that you're sending an email, you're not just writing something for the sake of writing it. Chances are context required is a whole bunch of historical emails. Maybe it's notes that you've made, maybe it's meeting notes, maybe it's, um, pulling something from your, um, any of like wherever you at work store stuff. So for me, like Google drive, one drive, um, in our super base databases, if we need to do some analysis or some data or something, preferably model can be plugged into all of those things and can go do some useful work based on it. The things that like I find most impressive currently that I am somewhat surprised work really well in late 2025, uh, that I can have models use super base MCP to query read only, of course, run a whole bunch of SQL queries to do pretty significant data analysis. And. And make charts and stuff and can read my Gmail and my notion. And okay. You actually use that. That's good. That's, that's, that's good. Is that a cloud thing? To various degrees of order, but chat GPD and Claude right now, I would say that this stuff like barely works in fairness right now. Like.George [00:48:33]: Because people are actually going to try this after they hear it. If you get an email from Micah, odds are it wasn't written by a chatbot.Micah [00:48:38]: So, yeah, I think it is true that I have never actually sent anyone an email drafted by a chatbot. Yet.swyx [00:48:46]: Um, and so you can, you can feel it right. And yeah, this time, this time next year, we'll come back and see where it's going. Totally. Um, super base shout out another famous Kiwi. Uh, I don't know if you've, you've any conversations with him about anything in particular on AI building and AI infra.George [00:49:03]: We have had, uh, Twitter DMS, um, with, with him because we're quite big, uh, super base users and power users. And we probably do some things more manually than we should in. In, in super base support line because you're, you're a little bit being super friendly. One extra, um, point regarding, um, GDP Val AA is that on the basis of the overperformance of the models compared to the chatbots turns out, we realized that, oh, like our reference harness that we built actually white works quite well on like gen generalist agentic tasks. This proves it in a sense. And so the agent harness is very. Minimalist. I think it follows some of the ideas that are in Claude code and we, all that we give it is context management capabilities, a web search, web browsing, uh, tool, uh, code execution, uh, environment. Anything else?Micah [00:50:02]: I mean, we can equip it with more tools, but like by default, yeah, that's it. We, we, we give it for GDP, a tool to, uh, view an image specifically, um, because the models, you know, can just use a terminal to pull stuff in text form into context. But to pull visual stuff into context, we had to give them a custom tool, but yeah, exactly. Um, you, you can explain an expert. No.George [00:50:21]: So it's, it, we turned out that we created a good generalist agentic harness. And so we, um, released that on, on GitHub yesterday. It's called stirrup. So if people want to check it out and, and it's a great, um, you know, base for, you know, generalist, uh, building a generalist agent for more specific tasks.Micah [00:50:39]: I'd say the best way to use it is get clone and then have your favorite coding. Agent make changes to it, to do whatever you want, because it's not that many lines of code and the coding agents can work with it. Super well.swyx [00:50:51]: Well, that's nice for the community to explore and share and hack on it. I think maybe in, in, in other similar environments, the terminal bench guys have done, uh, sort of the Harbor. Uh, and so it's, it's a, it's a bundle of, well, we need our minimal harness, which for them is terminus and we also need the RL environments or Docker deployment thing to, to run independently. So I don't know if you've looked at it. I don't know if you've looked at the harbor at all, is that, is that like a, a standard that people want to adopt?George [00:51:19]: Yeah, we've looked at it from a evals perspective and we love terminal bench and, and host benchmarks of, of, of terminal mention on artificial analysis. Um, we've looked at it from a, from a coding agent perspective, but could see it being a great, um, basis for any kind of agents. I think where we're getting to is that these models have gotten smart enough. They've gotten better, better tools that they can perform better when just given a minimalist. Set of tools and, and let them run, let the model control the, the agentic workflow rather than using another framework that's a bit more built out that tries to dictate the, dictate the flow. Awesome.swyx [00:51:56]: Let's cover the openness index and then let's go into the report stuff. Uh, so that's the, that's the last of the proprietary art numbers, I guess. I don't know how you sort of classify all these. Yeah.Micah [00:52:07]: Or call it, call it, let's call it the last of like the, the three new things that we're talking about from like the last few weeks. Um, cause I mean, there's a, we do a mix of stuff that. Where we're using open source, where we open source and what we do and, um, proprietary stuff that we don't always open source, like long context reasoning data set last year, we did open source. Um, and then all of the work on performance benchmarks across the site, some of them, we looking to open source, but some of them, like we're constantly iterating on and so on and so on and so on. So there's a huge mix, I would say, just of like stuff that is open source and not across the side. So that's a LCR for people. Yeah, yeah, yeah, yeah.swyx [00:52:41]: Uh, but let's, let's, let's talk about open.Micah [00:52:42]: Let's talk about openness index. This. Here is call it like a new way to think about how open models are. We, for a long time, have tracked where the models are open weights and what the licenses on them are. And that's like pretty useful. That tells you what you're allowed to do with the weights of a model, but there is this whole other dimension to how open models are. That is pretty important that we haven't tracked until now. And that's how much is disclosed about how it was made. So transparency about data, pre-training data and post-training data. And whether you're allowed to use that data and transparency about methodology and training code. So basically, those are the components. We bring them together to score an openness index for models so that you can in one place get this full picture of how open models are.swyx [00:53:32]: I feel like I've seen a couple other people try to do this, but they're not maintained. I do think this does matter. I don't know what the numbers mean apart from is there a max number? Is this out of 20?George [00:53:44]: It's out of 18 currently, and so we've got an openness index page, but essentially these are points, you get points for being more open across these different categories and the maximum you can achieve is 18. So AI2 with their extremely open OMO3 32B think model is the leader in a sense.swyx [00:54:04]: It's hooking face.George [00:54:05]: Oh, with their smaller model. It's coming soon. I think we need to run, we need to get the intelligence benchmarks right to get it on the site.swyx [00:54:12]: You can't have it open in the next. We can not include hooking face. We love hooking face. We'll have that, we'll have that up very soon. I mean, you know, the refined web and all that stuff. It's, it's amazing. Or is it called fine web? Fine web. Fine web.Micah [00:54:23]: Yeah, yeah, no, totally. Yep. One of the reasons this is cool, right, is that if you're trying to understand the holistic picture of the models and what you can do with all the stuff the company's contributing, this gives you that picture. And so we are going to keep it up to date alongside all the models that we do intelligence index on, on the site. And it's just an extra view to understand.swyx [00:54:43]: Can you scroll down to this? The, the, the, the trade-offs chart. Yeah, yeah. That one. Yeah. This, this really matters, right? Obviously, because you can b

Join host Justin Forman with Mark Grunden and Josh Seabaugh for a pivotal conversation about the unprecedented opportunity emerging at the intersection of church and entrepreneurship. Recorded during Faith Driven Entrepreneur's staff retreat in Charleston, this episode unpacks groundbreaking Barna research revealing that society trusts entrepreneurs twice as much as pastors—and why this isn't a threat, but rather the church's greatest partnership opportunity.Mark brings unique insight from seven years at Saddleback Church pioneering marketplace ministry, while Josh shares lessons from a decade as a campus pastor before joining FDE full-time. Together, they reveal why starting with entrepreneurs—rather than broad "faith and work" initiatives—creates sustainable momentum that cascades throughout entire congregations and communities.Key Topics:Barna research reveals entrepreneurs are trusted 2X more than pastors (and 9X more than politicians)Why starting with "everyone who works" causes entrepreneurs to leave the roomThe difference between convening for community vs. convening for missionBreaking free from the "parking jacket and coffee" trap for high-capacity leadersWhy churches need entrepreneurs more than entrepreneurs need the churchHow 250 churches are becoming hubs for faith-driven entrepreneurs in their citiesThe simple 8-week pathway any church can start this week (no cost, no catch)Notable Quotes:"Entrepreneurs are trusted two times more than pastors. I don't know if the influence of pastors is actually waning, but I think it's more that the impact of entrepreneurs are actually increasing because people are tired of talk in our society. They're looking for people of action." - Mark Grunden"If you get a pastor alone, he's intimidated by the entrepreneur. If you get an entrepreneur alone, he's intimidating by the pastor, which is why I'm excited that we can be the bridge." - Josh Seabaugh"If you start with everybody, you'll never get the entrepreneur. But if you start with the entrepreneur, everybody will follow." - Mark Grunden

Want to get away from the crowds? Want a high mountain lake or stream all to yourself?  The best way to do this is to take a backpacking trip, but you need to prepare more than you would for a car trip or a trip to a lodge. What exactly should you take and what should you leave behind?  What kinds of flies and accessories should you bring? How can you save weight and still have enough gear for a fun fishing trip? Derek Bargaehr [37:36], an experienced fly fisher and backpacker, gives us tips on how to make the most of your next backpacking trip. In the Fly Box this week, we have some questions. A couple of which could only be answered by my co-workers at Orvis so we have responses from both Pete Kutzer, our casting guru and Shawn Brillon, our bamboo rod craftsman. How can I easily estimate how much backing is on my unlabeled reels? A listener relates how some podcast advice on emergers helped him and his son have a successful trip I took a lesson on two-handed casting and it was all done on grass.  Was this wrong? What advice do you have on cleaning the ferrules on bamboo fly rods? Are Orvis bamboo fly rods impregnated? On a tarpon trip, the fish were in deep water so I used a sinking poly leader on my floating line.  Should I have used a full-sinking fly line instead? Is the Albright knot a better knot than the nail knot for attaching a leader to a fly line or backing to a fly line? When connecting pieces of tippet I will normally go up two X sizes, like from 2X to 4X.  Is this wrong? Is it OK to clear a casting lane on a trout stream? What can I do to find bigger trout during the dog days of summer?

In this episode, Tony and Marianna break down the commonly misunderstood condition known as 'skinny fat,' where individuals have low muscle mass and relatively high body fat despite appearing thin. They provide a clear, actionable five-step plan to address and fix this issue. The steps include prioritizing strength training with compound lifts, optimizing diet with high protein and appropriate calorie intake, incorporating strategic cardio routines, improving lifestyle factors like sleep and stress management, and tracking progress with patience. They emphasize the need for consistency and the importance of adjusting goals as one's body changes.⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Sign up for Fitness Stuff PREMIUM here!!⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ALL of our complete 12-week training programsBonus episodes every FridayJust $5 /month⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Legion Athletics⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠BOGO 50% off for your first order + 2X points on every order after thatuse code “FSPOD” at checkoutCalorie + Protein CalculatorsTimestamps:(02:56) What is “Skinnyfat”(09:00) What causes Skinnyfat(14:41) How to fix Skinnyfat

Hey there! I'm Kate from Hello Funnels, and welcome to Part 4—the final episode—of our End of Year Planning Series.If you haven't listened to Parts 1-3 yet, go back and do those first. This exercise builds on everything we've already covered.Today's episode might make you uncomfortable. And honestly, that's kind of the point.I'm walking you through a challenge that's going to stretch you and show you what's actually possible in 2026—even if it feels impossible right now.It's called the 10X Exercise. And it's designed to help you think bigger, notice your resistance, and consider strategies you never would have thought of otherwise.Because here's the truth: when we set achievable-feeling goals, we give ourselves achievable-feeling tasks. But if we want quantum-leap growth, we need to think bigger.And even if you don't hit the 10X, you might still 2X your results. And who doesn't want that?Want help building the plan and the systems to make this happen? DM us @hellofunnels on Instagram. We'd love to support you inside the 100K Club.Thanks for following along with this series. Now go do the work—and let's make 2026 incredible.

315 | Jess Lytle (Head of Marketing at Exit Five) hosts a live roundtable with Morgan Cole (VP of Demand Gen at Red Canary), Lisa Cole (CMO at 2X), and Jean Cameron (Sr. Director of Field & Partner Marketing at Demandbase) on how B2B teams are using AI to drive pipeline and revenue. They share real examples of how marketers are identifying in-market buyers earlier, moving deals faster, replacing outdated lead scoring, and keeping marketing, sales, and ops aligned around revenue. The conversation goes deep on intent signals, buying groups, predictive analytics, brand vs demand, and what's changing in the new era of pipeline accountability. Timestamps(00:00) - AI hype vs real revenue impact (06:16) - Panel intros and GTM perspectives (08:46) - The real pipeline problem: growth without more headcount (11:16) - How teams use AI to identify in-market buyers earlier (16:46) - Buying groups, not leads: why account signals matter (20:46) - Predictive analytics, pipeline forecasting, and deal analysis (27:36) - Why traditional lead scoring is breaking (37:28) - How teams “swarm” accounts with marketing + sales (43:48) - Brand and demand together: building future pipeline Join 50,0000 people who get our Exit Five Newsletter here: https://www.exitfive.com/newsletterLearn more about Exit Five's private marketing community: https://www.exitfive.com/***Today's episode is brought to you by Knak.Email (in my humble opinion) is the still the greatest marketing channel of all-time.It's the only way you can truly “own” your audience.But when it comes to building the emails - if you've ever tried building an email in an enterprise marketing automation platform, you know how painful it can be. Templates are too rigid, editing code can break things and the whole process just takes forever. That's why we love Knak here at Exit Five. Knak a no-code email platform that makes it easy to create on-brand, high-performing emails - without the bottlenecks.Frustrated by clunky email builders? You need Knak.Tired of ‘hoping' the email you sent looks good across all devices? Just test in Knak first.Big team making it hard to collaborate and get approvals? Definitely Knak.And the best part? Everything takes a fraction of the time.See Knak in action at knak.com/exit-five. Or just let them know you heard about Knak on Exit Five.***Thanks to my friends at hatch.fm for producing this episode and handling all of the Exit Five podcast production.They give you unlimited podcast editing and strategy for your B2B podcast.Get unlimited podcast editing and on-demand strategy for one low monthly cost. Just upload your episode, and they take care of the rest.Visit hatch.fm to learn more

After nearly 200,000 cold calls and a million auto-dialer calls, Stephen Oommen discovered something shocking: 98% of his revenue came from warm referrals. Today, he breaks down how sellers can turn relationships into predictable growth. In this episode, host Lyndsay Dowd sits down with Stephen Oommen, a 25-year go-to-market veteran, speaker, and author of the upcoming book The Referral Effect. Stephen shares why nearly 98% of his business revenue came from warm referrals, despite making hundreds of thousands of cold calls throughout his career. Stephen opens up about growing up as the child of immigrants in Oklahoma, navigating an identity crisis that ultimately became his superpower—the Chameleon Effect—his ability to adapt, connect, and create trust across any environment. That skill later became the foundation for his referral-based sales methodology. You'll learn: - Why executives don't respond to cold outreach—and what they do respond to - How to close the trust gap by scaling warm referrals - The "Magic Networking Question" that instantly upgrades your network - The 99 and 1 Principle for managing energy in sales and relationships - How leaders can balance intensity, kindness, and long-term legacy If you're a B2B seller, founder, GTM leader, or executive tired of low-yield outreach, this conversation will challenge how you think about networking, sales culture, and growth.

    Timestamps
 00:00 – Introduction: Stephen Oommen, the Truth Teller.
 02:22 – Stephen's Origin Story: From Bankruptcy to Corporate Success.
 04:48 – The Chameleon Effect: Turning Identity Crisis into a Superpower.
 10:39 – Cold Calls vs. Warm Referrals: The Efficiency vs. Effectiveness Debate.
16:54 – How to Start Networking: Nurturing and Activating Relationships.
 19:16 – The Live Exercise: Asking the Right Questions to Build a Network.
 22:50 – Using Qualifiers: Geography, Industry, and Title.
 26:08 – The 99 and 1 Principle: Managing Energy in Sales.
 30:04 – What Inspires Stephen: Growth, Contribution, and Laughter.
 32:38 – Legacy: Kindness Character vs. Intense Personality.
 35:00 – What's Next: Speaking Tours and The Referral Effect.

    About the Guest Stephen Oommen is a 25-year go-to-market veteran with experience spanning frontline sales to executive leadership. He has worked with startups and global enterprises including Microsoft, ADP, and Citibank. Stephen is the only speaker and trainer dedicated to helping B2B sellers solve the biggest challenge in modern sales: lack of access to decision makers. His work focuses on closing the trust gap by scaling the most successful method known—warm referrals. A successful entrepreneur and W2 employee ("entreployee"), Stephen has retired from corporate twice, paid off hundreds of thousands in non-mortgage debt, and is currently writing his book The Referral Effect. He believes legacy is built at the intersection of kindness, generosity, and laughter.  Connect with Stephen LinkedIn: https://www.linkedin.com/in/stephenoommen/

    About the Host – Lyndsay Dowd is a Speaker, Founder, Author, Coach, Podcast Host—and unapologetic Disruptor. With 30 years of leadership experience, including 23 at IBM, she's built and led high-performing teams that consistently delivered results. She also served as a Guest Lecturer at Harvard University, sharing her insights on modern leadership and culture transformation. 

 As the founder of Heartbeat for Hire, Lyndsay helps companies ditch toxic leadership and build irresistible cultures that drive performance, retention, and impact. She's been featured in Fortune Magazine, HR.com, ABC, NBC, FOX, CBS, and over 100 podcasts. 

   Lyndsay is a two-time best selling author of Top Down Culture and Voices of Women, and the host of the globally ranked and 2X awarded Heartbeat for Hire podcast—sitting in the top 2.5% worldwide. She is also the host of a weekly live show called THE LEADERSHIP LOUNGE. Lyndsay is a frequent speaker, moderator, and guest, known for her candor, humor, and ability to spark action.
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 If you are looking for an amazing gift or a way to treat yourself, Go to https://cozyearth.com/ and use the code LEADWITHHEART and get 41% off. It's the deepest discount you will find anywhere and I get commission too! This brand has been on Oprah's Favorite Things 9 times!! Happy Shopping! 
   
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   #B2BSales #SalesStrategy #WarmReferrals #ColdCalling #SalesLeadership #GTM #Networking #RelationshipSelling #SalesPodcast #TheReferralEffect

RaysUp Off Season subtraction is actually a strong positive More Christmas presents to come3-Way Trade with Pittsburgh  Brandon Lowe to Pirates – currently contract at $11.5 million contractJake Mangum & Chandler Simpson – similar players – Mason Montgomery – left handed starter and/or lethal closer like Aroldis ChapmanMike Burrows & Houston AstrosJacob Melton to the Rays – Kevin Kiermaier'ish outfield performance plus some hitting strengthAnderson Brito – one of the talents when you can see the ceiling of being a number 1Rays building a strong rotation at A+ level Shane Baz example - jumping from A to AA to Majors  - skipping AAA altogether21-year old Brito will be coming up with Santiago Suarez. Trevor Harrison, Jose Urbina, and Andres GolanHis fielder independent, , he had one of 2.91 and Santiago. Suarez, who's been consistently in the top 10, uh, prospects for the Rays is at 2.97Brito was an immediate improvement – to the RaysRays got more from the Shane Baz deal than they did with the Chris Archer dealFuture with prospects versus playoffs this yearLethal rotation with Drew Rasmussen. Ryan Pepiot. Shane McClanahan. Steven Mattson. Joe Boyle. What would Rays do if Shane McClanahan goes down  – Rays could bring in  Ian Seymour, Joe Rock, &  Osvaldo BidoYoendrys Gomez – relief/starting pitcher comes in from the White SoxShane Baz's potential to become an ace pitcher versus potential health issuesCatcher of the future for the Rays – Ketel Marte 2 tiers above Brandon LoweBrandon DonovanCardinals, Chaim Bloom's very familiar with Taylor WallsJadher Areinamo2nd base is solveableCedric Mullins is sliding into that Manuel Margot role – stronger Right Field?Where does Josh Lowe wind upShane Baz traded placesMichael Forret – what will he add to pitching depthCatcher, Caden Bodine – significant hit toolSlater de Brun compared to Corbin Carroll & musical talentAustin Overn like Colton Ledbetter with 2X the speedIncreasing the pressure in the Rays affiliate programCompensation pick –  essentially adding a first round pick for the RaysShane Baz trade =  Zach Eflin & four other prospectsHow much have the Rays cleared up in salaries Brandon Lowe - $11.5 million, Shane Baz - $3.5 million plusKetel Marte is currently making $12.5 millionCould Richie Palacios split time with Taylor WallsJonny DeLuca, Taylor Walls & Josh Lowe are still on the roster todayThe 3-way trade & Ryan Pepiot's arm with the D-backsFuture show on the web of the Rays impact across several MLB Front OfficesThe Chicago White Rays – Duncan David, Curtis Mead, Ben Peoples, Alexander Alberto, Everson Pereira, Mike VasilMets move Jeff McNeil to Athletics'Will Mets pick up Kyle Tucker or Cody BellingerWould like to see Eugenio Suarez to MarlinsThe Cardinals, Curt Flood, the Reserve Clause & the fight for Free AgencyCurt Flood's letter to Baseball Commissioner, Bowie KunPeople are still talking $400 million for Kyle Tucker, they're still talking, 300 million for Bo Bichette.Ketel Marte to the Rays would be a great Christmas Happy Festivus to the Rest of UsFind Mat at @matgermain.bsky.social or reach Mark @  baseballbizondeck@gmail.com BaseballBiz on Deck, @ iHeart Apple, Spotify, Amazon Music, & at www.baseballbizOnDeck.com Special Thanks to XTaKe-R-U-X for the music Rocking Forward

Today on Fitness Stuff for Normal People, Marianna and Tony break down why goal setting works for some people and consistently fails for others. If you have ever felt frustrated, inconsistent, or unsure why your effort is not matching your results, you are not alone. This episode dives into the psychology behind effective goal setting, the most common reasons people fall short, and how clearer, more intentional goals change behavior. The conversation offers a practical framework for setting goals that are realistic, motivating, and aligned with real life.⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Sign up for Fitness Stuff PREMIUM here!!⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ALL of our complete 12-week training programsBonus episodes every FridayJust $5 /month⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Legion Athletics⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠BOGO 50% off for your first order + 2X points on every order after thatuse code “FSPOD” at checkoutTimestamps:(5:57) Goal Setting Theory
(15:35) How to Actually Set and Achieve Your Goals
(19:19) 5 Steps to Set Your Goal and Plan
(19:28) Step 1: Set Desired Outcome(24:24) Step 2: Decompose the Goal Into Micro-Processes
(26:54) Step 3: Decide What to Measure(31:37) Step 4: Feedback and Adaptability
(35:15) Step 5: Accountability Systems
(42:49) Why Most People Fail

What if the solution to feeding the world isn't on land—but in the ocean? Today, we're diving into the future of food with James Beard and Emmy-nominated storyteller Jennifer Bushman. In this episode of The Heartbeat for Hire, we dive into the deep blue with Jennifer Bushman, a James Beard Award–nominated chef, Emmy-nominated producer, and co-founder of Fed by Blue. Jennifer shares her journey from growing up in a cattle-ranching family in Colorado to becoming one of the world's leading advocates for sustainable aquaculture, ocean health, and blue foods. We explore her groundbreaking PBS docuseries Hope in the Water, the innovators restoring our oceans, and why the future of food depends on what comes from water—not land. Jennifer debunks common myths around farmed vs. wild seafood, explains how seaweed farming can regenerate ecosystems, and reveals why storytelling—not fear—is the key to environmental leadership and lasting change. From shrimp farms in Minnesota dairy barns to kelp used in skincare and ice cream, this conversation offers a hopeful, practical vision for feeding a growing world while healing our oceans.

    Timestamps
 00:00 – Intro: Why Seaweed is the Vegetable of the Future
 00:44 – Welcome: Meet Jennifer Bushman
 01:51 – Jennifer's Origin Story: From Cattle Ranching to Ocean Advocacy
 03:50 – Feeding the World: Reliance on Blue Foods
 05:15 – Seaweed: It's More Than Just Sushi (Skincare, Toothpaste, & Ice Cream)
 07:05 – Fed by Blue and the Hope in the Water Docuseries
 09:00 – The Power of Celebrity Advocates: David E. Kelly & Martha Stewart
11:35 – Breaking the Stigma: The Truth About Farm-Raised Seafood
 14:10 – Innovation Spotlight: Farming Shrimp in Minnesota Dairy Barns
 16:45 – Leadership Lesson: Using Storytelling to mobilize funding and action
22:15 – Finding Inspiration and Defining Legacy
 24:58 – What's Next & The Blue Food Cookbook

    About the Guest Jennifer Bushman is an award-winning chef, cookbook author, consultant, and storyteller working at the intersection of food, sustainability, and ocean health. A multiple James Beard Award nominee and Emmy nominee, Jennifer is the co-founder of Fed by Blue, a nonprofit dedicated to advancing sustainable blue foods and aquaculture. She is also the creator and producer of the PBS docuseries Hope in the Water, spotlighting the water farmers, fishers, and scientists driving real solutions to restore our oceans and feed the world. Jennifer serves on the Board of Directors of The Marine Mammal Center and believes innovation, education, and hope are essential to solving the ocean crisis.  Website: www.jenniferbushman.com
  LinkedIn: https://www.linkedin.com/in/jennifer-bushman-86782212/
  Instagram: https://www.instagram.com/jen_bushman

    About the Host – Lyndsay Dowd is a Speaker, Founder, Author, Coach, Podcast Host—and unapologetic Disruptor. With 30 years of leadership experience, including 23 at IBM, she's built and led high-performing teams that consistently delivered results. She also served as a Guest Lecturer at Harvard University, sharing her insights on modern leadership and culture transformation. 

 As the founder of Heartbeat for Hire, Lyndsay helps companies ditch toxic leadership and build irresistible cultures that drive performance, retention, and impact. She's been featured in Fortune Magazine, HR.com, ABC, NBC, FOX, CBS, and over 100 podcasts. 

   Lyndsay is a two-time best selling author of Top Down Culture and Voices of Women, and the host of the globally ranked and 2X awarded Heartbeat for Hire podcast—sitting in the top 2.5% worldwide. She is also the host of a weekly live show called THE LEADERSHIP LOUNGE. Lyndsay is a frequent speaker, moderator, and guest, known for her candor, humor, and ability to spark action.
    Official Brand Partner: https://MyDeals.Page/19c3 
 To my loyal listeners - I love luxury and I love a great deal. 
 If you are looking for an amazing gift or a way to treat yourself, Go to https://cozyearth.com/ and use the code LEADWITHHEART and get 41% off. It's the deepest discount you will find anywhere and I get commission too! This brand has been on Oprah's Favorite Things 9 times!! Happy Shopping! 

    Connect with Lyndsay Dowd:  Website: https://heartbeatforhire.com
  LinkedIn: https://www.linkedin.com/in/lyndsaydowdh4h/ 
  Instagram: https://www.instagram.com/lyndsaydowdh4h/ 
  Facebook: https://www.facebook.com/LyndsayDowdH4H
  Tiktok: https://www.tiktok.com/@lyndsaydowdh4h

   #JenniferBushman #FedByBlue #BlueFoods #FutureOfFood #SustainableSeafood #OceanHealth #Aquaculture #FoodSystems #EnvironmentalLeadership #HopeInTheWater #SustainableEating #ClimateSolutions

When's the last time you replayed your old episodes and really listened? It's the end of another year of podcasting, and that means looking back on how far you've come and planning the next steps. Whether you're taking some time off for the holiday or plugging away between the eggnog and the family time, Mary has one non-negotiable for you: you need to start listening back to your old episodes—and not just at 2X speed. For a medium that celebrates the voice, podcasters are way too lax about auditing their primary instrument. Yes, it's awkward, and chances are you'll sound weird to yourself. You might even get a hint of that imposter syndrome you thought you quashed. But trust Mary: give yourself the gift of perspective and growth this year by running some personal airchecks. It really does get easier the more you do it, and you'll unlock so much potential for your show in 2026 and beyond. Put aside the mic and queue up some past episodes. Discover: How focusing on feelings helps you develop a discerning ear; Efficiency hacks for reducing the cringe factor of listening to your own voice; Reflection questions to consider as you review old episodes. Links worth mentioning from the episode: Try Smitten Kitchen's Brownie Roll-Out Cookies: https://smittenkitchen.com/2008/04/brownie-roll-out-cookies/  Listen to Episode 15, Identifying Your Audience for Podcast Growth: https://www.organizedsound.ca/identifying-your-audience-for-podcast-growth-episode-15/  Listen to Episode 50, Stop Thinking About Yourself: https://www.organizedsound.ca/stop-thinking-about-yourself-episode-50/ Listen to Episode 105, How to Keep Fear From Overpowering Your Voice with Kat Stewart and Kevin Ribble: https://www.organizedsound.ca/how-to-keep-fear-from-overpowering-your-voice-with-kat-stewart-and-kevin-ribble-episode-102/ Connect with Mary! Leave a voice note with your feedback at https://www.speakpipe.com/VisibleVoice or email visiblevoicepodcast@gmail.com Get the full transcript of the episode at http://www.visiblevoicepodcast.com Read up on more secrets with the Visible Voice Insights Newsletter https://www.organizedsound.ca/newsletter To learn more or work with Mary, check out https://www.organizedsound.ca Link up on LinkedIn https://www.linkedin.com/in/marychan-organizedsound/ Engage on Instagram @OrganizedSoundProductions https://www.instagram.com/organizedsoundproductions Show Credits: Podcast audio design, engineering, and editing by Mary Chan of Organized Sound Productions Show notes written by Shannon Kirk of Right Words Studio Post-production support by Kristalee Forre of Forre You VA Podcast cover art by Emily Johnston of Artio Design Co.

Micro Dose Monday is back for Fitness Stuff for Normal People with Marianna and Tony, and we're so glad you're here. This episode covers four listener requested topics, including the real science behind glyphosate in food, a new diabetes and fat loss pill that targets muscle instead of appetite, why daily low dose Cialis is being studied as a longevity tool, and a major shredded cheese recall and what it actually means for you. It's fast paced, evidence based, and designed to give you clarity without the fear or hype. Thanks for listening, being part of this community, and kicking off your week with us.⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Sign up for Fitness Stuff PREMIUM here!!⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ALL of our complete 12-week training programsBonus episodes every FridayJust $5 /month⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Legion Athletics⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠BOGO 50% off for your first order + 2X points on every order after thatuse code “FSPOD” at checkoutTimestamps:(3:58) Glyphosate and Monsanto(17:10) New fat burning pill that protects muscle and appetite(28:30) Daily low dose Cialis as a new health protocol(36:12) Food recalls

Attention: Full service, creative, marketing agency owners. The number #1 reason you started the agency: 1) Freedom That's how simple it is. You want to grow your agency while working less in the business, right? We help you transform from the hustler/doer to the CEO. https://www.linkedin.com/in/jessepgilmore/ https://www.nicheincontrol.com/  With our Leverage for Growth program and my 1-1 support, together we: — Create scalability in your agency so as you take on more clients, you don't increase your personal hours to serve them. — Increase your revenue by consistently attracting your dream clients that value your services through an effective client attraction system (referral, inbound and outbound). — Find, train and manage a growing team to handle whole parts of the company so you can focus on growth or taking time for yourself. A selection of the agency owners we've worked with: — Jade (digital marketing agency owner) took 8 weeks off and still hit record-breaking sales this year. — Melanie (marketing consultant) 2X revenue while working less and doing more of what she loves. — Ray (digital marketing) regained control of his time with new systems that supported success. — Scott (ad agency) 2X'd profit margins and took a full month off while clients were still served. — Ryan (content marketing) doubled revenue while cutting his workload by 50% in 12 months. — Michele (web + design) built a client-finding system and took back control of her business. — Shari (creative + branding) transformed her business and team dynamics in just 3 months. — Daisy (PR agency owner) eliminated 100+ hours/month and doubled revenue in 4 months. — Casey (marketing expert) shifted from generalist to niche authority with a dialed-in offer. — Laryssa (digital marketing) doubled her MRR in 3 months by landing high-ticket clients. — Chad (ad agency) transformed his mindset and created team unity for scalable growth. — Reece (digital marketing) gained clarity and implemented the systems needed to grow. — Mike (web dev) cut 30+ weekly work hours and scaled with an 8-hour, 5-day schedule. — Warren (digital marketing) scaled from $15K/month to over $100K/month in 9 months. — Tonnisha (social media) slashed 30 hours/week and tripled her revenue in 5 months. — Susan (creative) 2X'd her revenue + exited through acquisition in just 18 months. — Sara (social media) rebuilt her confidence and clarity with systems that scale. — Nick (SEO) streamlined ops, boosted team morale, and amplified growth.

What if the secret to leading creative teams wasn't control — but curiosity? Rob Sharenow shares the leadership philosophy behind decades of award-winning programming.   In this episode of The Heartbeat for Hire Podcast, host Lyndsay Dowd sits down with Rob Sharenow, President of Programming for A+E Networks, overseeing the creative vision behind A&E, HISTORY, Lifetime, A&E Indie Films, and Home.Made.Nation.   Rob is one of the most respected creative executives in modern media — an award-winning writer and producer, Emmy and Peabody–recognized leader, and a guiding force behind some of the most impactful storytelling and programming in the industry.   But his career? Anything but linear. Rob takes us through his unexpected path: ➡️ an unhappy academic in a PhD program ➡️ a risk-taking pivot into screenwriting ➡️ a bold 30–40% pay cut to pursue passion ➡️ and finally, rising to the top of a major media organization   This powerful conversation offers a rare inside look at what it really takes to lead creative teams, navigate volatility, and shape culture in one of the most competitive industries in the world.   This episode is a must-listen for creators, leaders, media professionals, entrepreneurs, and anyone who wants to understand the DNA of great storytelling and extraordinary leadership.  

In this episode, Carolyn and Amber pull back the curtain on a $500M cybersecurity company that came to Passetto stuck in last-touch reporting, declining win rates, an overreliance on product trials, and zero visibility into what SDRs were actually working.In just 14 days, their Growth Sprint surfaced what months of internal analysis couldn't: the true drivers of revenue, why trials convert at only 5%, why hand-raisers deliver 2X the deal size and win rate, and how 40% of opportunities are created with no traceable sales trigger at all.We walk through the exact before-and-after: their revenue architecture score, the missing SDR prospecting layer, the downstream impact of “low-signal” opportunities, and the data that finally gives the team conviction to modernize their demand engine.Even with strong tools and a mature sales motion, they're operating with only 55% revenue visibility, record-low win rates, and a demand strategy built almost entirely on trials—until the Sprint changes the trajectory.We break down the insights their team uncovers:Why 55% of SDR workload comes from trials that win at only 5%How high-intent hand raisers deliver 2X the ACV and more than 2X the win rateWhy only 35% of opportunities show early-stage signalsHow more than 40% of opportunities have no traceable prospecting trigger at allAnd how a two-week sprint becomes the “forcing function” they need to move from uncertainty to a clear set of strategic prioritiesA powerful example of what happens when companies finally get the full-funnel visibility they've been missing.

In this episode of 'For the 23%', Dielle McMillan shares her top business lessons from 2025, emphasizing the importance of skills over goals, the necessity of taking risks, and the value of making mature business decisions. She discusses how grief can signify growth and introduces the concept that 10X growth is easier than 2X, encouraging listeners to embrace change and focus on long-term success. 00:00 — Introduction to the Podcast and Mastermind Program 02:21 — Top Business Lessons from 2025 03:48 — Skills Over Goals: The Key to Success 11:06 — The Importance of Risk in Business 20:05 — Making Mature Business Decisions 25:17 — Grief as a Sign of Growth 30:57 — 10X is Easier than 2X: A New Perspective For the 23% is the women of color business and entrepreneurship podcast hosted by multi-million-dollar entrepreneur Dielle Charon. Each week you'll learn how to grow your sales, money, and freedom so we can increase the 23% of business owners who are women of color. Website: forthe23percent.com Instagram: @forthe23percent Membership: forthe23percent.com/membership

In today's episode, Tony and Marianna are diving into how to keep your progress moving forward even when you are completely out of your routine. Today, Fitness Stuff for Normal People breaks down how to adjust your diet, tweak your workouts, and set real guardrails so you can stay consistent through the holidays or any season when life gets busy. The holidays in particular make it tough to manage your routine and habits, but the right structure can keep you feeling in control without giving up the fun. These tools work whether you are traveling, moving, changing jobs, or juggling a full calendar. Long term success comes from learning how to pivot, not panic, and they are here to show you how to make that happen.⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Sign up for Fitness Stuff PREMIUM here!!⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ALL of our complete 12-week training programsBonus episodes every FridayJust $5 /month⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Legion Athletics⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠BOGO 50% off for your first order + 2X points on every order after thatuse code “FSPOD” at checkoutTimestamps:(7:26) Concept of "Guardrails"(10:56) Diet Guardrails(29:09) Training Guardrails(38:12) Mindset

Is it normal…or is it ADHD? That's the question that keeps so many parents of neurodivergent kids up at night, especially when old behaviors resurface after months or years of progress.  In this episode of The Soaring Child podcast, Dana Kay, board certified holistic health and nutrition practitioner, 2X international bestselling author, and mom of a child with ADHD, opens up about the emotional whiplash that can come with raising a neurodiverse child.  She shares what it's like to second-guess every behavior, even the ones that might just be typical childhood moments. Tune in to discover the difference between developmentally typical behavior and patterns that signal deeper dysregulation. Links Mentioned in the Show ▶ https://adhdthriveinstitute.com/breakfastguide ▶ https://adhdthriveinstitute.com/tool ▶ https://adhdthriveinstitute.com/supplements ▶ https://adhdthriveinstitute.com/parenting ▶ https://adhdthriveinstitute.com/book Key Takeaways with Timestamps [00:16] Why calm can trigger panic for ADHD parents [02:41] The "Is this normal or ADHD?" fear spiral [04:27] What counts as developmentally typical behavior [06:05] When patterns—not moments—signal deeper concerns [06:53] Why one meltdown feels heavier after progress [08:26] A client story: panic when the school didn't call [10:12] Why children (and adults) naturally have off days [11:34] How biology—gut, nutrients, inflammation—affects behavior [12:20] Questions parents can ask when behaviour worries them [14:17] Why hyperactive boyhood isn't pathology [16:42] Tracking patterns over time rather than reacting to one-offs [18:13] Validation that every parent needs to hear   Memorable Moments with Timestamps (Exact Quotes) "If peace somehow feels unsafe, it's not your fault." "I felt my whole body tighten… that hot flush that runs through every bone in your body." "One school phone call… and we spiral." "That fear doesn't mean everything is unraveling. It means that you care." "Progress hits harder when you finally experience peace." "For years, silence meant brace yourself—something bad's coming." "It means they're human children." "We've been conditioned to expect our children to behave better than most adults do." "These aren't signs of ADHD symptoms returning—these are signs of life." "Let them be messy. Let them be human. Let them be in process." Connect with Ashley: ▶ Instagram – https://www.instagram.com/healing_with_ashley ▶ Facebook – https://www.facebook.com/ashley.gobeil.50 ▶ Website – https://ashleychildtherapies.com.au Dana Kay Resources:

In this powerful episode, host Jacqueline Landry interviews Dave Seymour, retired firefighter turned real estate mogul and star of A&E's "Flipping Boston." Dave reveals why corporate professionals are most vulnerable to the coming AI disruption and how multifamily real estate investing can create financial security.Episode Highlights:Why trading time for money creates a ceiling on successHow discipline beats motivation in wealth buildingThe AI layoff wave targeting high-earning professionalsOwning cash-flowing multifamily assets with 2X returns over 5-7 yearsTax strategies that eliminate W-2 tax burden (depreciation & cost segregation)Teaching kids about the "rat race" and wealth-buildingThe truth about real estate failures and why doing nothing guarantees defeatKey Quotes: "Seekers seek, finders find. Knock and the door will be opened." "I can guarantee 100% failure in this business, and that's to not do anything."Perfect for corporate professionals worried about job security, high-earners drowning in taxes, or anyone ready to break free from traditional retirement models.Connect with Dave Seymour: Website: freedomventure.com LinkedIn: daveseymour343 YouTube: @legacyallianceclub X: @daveseymour343 Instagram: @daveseymour343 Facebook: @daveseymourlive Email: info@freedomventure.comAbout Dave: Retired 16-year firefighter and paramedic who launched his real estate career during the last market crash. Leading expert in commercial multifamily and ground-up development. Featured on A&E's "Flipping Boston," CBS, ABC, CNBC, and Fox News. Founder of Freedom Venture Investments and Legacy Alliance.Subscribe to Get Diversified for more episodes on multifamily investing, tax strategies, and generational wealth!

What happens when a medical device executive walks away from a stable 17-year career to build a digital marketing agency in one of the most complex industries on Earth? In this compelling episode of The Proven Entrepreneur Show, host Don Williams sits down with Saul Marquez, founder and CEO of Outcomes Rocket, to uncover the untold story of pivoting, perseverance, and the power of trusting your gut in healthcare entrepreneurship.Before he founded Outcomes Rocket, Saul Marquez spent 17 years in medical devices, living what many would call a "dream career." In this candid conversation with host Don Williams on The Proven Entrepreneur Show, Saul shares how he walked away from that security to build a specialist healthcare marketing agency serving health tech, medical device companies, and ambulatory provider groups. If you've ever felt torn between a safe path and a bigger vision, this episode will feel uncomfortably familiar in the best way.You'll hear Saul break down his simple decision framework of "dreams and data"—how he used both gut instinct and real-world evidence from over 2,000 podcast interviews with healthcare leaders to validate his leap into healthcare entrepreneurship. The discussion dives deep into health tech marketing, medical device marketing, and why "you sell like you buy" is one of the most practical mindset checks for any founder, CEO, or marketing leader. They unpack why "cheap marketing" is so expensive, when to stop DIYing and hire real experts, and how to think about podcasts and webinars for lead generation in today's healthcare landscape.Saul also shares a raw story about a webinar gone wrong—a painful early failure that turned into a long-term client relationship and bulletproof SOPs (Standard Operating Procedures) through radical ownership. Along the way, Don and Saul talk about comfort zones, "burn the boats" moments, choosing mentors wisely, and what big thinkers in healthcare are really struggling with behind the scenes. This conversation covers essential topics for anyone navigating the intersection of healthcare business growth and digital transformation.What You'll Learn:How to validate a business idea using the "dreams and data" framework before taking the leapWhy healthcare commercialization requires strategic marketing partnerships, not budget solutionsThe psychological barriers keeping healthcare professionals from becoming successful entrepreneursHow B2B healthcare marketing differs from other industries and why it requires specialized expertiseThe role of content marketing, webinars, and podcasts in healthcare lead generationWhy 10X growth is easier than 2X growth—and what that means for your strategyHow to recover from catastrophic failures and turn them into competitive advantagesThe importance of surrounding yourself with mentors who've already achieved your goalsPractical strategies for health tech and medical device company growthThe "three M's of leadership": Mindset, Mission, and MethodologyWhy This Episode Matters:This isn't generic entrepreneurship advice—it's a masterclass in healthcare business strategy from someone who's built a thriving agency while serving some of the most complex organizations in the industry. If you're a health tech founder, medical device company leader, healthcare CEO, ambulatory provider, or anyone in the healthcare sales space wondering why your marketing isn't working, this conversation will rewire how you think about growth.Subscribe to The Proven Entrepreneur Show for more unfiltered conversations with leaders building billion-dollar healthcare businesses and navigating healthcare commercialization.

What It Feels Like to Lead the World's Most Successful Musical with Maggie Brohn ---------------------------- She started answering phones. Now she runs Broadway's biggest global hit. Meet Maggie Brohn, the powerhouse behind Hamilton. In this episode of Heartbeat for Hire, host Lyndsay Dowd sits down with Maggie Brohn, Chief Operating Officer of Adventureland and the powerhouse Executive Producer of Hamilton across Broadway, the West End, Disney+, multiple global tours, and international productions. Maggie shares the remarkable story of how she went from answering phones in a theatrical office to becoming an owner, producer, and one of the most influential leaders in modern theater. She breaks down how Hamilton transitioned from a groundbreaking production into a global business — operating more like a major corporation than a traditional Broadway show. We explore the art of leading creatives, building trust, setting authority, navigating strong emotions, and making mission-critical decisions. Maggie reveals what it takes to guide artists while staying grounded in business realities and cultivating a team capable of worldwide excellence. She also opens up about listening, cultural sensitivity, DEI conversations, building long-term contracts, and why the industry needs a full reset. Plus, Maggie shares what Broadway needs most right now — and how audiences can help.
   
 Timestamps
 00:00:00 Intro: The Audience's Desire for Delight in Theater
 00:01:00 Introducing Maggie Brohn: Broadway's Executive Producer and COO
00:01:58 Maggie's Journey: From Answering Phones to Producing Hamilton
00:03:23 Leading Creatives: Setting Authority and Navigating Feelings
 00:04:30 The Power of Trust and Delegating to Expertise
 00:06:00 The Biggest Lesson: Moving Theater from "Show" to Global Business
00:08:15 Adapting Hamilton for International Audiences
 00:11:59 The Current State of the Broadway Business
 00:18:24 Setting Boundaries as a Manager
 00:20:32 An Early Leadership Test: The Jack Daniels & Massage Request
00:23:46 Leading as an Outsider and a Woman in a Male-Dominated Group
00:24:49 Listening & Hard DEI Conversations
 00:26:50 Maggie's Legacy: Leading an Industry "Reset"
 00:30:22 Union Negotiations & Long-Term Contracts
 00:33:26 How to Support Theater & Broadway Today
 00:34:18 Conclusion & Final Thoughts
   
 About the Guest
 Maggie Brohn is the Chief Operating Officer of Adventureland and the Executive Producer of Hamilton on Broadway, the West End, the international tour, UK/Ireland Tour, and Disney+. Her recent credits include The Nightmare Before Christmas Light Trail at New York Botanical Garden, the 2023 Sweeney Todd Broadway revival, Hamilton in Hamburg and Australia, Derren Brown: Secret, and The Cher Show. Previously a partner at Bespoke Theatricals, Maggie general-managed major plays and musicals for over a decade. She serves on the Board of Governors and Executive Committee for The Broadway League and is a former Co-Chair of the Labor Committee. She resides in New York City with her husband and two children. 
 About the Host – Lyndsay Dowd is a Speaker, Founder, Author, Coach, Podcast Host—and unapologetic Disruptor. With 30 years of leadership experience, including 23 at IBM, she's built and led high-performing teams that consistently delivered results. She also served as a Guest Lecturer at Harvard University, sharing her insights on modern leadership and culture transformation. 

 As the founder of Heartbeat for Hire, Lyndsay helps companies ditch toxic leadership and build irresistible cultures that drive performance, retention, and impact. She's been featured in Fortune Magazine, HR.com, ABC, NBC, FOX, CBS, and over 100 podcasts. 

   Lyndsay is a two-time best selling author of Top Down Culture and Voices of Women, and the host of the globally ranked and 2X awarded Heartbeat for Hire podcast—sitting in the top 2.5% worldwide. She is also the host of a weekly live show called THE LEADERSHIP LOUNGE. Lyndsay is a frequent speaker, moderator, and guest, known for her candor, humor, and ability to spark action.
  Official Brand Partner: https://MyDeals.Page/19c3 
 To my loyal listeners - I love luxury and I love a great deal. 
 If you are looking for an amazing gift or a way to treat yourself, Go to https://cozyearth.com/ and use the code LEADWITHHEART and get 41% off. It's the deepest discount you will find anywhere and I get commission too! This brand has been on Oprah's Favorite Things 9 times!! Happy Shopping!   
 Connect with Lyndsay Dowd:  Website: https://heartbeatforhire.com
  LinkedIn: https://www.linkedin.com/in/lyndsaydowdh4h/  Instagram: https://www.instagram.com/lyndsaydowdh4h/ 
  Facebook: https://www.facebook.com/LyndsayDowdH4H
  Tiktok: https://www.tiktok.com/@lyndsaydowdh4h
   #Hamilton #Broadway #MaggieBrohn #HamiltonMusical #ExecutiveProducer #LeadershipPodcast #CreativeLeadership #TheaterBusiness #WomenInLeadership #BehindTheScenes #HeartbeatForHire

The Truth About Food Nobody Told You with Matt Beaudin | with Lyndsay Dowd   Some chefs chase fame. Matt Beaudin chased truth. From riverbank fires in Vietnam to volcanic soil in Rwanda, he learned from people whose kitchens often had no walls—only stories, culture, and purpose. Today, he shares that journey with us. In this cinematic and eye-opening episode, we sit down with Chef Matt Beaudin, a world-class culinary leader whose career has been built not in glossy kitchens—but in the kitchens of villagers, fishermen, farmers, and cultures most chefs have only read about. Matt's journey has taken him from the volcanic slopes of Rwanda to riverbank fires in Vietnam, from hidden markets in Hong Kong to back-porch grills in the Caribbean and small island kitchens in Barbuda. He didn't travel to collect stories—he traveled to earn them. Today, Matt is a leading voice in sustainability and conservation, using food as a platform for purpose. In this conversation, he shares how consumer choices shape global supply chains, why real sustainability requires truth—not marketing—and how partnering with the right suppliers can uplift communities and protect the environment. We also dive into his journey from barely graduating high school in a small New Hampshire town to attending the Culinary Institute of America, often called the "Harvard of cooking schools," and becoming a globally respected culinary storyteller. If you care about food, culture, leadership, conservation, or making an impact, this is a must-listen.

    Timestamps
 00:00 – Welcome and Episode Themes
 01:18 – Meet Chef Matt Beaudin: From Small Town to CIA
 04:39 – Leadership and Culture in the Kitchen
 05:31 – Partners, Not Purveyors: Food as a Conservation Platform
 08:49 – The Reality of the Global Supply Chain (Ghana & Vietnam)
 13:00 – Finding Purpose: SSA Group & Seafood Watch
 17:14 – Simple Ways to Make an Impact
 24:56 – The Power of Consumer Choice & Sense of Place
 28:49 – Bluefin Tuna & Conservation Wins
 32:00 – Final Takeaway

    About the Guest
Matt Beaudin is a globally recognized chef, culinary storyteller, and advocate for sustainability and conservation. His work bridges culture, food integrity, and environmental responsibility through partnerships with communities around the world. 
 About the Host – Lyndsay Dowd is a Speaker, Founder, Author, Coach, Podcast Host—and unapologetic Disruptor. With 30 years of leadership experience, including 23 at IBM, she's built and led high-performing teams that consistently delivered results. She also served as a Guest Lecturer at Harvard University, sharing her insights on modern leadership and culture transformation. 

 As the founder of Heartbeat for Hire, Lyndsay helps companies ditch toxic leadership and build irresistible cultures that drive performance, retention, and impact. She's been featured in Fortune Magazine, HR.com, ABC, NBC, FOX, CBS, and over 100 podcasts. 

   Lyndsay is a two-time best selling author of Top Down Culture and Voices of Women, and the host of the globally ranked and 2X awarded Heartbeat for Hire podcast—sitting in the top 2.5% worldwide. She is also the host of a weekly live show called THE LEADERSHIP LOUNGE. Lyndsay is a frequent speaker, moderator, and guest, known for her candor, humor, and ability to spark action.
   
 To my loyal listeners - I love luxury and I love a great deal. 
 If you are looking for an amazing gift or a way to treat yourself, Go to https://cozyearth.com/ and use the code LEADWITHHEART and get 41% off. It's the deepest discount you will find anywhere and I get commission too! This brand has been on Oprah's Favorite Things 9 times!! Happy Shopping! 

    Connect with Lyndsay Dowd: 
  Website: https://heartbeatforhire.com
  LinkedIn: https://www.linkedin.com/in/lyndsaydowdh4h/ 
  Instagram: https://www.instagram.com/lyndsaydowdh4h/ 
  Facebook: https://www.facebook.com/LyndsayDowdH4H
  Tiktok: https://www.tiktok.com/@lyndsaydowdh4h

   #ChefMattBeaudin #CulinarySustainability #FoodCulture #VoteWithYourPlate #CulinaryJourney #ConservationMatters #SustainableSeafood #GlobalCuisine #CulinaryLeadership #FoodWithPurpose

In this episode of Fitness Stuff for Normal People, it's Microdose Monday, and Tony and Marianna delve into four diverse topics that have grabbed their audience's attention. They start by discussing how neglecting essential activities like lifting weights and walking can be more hazardous than smoking or drinking. Then, they dive into recent concerning findings regarding the effects of daylight savings time on health. Following that, they explore promising new data on how GLP-1 medications might aid in combating alcohol and drug addiction. Before wrapping up, they touch on the impact of changing sleep patterns on overall health and discuss upcoming, exciting developments in the realm of fitness and wellness.⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Sign up for Fitness Stuff PREMIUM here!!⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ALL of our complete 12-week training programsBonus episodes every FridayJust $5 /month⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Legion Athletics⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠BOGO 50% off for your first order + 2X points on every order after thatuse code “FSPOD” at checkoutTimestamps:(04:48) Sitting vs. Smoking(13:01) GLP-1s and Alcohol + Drug Addiction(23:47) DST Science

Once again the Devils are finding out that life without Jack is going to be a grind. Our heroes struggled on offence whilst getting shut out by the 2X champs. The "Puckers" discuss who really needs to step up? who is available to come in and help? and lastly, can we please have Bill Spaulding back? He never once confused us with the freaking Rangers. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Ever look at your to-do list and think, 'Cool, I'll just clone myself and maybe then I'll get it all done'? Yeah. Same. But here's the truth — overwhelm isn't a sign you're doing too little. It's a sign you're doing too much of the wrong stuff. Let's fix that. Feeling buried under your to-do list? You're not alone — but you don't have to live there. In this high-impact episode, April breaks down five simple, tactical moves that shift you from chaos to clarity. Whether you're running a business, leading a team, or juggling it all, this episode will help you reclaim control, eliminate noise, and focus on what actually matters. Because you don't need more time — you need fewer distractions disguised as priorities. Key Takeaways 1️⃣ The 4-Step PivotMe Process Ask: Does this need to be done? Does it need to be done by me? If not, delegate, delay, or delete. Then check for OPP (Other People's Priorities), pick your one move that moves the needle, and execute with focus. 2️⃣ The Eisenhower Matrix Separate urgent from important: Urgent + important → Do now. Important + not urgent → Schedule. Urgent + not important → Delegate. Neither → Delete. 3️⃣ The 10X Filter Ask: "If I were operating at my 10X goal, would I be doing this?" Your next level requires next-level decisions. 4️⃣ The Pivot Pause Step away, breathe, and ask, "What actually needs to happen next?" Stillness creates clarity. 5️⃣ Time Blocking with Themes Batch your focus. Example: Monday: Strategy Tuesday: Clients Wednesday: Content Thursday: Networking Friday: Financials Context-switching drains energy — batching restores it. Bonus: Write your Stop-Doing List. Subtraction equals freedom.  Quotes "Not every fire deserves your water." "You win the day by finishing, not by juggling." "You can't 10X your life doing the same things you did at 2X." "Stillness creates clarity — not chaos."  Action Steps ✅ Run your to-do list through the 4-Step PivotMe Filter. ✅ Create your own Eisenhower Matrix and start deleting what doesn't matter. ✅ Ask the 10X question before saying yes. ✅ Schedule your Pivot Pause — don't wait for burnout to do it. ✅ Build a Time-Blocked Week that aligns with your future self. When you're overwhelmed, stop reacting and start pivoting. You don't need more caffeine — you need more clarity. One focus, one day, one pivot at a time.

In this transformative episode, Lyndsay Dowd sits down with Dr. Iris Crawford, the world's leading authority on the Pre-Hormone System and one of the most trusted voices in women's hormonal health. Known as The Hormone Boss, Dr. Crawford reveals the truth about menopause, perimenopause, burnout, fatigue, and why conventional medicine is still operating from outdated hormonal science. Dr. Crawford opens up about her journey from growing up in poverty to becoming a nationally recognized naturopathic physician dedicated to empowering women with real answers. She explains why most women enter menopause already hormonally imbalanced—and why a "just do HRT" approach is not only incomplete but can be ineffective or harmful. This episode breaks down the stress response system, the pre-hormone system, and why accurate hormone ratio testing is the missing key to helping women reclaim their energy, mood, and mental clarity. Dr. Crawford outlines her proven six-month protocol, designed to repair hormone production at the root. Whether you're navigating hormonal changes, burnout, or searching for answers your doctor can't explain, this episode will leave you informed, empowered, and hopeful.

   About the Guest
 Dr. Iris Crawford is the world's leading expert on the Pre-Hormone System, a licensed naturopathic physician, author, speaker, and national women's hormone specialist. Affectionately known as The Hormone Boss, she earned her medical degree from the National University of Natural Medicine and her Bachelor of Science in Holistic Nutrition from Bastyr University. With decades of clinical experience, Dr. Crawford has helped thousands of women finally understand the root causes of fatigue, mood swings, weight changes, perimenopause, menopause symptoms, and burnout. Her groundbreaking approach moves beyond outdated HRT-only models and focuses on restoring hormonal balance by repairing the body's stress and pre-hormone systems. She is dedicated to empowering, educating, and unlocking the leadership potential of women by helping them reclaim their health—from the inside out.
  Connect with Dr. Iris Crawford Website: https://www.hormone-boss.com/
 Facebook: https://www.facebook.com/thehormoneboss
 Instagram: https://www.instagram.com/hormone.boss
 LinkedIn: https://www.linkedin.com/in/dririscrawford/
 Membership: https://go.hormone-boss.com/opt-in-page-401882   
About the Host – Lyndsay Dowd is a Speaker, Founder, Author, Coach, Podcast Host—and unapologetic Disruptor. With 30 years of leadership experience, including 23 at IBM, she's built and led high-performing teams that consistently delivered results. She also served as a Guest Lecturer at Harvard University, sharing her insights on modern leadership and culture transformation. 

As the founder of Heartbeat for Hire, Lyndsay helps companies ditch toxic leadership and build irresistible cultures that drive performance, retention, and impact. She's been featured in Fortune Magazine, HR.com, ABC, NBC, FOX, CBS, and over 100 podcasts. 

Lyndsay is a two-time best selling author of Top Down Culture and Voices of Women, and the host of the globally ranked and 2X awarded Heartbeat for Hire podcast—sitting in the top 2.5% worldwide. She is also the host of a weekly live show called THE LEADERSHIP LOUNGE. Lyndsay is a frequent speaker, moderator, and guest, known for her candor, humor, and ability to spark action.

    To my loyal listeners - I love luxury and I love a great deal. 
If you are looking for an amazing gift or a way to treat yourself, Go to https://cozyearth.com/ and use the code LEADWITHHEART and get 41% off. It's the deepest discount you will find anywhere and I get commission too! This brand has been on Oprah's Favorite Things 9 times!! Happy Shopping! 

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Try Activations free for 2 weeks + get a huge discount at https://www.activations.com/podcast/sahara   In this episode, I'm sitting down with the incredible Mimi Bouchard, founder of Activations, to talk about abundance, manifestation, career pivots, and money mindset.   One of the biggest questions I get is how I created a business where I'm literally paid to be me, making seven figures while talking about past lives, sacred feminine energy, and rose serpentine between Bali, Egypt, and India.    Growing up, no woman in my family even worked. I was told you get a job you hate, and that's life. I thought it was either do what you love and be broke, or sell your soul to make money.   Mimi's story is so similar. She didn't come from wealth. She grew up watching her parents fight about money, surrounded by scarcity and fear. But she made these massive mindset shifts that completely transformed her reality.    Now she's living in the Bahamas, married to her dream partner, and running a seven-figure business with Activations, a revolutionary audio app that's not meditation, not affirmations, it's activation. Over 700 guided visualizations paired with cinematic music designed to rewire your brain while you move through your day.   We dive into: ✨ How to rewire limiting beliefs around money and abundance

Today's episode of Fitness Stuff for Normal People breaks down five of the most misunderstood topics in health and fitness and the myths that refuse to die. Sugar, inflammation, fat loss, cortisol, and seed oils are some of the most talked about topics in the space, yet they're still widely misunderstood. Marianna and Tony walk through the research, clear up common confusion, and explain what's real in a way that actually feels approachable. You'll leave with a clearer understanding of what truly impacts your health and what tends to get overstated.⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Sign up for Fitness Stuff PREMIUM here!!⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ALL of our complete 12-week training programsBonus episodes every FridayJust $5 /month⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Legion Athletics⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠BOGO 50% off for your first order + 2X points on every order after thatuse code “FSPOD” at checkoutTimestamps:(4:53) Inflammation(22:25) Sugar(31:55) Cortisol(43:07) Fat Burning(46:57) Seed Oils

Good morning, afternoon, and evening, fellow real estate gladiators! Ever wondered if those sweet Airbnb profits are just a myth, or if you can actually turn a rental into a cash-flowing beast? Well, get ready, because Scott is joined by the Twin Cities' own rockstar investor, Mike Swenson! Mike's not just an amazing investor, he's a realtor-broker, a multifamily maven, and he's mastered the art of short-term rental (STR) arbitrage. We're diving deep into his journey from a foreclosed townhouse to building a robust real estate empire, including some juicy stories from the front lines of STR management. If you're looking to boost your cash flow, scale your portfolio, or just avoid cleaning up after a wild party, this episode is your golden ticket!In this episode, you'll learn:Arbitrage & Strategic Market Shift: Discover Mike's strategic pivot from Minneapolis/St. Paul's complex regulations and tenant-friendly policies to the growth potential of Southern Minnesota (hello, Mayo Clinic!). Learn how STR arbitrage became his "air game" – a brilliant way to gain experience and quick cash flow without the huge capital commitment of "slow-flip" apartment buildings.Nailing STR Profitability: The 2X Rule & Smart Due Diligence: Forget the 1% rule for traditional rentals; Mike shares how he aims for 2X the conventional rent for his short-term rentals. Get his insider tips on using tools like AirDNA for market analysis, spotting "notch above" properties (think updated kitchens & baths!), and why consistent year-round demand (near airports, attractions like the Mall of America, and business hubs) trumps seasonal "cabin country" for stable income.Landlord Hacks & Ironclad Insurance: Mike reveals his secret sauce for convincing landlords to embrace STR arbitrage – frame it as a "corporate rental" and highlight the benefits of consistent property oversight, proactive maintenance, and reliable rent. Plus, understand the crucial role of specialized landlord insurance and the necessity of your own STR policy to protect against those inevitable "hiccups" (like, say, a drug lab or a wild party!).The Unfiltered Truth of STR Operations: Cleaners, Guests & The Occasional Chaos: Prepare for the unfiltered truth about STR management! Mike breaks down the biggest operational challenges: finding and managing reliable cleaning crews (a major expense!), handling demanding guests (some expect the Four Seasons, bless their hearts!), and the constant battle against wear and tear (RIP that toilet paper holder!). Learn why banning one-night and same-day local bookings became his hard-earned golden rule to dodge party animals and less-than-desirable tenants.Scaling Smart: From Side Hustle to Empire & Your Next Steps: Mike reflects on his journey, explaining why arbitrage was his training ground and how he eyes future growth by owning STR properties for long-term appreciation or scaling into hospitality ventures. He offers crucial advice: truly understand your numbers (margins can shrink!), don't scale too fast, and always include lease clauses to protect yourself from changing STR regulations. Remember, it's not truly passive until you build the right leverage!So there you have it, folks! Mike Swenson's deep dive into the dynamic world of short-term rentals and multifamily investing proves that with strategy, resilience, and a good sense of humor, you can navigate the ups and downs of real estate. From dodging party planners to mastering landlord relations, his insights are pure gold. Ready to grab some of that cash flow for yourself and maybe even build an apartment empire? Connect with Mike and let his journey inspire your own. Go out, take some action, and let's turn those properties into cash cows (preferably without the weed smokers!). We'll see you at the top!Watch the Original VIDEO HERE!Connect with Mike Here!Book a Call With Scott HERE!Sign up for the next FREE One-Day Note Class HERE!Sign up for the WCN Membership HERE!

In this episode of The Tech Leader's Playbook, Avetis Antaplyan sits down with Valerie Jackson — Harvard College and Georgetown Law alum, former securities lawyer turned C-suite people leader — to explore what it really takes to scale companies without breaking leaders or culture. Valerie traces her journey from advising public companies and serving at the U.S. Public Company Accounting Oversight Board to building one of the first law-firm diversity departments and leading people operations across VC-backed rockets, public SaaS, and PE-owned businesses. Together they unpack human-centered leadership, the mechanics of burnout (as recognized by the WHO), and why self-work is often the hardest part of scaling. Valerie shares practical tools — from 360s, “powerful partnerships,” and time audits to managing brain chemistry — and makes a compelling case that AI should elevate people, not erase them, because nothing can replace a leader's “energetic signature.” The conversation closes with hard-won lessons on IPO vs. going private, PE vs. VC risk appetites, and Valerie's mantra: “Know your ripple.”TakeawaysGreat leadership starts with self-awareness. Learn yourself to lead others.Build “powerful partnerships”: pair visionary thinkers with linear operators.Align culture: what we say (cognitive) with how we behave (emotional).Use 360 feedback to surface blind spots with curiosity and humility.Burnout = exhaustion + inefficacy + cynicism. Address all three to recover.Run time audits to find your “golden ratio” of energizing vs draining work.Support brain chemistry intentionally: dopamine, serotonin, oxytocin, endorphins.Keep AI human-centric. Technology should amplify people, not replace them.Design for tool obsolescence and misuse while protecting the humans.IPOs bring capital and scrutiny; going private can restore flexibility.PE and VC differ on time horizons, risk, and control expectations.Leader's billboard: “Know your ripple.” Be intentional about your impact.Chapters00:00 Intro and why human-centered leadership matters01:28 Meet Valerie Jackson: law to people leadership across stages03:25 Early diversity work and career inflection points05:10 Patterns across org models: partnership, VC, public, PE06:59 Visionary vs linear strengths and “powerful partnerships”08:51 Self-work as a prerequisite to leading others12:20 Culture alignment: words, behaviors, and trust17:29 Feedback that works: curiosity, humility, and 360s25:00 Burnout explained: exhaustion, inefficacy, cynicism32:31 Time audits and defining your “golden ratio”34:23 Brain chemistry levers for sustainable performance37:03 Delegate to elevate: designing roles around energy40:04 Keeping people at the center of AI43:11 The “energetic signature”: what AI cannot replace52:49 IPO tradeoffs and why some companies go private56:13 PE vs VC: incentives, timelines, and control1:03:09 Tools and books leaders actually use1:05:22 10X vs 2X: optimization vs transformation1:08:52 Billboard for leaders: “Know your ripple”1:11:19 Closing and take-home actionsValerie Jackson's Social Media Link:https://www.linkedin.com/in/vadjackson/Resources and Links:https://www.hireclout.comhttps://www.podcast.hireclout.comhttps://www.linkedin.com/in/hirefasthireright

In this fascinating episode of Heartbeat for Hire, host Lyndsay Dowd sits down with Brian Galke, a communication strategist, keynote speaker, and founder of Subtle Skills, to explore the science of face reading, body language, and connection in an increasingly digital world. Known as The Decoding Detective, Brian reveals how understanding facial features can unlock deeper human connection and more effective communication — whether you're in leadership, sales, or just trying to better understand the people around you. From overcoming social anxiety to managing a $40M book of business, Brian's journey proves that anyone can learn to decode others and communicate with confidence. He breaks down the subtle cues that reveal how people process information, make decisions, and prefer to be spoken to — and how applying these tools can make you more influential, authentic, and connected.

Welcome back to Fitness Stuff for Normal People. Today's episode is a split. First, Marianna and Tony break down what actually separates training for strength from training for size, and how dialing in the right approach can change your progress entirely. Then we move into why “skinny” isn't the goal, and what real health looks like when you zoom out past aesthetics. Consider this a reset for both your programming and your perspective, so your training reflects what you actually want.⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Sign up for Fitness Stuff PREMIUM here!!⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ALL of our complete 12-week training programsBonus episodes every FridayJust $5 /month⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Legion Athletics⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠BOGO 50% off for your first order + 2X points on every order after thatuse code “FSPOD” at checkoutTimestamps:(5:16) Strength vs Size
(27:34) Skinny Tok

Tech editor Alvin Holbrook fires up Velo's crystal ball to make some predictions about what the road and gravel world might look like in 2026. He makes his case for peak tire width combined with improved casings, more integrated pressure-monitoring systems (and more batteries), Chinese gravel bikes shaking up the market, and the continued slow demise of 2X drivetrains. But is he channelling Edgar Cayce, or are his divinations more in line with Miss Cleo? Josh, Alvin, and Levy also discuss how prepared they are (or aren't) for a mid-ride disaster, and the crew describes their own go-to repair kit that they each bring on every single ride. Also, when is it best to just call someone to come pick you up? Want to join Josh on his Zwift group ride? See the info here. See more episodes of the Velo Podcast here. Further reading: Hookless Is Out, AI Shades Are In: 7 Road Bike Trends We Expect to See in 2026 Garmin Teamed Up With Oakley and Meta to Make Smart Glasses We Actually Want to Wear MTB Tires Are Out, Suspension Is In: 5 Gravel Bike Trends We Expect in 2026 Forget $300 Fans, Our 3 Favorite Cooling Hacks for Indoor Training Are Basically Free 0:00 Intro1:20 Josh's inflammatory no-tube comments3:11 Gravel predictions32:30 Interlude: Josh used the new Oakley x Meta Vanguard glasses39:45 Road predictions51:30 How prepared are you? What we carry for our rides59:00 Josh, Alvin, and Levy's toolkits

What if perfectionism is actually killing your success? In this Habits and Hustle episode, Kim Perell, a nine-time serial entrepreneur, joins me to share why waiting to feel ready is the biggest mistake aspiring business owners make.  We dive into Kim's morning routine, her partnership with Jay Shetty on Junie, and why exercise is her number one productivity tool. We also discuss why iteration beats innovation, and how she balances building multiple companies while raising four kids. Kim Perell is a 9X founder, 2X bestselling author, and investor in 100+ companies. Kim is a dynamic TV personality on Entrepreneur Magazine's Elevator Pitch and regularly appears on Good Morning America, The Today Show, CNBC, Fox, and in Forbes, Inc., and The New York Times. Her book "Mistakes That Made Me A Millionaire" shares the unfiltered truth about the journey to success, proving that every mistake holds the potential for million-dollar lessons. What We Discuss: 04:20 - The number one mistake: waiting to feel 100% ready before starting 05:09 - The Marine Corps 70% solution and how to apply it 06:56 - Why iteration beats innovation (and saves time) 07:21 - Co-founding Junie with Jay Shetty in a crowded beverage market 58:10 - Daily routine: waking at 6 AM, red light therapy, and meditation 59:28 - Running a household with four kids like a company 01:00:29 - Workout routine: HIIT, Peloton, and personal training at home 01:01:08 - Supplement stack: Momentous protein and creatine 01:03:00 - Why exercise is about mental health and focus, not competition 01:03:27 - Exercise as the number one longevity hack above all supplements …and more! Thank you to our sponsors: Therasage: Head over to therasage.com and use code Be Bold for 15% off  Air Doctor: Go to airdoctorpro.com and use promo code HUSTLE for up to $300 off and a 3-year warranty on air purifiers. Magic Mind: Head over to www.magicmind.com/jen and use code Jen at checkout. Momentous: Shop this link and use code Jen for 20% off  Manna Vitality: Visit mannavitality.com and use code JENNIFER20 for 20% off your order  Prolon: Get 30% off sitewide plus a $40 bonus gift when you subscribe to their 5-Day Program! Just visit https://prolonlife.com/JENNIFERCOHEN and use code JENNIFERCOHEN to claim your discount and your bonus gift. Amp fits is the perfect balance of tech and training, designed for people who do it all and still want to feel strong doing it. Check it out at joinamp.com/jen    Find more from Jen:  Website: https://www.jennifercohen.com/ Instagram: @therealjencohen   Books: https://www.jennifercohen.com/books Speaking: https://www.jennifercohen.com/speaking-engagement Find more from Kim Perell:  Instagram: @kimperell Website: https://kimperell.com/ 

Your mind can literally change your body just by believing something will work. In this episode Tony and Marianna break down the placebo and nocebo effects and how your thoughts alone can shape pain hormones recovery and performance. They dig into the science in a way that actually makes sense talk through real examples and share how to apply it to your own training and health. Join the Fitness Stuff community for a conversation that will change how you think about what your body is capable of.⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Sign up for Fitness Stuff PREMIUM here!!⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ALL of our complete 12-week training programsBonus episodes every FridayJust $5 /month⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Legion Athletics⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠BOGO 50% off for your first order + 2X points on every order after thatuse code “FSPOD” at checkoutTimestamps:(3:58) Placebo(6:35) Nocebo(13:01) How the Placebo Effect Works(28:30) The Nocebo Effect in Action(39:40) Placebo in Action(46:09) Using and Avoiding Placebo and Nocebo Effects

At 35, Sara Vaughn was just getting started—landing her first professional contract and proving that sometimes the best chapters come when you're brave enough to rewrite the story.Sara Vaughn is mom of 4, placed 6th in the NYC Marathon in 2024, is a top American and 2X top 10 at the Chicago Marathon.Jon chats with Sara about:​living the fullest Boulder lifestyle​her marathon training structure​the winning mindset to have at the start line​post-race recovery techniques​the go-to PUMA shoes that have lead to PRsStay connected:Follow Sara:https://www.instagram.com/saravaughn_realtor/https://www.instagram.com/vaughnchildcarefund/This episode is supported by:PUMA: Get your pair at your local Fleet Feet or your favorite local running shop!Janji: Use code “FTLR” at checkout when shopping at janji.com for 10% off your order and see why Janji is the go-to for runners who want performance gear made to explore. All apparel is backed by a 5 year guarantee, so you know it's meant to last!Eternal: Eternal is a performance health company for runners, endurance, and anyone serious about their training, with expert guidance to keep you healthy and performing your best.AmazFit Check out the T-Rex 3 and a selection of GPS watches at http://bit.ly/4ojbflT and use code “FTLR” for 10% off.Boulderthon: Our favorite Colorado race event with a variety of distances. Use code FTLR20 for $20 off the marathon or half marathon when you register at www.boulderthon.org.

Want to 2X your passive income from every real estate deal? Kris Krohn reveals a powerful yet overlooked method to dramatically increase your cash flow, whether you're investing in single-family homes, multi-family units, or commercial properties. Tune in to discover how to strategically move your money to maximize returns and create sustainable financial freedom.

Spencer Reese welcomes Lieutenant Commander Webster Felix, a Navy prosthodontist, for an in-depth discussion about maximizing military medicine benefits. Webb's journey from enlisted E6 dental student to O5 prosthodontist showcases the incredible opportunities available in military healthcare. This episode unpacks lesser-known scholarship programs, specialty training funding, loan forgiveness strategies, and GI Bill transfers that enabled Webb and his wife to complete advanced degrees debt-free while building generational wealth for their family. Lieutenant Commander Webster Felix, USN Specialty: Prosthodontist (restorative dentistry expert, full mouth rehabilitations) Current Station: Naval Medical Readiness and Training Command (NMRTC) Pearl Harbor, Hawaii Career Timeline: 14 years active duty, recently selected for O5 Education: Bachelor's in Biology, Temple University (2011) DDS, Columbia University College of Dental Medicine (2015) Master's in Dental Education (completed during dental school using GI Bill) Prosthodontics Residency, USC (2021-2024, funded by DUIN) Instagram: @prosthopapi - Features clinical cases and prosthodontic work Personal Background: Son of Haitian immigrants who arrived in the US in 1987; first-generation college graduate demonstrating how military medicine can transform generational wealth trajectories HSCP vs HPSP - The Scholarship Most People Don't Know About: HPSP covers full tuition but you're not active duty during school HSCP means active duty status (E6/E7 pay + BAH + TRICARE) but you take loans for tuition Webb entered dental school as E6, commissioned directly to O3E in 2015 Critical advice: Apply for BOTH programs simultaneously The $500K Student Loan Forgiveness Strategy: Graduated Columbia dental school with ~$400-500K in loans Enrolled in Public Service Loan Forgiveness (PSLF) immediately First payments: $170/month (based on E6 salary) Current payments: ~$800/month (O4E salary) Hitting 10-year mark in October 2025—expecting full forgiveness Must consolidate to federal direct loans or you won't qualify Duty Under Instruction (DUIN) - Free Specialty Training: Navy funded Webb's 3-year USC prosthodontics residency Continued receiving full salary, BAH, and bonuses—zero out-of-pocket costs FTOS (Full-Time Out-Service) allows civilian residency attendance Competitive annual program—check BUMED notices for available slots Strategic GI Bill Transfers: Webb transferred 15 months of GI Bill to his wife She completed UCLA nurse practitioner program debt-free Still has 15 months remaining for kids' education Transfer requires 4-year commitment—sign paperwork strategically Career Highlights: Temple University → Columbia DDS → O3 commission (2015) San Diego (AEGD) → Port Hueneme/Okinawa (Seabees, 2 deployments) → Key West → LA (USC residency) → Pearl Harbor Wife completed NP degree concurrent with his residency while caring for one-year-old Key Takeaways Military Medicine Benefits Add Up Fast: TRICARE coverage during school and career Active duty time counting toward retirement during education PSLF potential for massive loan forgiveness Specialty training fully funded (DUIN) GI Bill transfers for spouse education No pressure to over-treat patients for profit Civilian vs Military Prosthodontist Pay: Civilian side approximately 2X on paper But when factoring TRICARE, BAH, pension, education benefits—much closer Some civilian practices sacrifice autonomy for high volume/pay Military provides genuine patient care without profit motive Critical Actions: Apply for both HSCP and HPSP if pursuing military medicine Consolidate all student loans to federal direct loans immediately Enroll in PSLF and never miss payments Join Facebook group: "Public Service Loan Forgiveness Program Support" (216K members) Sign GI Bill transfers concurrent with existing obligations Resources Mentioned Kate Horrell's episodes - GI Bill expert (new book: "College Planning for Military Families") Dr. Pritish Sahoo episode - Army medicine path MMM Podcast #181 PSLF Facebook Group - "Public Service Loan Forgiveness Program Support" Naval Postgraduate Dental School (Bethesda) BUMED annual DUIN notices Who This Is For Pre-med/dental students considering military service, active duty members interested in medical careers, medical officers with student debt, anyone pursuing PSLF, families planning GI Bill transfers, or those comparing military vs civilian healthcare compensation.

Sign up to https://addednutrition.comfor $10 credit when we launch Added Sleep.For those interested in joining the Right Brain Reset community jump on at https://rightbrainresetters.comIn this episode, Stephen Martin discusses his journey with sleep supplements, his health goals, and the concept of setting ambitious targets. He shares insights on the development of his sleep supplements, the challenges of weight loss, and the importance of visualizing success. Stephen emphasizes the need for motivation and the impact of ADHD on his journey, while encouraging listeners to set unreasonable goals for themselves.TakeawaysI've been focusing on sleep supplements for the last few months.Testing sleep supplements has shown promising results with sleep scores in the 80s.Keto can negatively impact sleep, but I'm still achieving good scores.The journey of weight loss is often non-linear and challenging.Setting a 10X goal can be more motivating than a 2X goal.Visualizing success helps in achieving health goals.Cortisol levels can affect sleep quality and motivation.Engaging with mothers who struggle with sleep can guide product development.It's important to find a balance between relaxation and motivation with supplements.Setting unreasonable goals can lead to unexpected success.Sleep supplements, health goals, weight loss, ADHD, dyslexia, 10X goals, motivation, keto, cortisol, mindfulness, adults with dyslexia, support for adults.Join the clubrightbrainresetters.comGet 20% off your first orderhttps://addednutrition.comIf you want to find out more visit:⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠truthaboutdyslexia.com⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Join our Facebook Group⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠facebook.com/groups/adultdyslexia⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠

In this episode, CJ sits down with Brandon Sullivan, CFO at 2X, to unpack one of the most enduring tensions in business — the uneasy relationship between finance and marketing. From the myth of clean ROI to the chaos of martech spend, Brandon explains why measuring marketing impact is far harder than most CFOs think, and how spreadsheet logic can lead to bad decisions. He shares what it's like to run finance inside a 1,200-person marketing org, why cutting too deep in downturns can backfire, and what it takes to actually bridge the gap between teams that speak different languages. Along the way, he reveals lessons from scaling 2X across time zones, building global reporting rhythms, and redefining how finance and marketing can finally pull in the same direction.—LINKS:Brandon Sullivan on LinkedIn: https://www.linkedin.com/in/brandonsullivan2x/2X: https://2x.marketing/CJ on X (@cjgustafson222): https://x.com/cjgustafson222Mostly metrics: https://www.mostlymetrics.com—RELATED EPISODES:From Facebook's Hypergrowth to Daffy's Disruption: A CFO's Playbook for Saying Yes—TIMESTAMPS:(00:00:00) Preview and Intro(00:02:28) Sponsor – Aleph | Rillet | Fidelity Private Shares(00:05:55) Behind Enemy Lines: Finance Meets Marketing(00:07:00) Why CFOs and CMOs Clash(00:08:12) The Myth of Marketing ROI(00:10:19) Why Marketing Is So Hard to Measure(00:11:23) The Single Source of Truth Problem(00:15:29) Sponsor – Mercury | RightRev | Tipalti(00:19:35) The Three Buckets of Marketing Spend(00:21:26) The Long-Term Cost of Cutting Program Spend(00:23:27) How AI and ChatGPT Are Changing Marketing Attribution(00:25:43) Building a Modern Finance Team(00:27:55) The First-Time CFO Learning Curve(00:31:05) From Solo Operator to Scaled Finance Org(00:32:41) Why Weekly Reporting Beats Monthly Reviews(00:40:10) Working with Private Equity Partners(00:43:43) The Founding Story of 2X(00:48:12) Running a Global Team Across Time Zones(00:54:00) Long-Ass Lightning Round(00:57:00) Advice to Younger Self(00:58:58) Finance Stack and Craziest Expense Story(00:59:58) Credits and Sign-Off—SPONSORS:Aleph automates 90% of manual, error-prone busywork, so you can focus on the strategic work you were hired to do. Minimize busywork and maximize impact with the power of a web app, the flexibility of spreadsheets, and the magic of AI. Get a personalised demo at https://www.getaleph.com/runRillet is the AI-native ERP modern finance teams are switching to because it's faster, simpler, and 100% built for how teams operate today. See how fast your team can move. Book a demo at https://www.rillet.com/metricsFidelity Private Shares is the all-in-one equity management platform that keeps your cap table clean, your data room organized, and your equity story clear—so you never risk losing a fundraising round over messy records. Schedule a demo at https://www.fidelityprivateshares.com and mention Mostly Metrics to get 20% off.Mercury is business banking built for builders, giving founders and finance pros a financial stack that actually works together. From sending wires to tracking balances and approving payments, Mercury makes it simple to scale without friction. Join the 200,000+ entrepreneurs who trust Mercury and apply online in minutes at https://www.mercury.comRightRev automates the revenue recognition process from end to end, gives you real-time insights, and ensures ASC 606 / IFRS 15 compliance—all while closing books faster. For RevRec that auditors actually trust, visit https://www.rightrev.com and schedule a demo.Tipalti automates the entire payables process—from onboarding suppliers to executing global payouts—helping finance teams save time, eliminate costly errors, and scale confidently across 200+ countries and 120 currencies. More than 5,000 businesses already trust Tipalti to manage payments with built-in security and tax compliance. Visit https://www.tipalti.com/runthenumbers to learn more.#RunTheNumbersPodcast #FinanceVsMarketing #CFOInsights #MarketingROI #BusinessStrategy This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit cjgustafson.substack.com

Ever notice how big goals melt into "some day land" when the day gets messy?  On today's episode, we break down a simple, evidence-backed tool that turns “I should” into “I did,” replacing fragile motivation with clear cues and automatic actions. Instead of relying on willpower, we show how to script your behavior like software: a specific trigger, a concrete next step, and a defined finish line that delivers a quick reward your brain actually remembers.  Who does what, when, where, how often, and with whom?  A fundamental question to answer if you want to get good at programming your brain for challenging, consistent action.  You'll hear a practical running example that moves from vague hopes to precise routines: when to act, what to wear, where to go, and how to know you're done. We layer in environment design to remove hidden friction and temptation bundling to make new habits feel rewarding right away. The goal is less decision-making in the moment and more doing on cue.  Then we add the secret amplifier: WOOP—Wish, Outcome, Obstacle, Plan. By naming likely blockers upfront - low energy, surprise tasks, bad weather - and writing alternative if-then plans for each, you keep momentum even when the day doesn't cooperate. You'll learn how to apply the same structure to leadership, feedback, learning, and communication, so your next move is already decided when it matters. Fewer negotiations with yourself, more consistent action, and a system that sticks.  If you're ready to trade hope for a reliable plan, press play and build your first brain program today!  3-minute blog this episode is based on: The simple trick that 2X your chances of doing what you said you would. Programming your brain to follow through 101  Text Me Your Thoughts and IdeasSupport the showBrought to you by Angela Shurina Behavior-First, Executive, Leadership and Optimal Performance Coach 360, Change Leadership & Culture Transformation Consultant

In this electrifying episode, Joseph sits down with Austin Armstrong — a digital juggernaut whose journey from relentless content creator to AI visionary has reshaped the marketing landscape. With over 6,000 videos and billions of views under his belt, Austin shares the mindset, strategy, and soul behind his meteoric rise.From founding Syllaby, the AI platform revolutionizing video creation, to co-launching AI Marketing World, Austin is not just riding the wave of innovation — he's building it. Tune in as we explore how creators can harness AI to scale their voice, deepen their impact, and build legacy in the age of algorithms.How Austin built a multi-platform empire with billions of viewsThe secret to consistent, high-impact content creationWhy AI is the future of storytelling — and how to use it nowThe origin story of Syllaby and its mission to empower creatorsBehind the scenes of AI Marketing World and what's next for the industryAustin Armstrong is a lifelong digital marketer, keynote speaker, 2X 7-figure entrepreneur, and host of the BusinessTok podcast. As CEO of Syllaby and co-founder of AI Marketing World, Austin is leading the charge in AI-powered content creation. His work has earned him millions of followers and billions of views across every major social platform. He's passionate about sharing what works — and helping creators turn strategy into scale.Website: syllaby.ioPodcast: BusinessTokSocial: @AustinArmstrong on all platforms

Back in June, Chase refreshed its personal Sapphire Reserve card and introduced the Chase Sapphire Reserve Business card, complete with highest ever annual fees for rewards cards. Not to be outdone, American Express quickly followed with its own updates to the personal and business Platinum Cards. Now that the details are here, it's time to look at what's changed and what it means for cardholders. In this episode, I'm joined by Kelly, the Points and Miles Doc to walk through the Amex Platinum cards refresh. We cover the higher annual fees, the new credits, and why the personal Platinum still struggles with bonus categories. You'll also hear our reactions to the removal of the 35% rebate on the business Platinum, the addition of a $600 hotel credit, and the new 2X earning on large purchases over $5,000. We share our thoughts on whether the $895 annual fee on the personal Platinum makes sense, how the new benefits are user-dependent, and why the business Platinum refresh feels more useful for high spenders. Get full show notes and transcript: https://pointmetofirstclass.com/amex-platinum-refresh-2025/ Want to shape the show? Take the Point Me To First Class listener survey and share what you love and want more of! https://docs.google.com/forms/d/e/1FAIpQLSeAPfb3wIaphMn_NoQzm_fljydsivTELQwh7pYoxrI2uTFoKQ/viewform?usp=header Eager to learn the secrets of award travel so that you can turn your expenses into unforgettable experiences? Join the Points Made Easy course waitlist here: https://pointmetofirstclass.com/pointsmadeeasy

You know how it goes—you start the year full of ideas, goals, and good intentions…yet somehow your to-do list keeps growing, and your big projects never get done. You wonder if you'll ever break free from procrastination and actually see results?In this episode, we dive into the top five procrastination triggers that are silently stealing your time, focus, and profits—and I show you how to fix each one with practical, faith-driven strategies. If you've been working hard but not seeing the growth, momentum, or impact you want, this is your blueprint to 10X your productivity and 2X (or more!) your profits in the next 90 days.Let's kick procrastination to the curb, reclaim your time, and step fully into the steward role God has called you to—so you can grow your business, expand your impact, and finally get the results you've been chasing.Grab access to the 10X Productivity + 2X Profits in the Next 90 Days Masterclass https://redeemhertime.com/10XLearn more (or jump in) CEO Focus, our 12-week coaching + accountability program to create 10X results before the end of the year https://redeemhertime.com/focus-infoYOU. HAVE. TIME. LissaP.S. Come join the conversation inside the REDEEM Her Time Community redeemhertime.com/communityP.P.S. Wanna get back 5 hours THIS week? Binge the Productive + Profitable C.E.O. Private Podcast to discover the secret to productivity is not in your to-do list and how one simple shift can double your results. Walk away with more margin, less to-do's and exponential growth! (P.S. I'll share the secret to 10,000% productivity increase…no that's not a typo!)P.P.S. Better yet, come join me inside CEO Focus to scale up your results (aka reach + revenue) in just 12 weeks! Let's get you more leads, sign more clients, create more cashflow...and SCALE this business God put on your heart!