Podcasts about ui ux

SEO job seekers face intense competition in today's market. Nick LeRoy, founder of SEOjobs.com, shares insights from his comprehensive industry report on the most in-demand SEO skills. Data analytics, technical SEO, and stakeholder management correlate most strongly with higher salaries, while AI expertise and UI/UX knowledge are increasingly sought after by employers. LeRoy recommends candidates develop a clear point of view on AI implementation and focus on building skills they can control to stand out in application processes.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

JOIN THE VALOR COFFEE COMMUNITY – Courses, Exclusive Videos, PDFs, Spreadsheets and more:⁠ https://community.valor.coffee/landing-page?utm_source=spotify&utm_campaign=ep138Thanks for listening, following/subscribing, giving us a good review, and sharing with your friends on social media. It goes a long way!We had the pleasure of sitting down again with our buddy Kent from LocalEyes, our go-to SEO expert and a wizard behind the curtain when it comes to how coffee companies can actually win on Google. Whether you're running a cart, a café, or selling beans online, this episode is for you. We define key SEO terms (H1s, meta descriptions, and more), walk through real listener-submitted websites, and share instant improvements that can help your pages rank better today. Kent also gives us a sneak peek into the brand new SEO course he filmed for our Valor Coffee Community. It's packed with insight, as we roast some websites (gently) and break down exactly what coffee companies are doing right and wrong. Whether you're DIY-ing your Squarespace site or working with an agency, this is one you don't want to miss.Kent's Socials: https://taplink.cc/kent.fyi*If you purchase something through one of our links, we may be entitled to a share of the sale*Buy Valor Coffee: ⁠https://valor.coffee/shop⁠Watch on Youtube: ⁠https://youtube.com/valorcoffee16⁠Want to become a Wholesale Partner? Email us at wholesale@valor.coffee to set up an account!Want to send us coffee? Have a question you want to answer on the show? Send us an email to info@valor.coffeeWe're partnered with Clive to bring you sweet deal at a discounted rate! Use Discount Code VALOR5 at checkout for 5% off Mahlkonig, Anfim and Eureka products!Shop Clive products here: ⁠https://clivecoffee.com?sca_ref=5315485.6axWuRlcEr⁠Want to get your business in front of more people? We partnered with Local Eyes Growth to grow our business through SEO and the results have been incredible. Local Eyes is offering a FREE backlink ($300 value) to Valor Coffee Podcast listeners who partner through our exclusive link. Visit ⁠https://localeyesgrowth.com/valor⁠ to get the ball rolling!Follow the Valor Coffee Podcast on Instagram: ⁠http://instagram.com/valorcoffeepod⁠Follow Valor on Instagram: ⁠http://instagram.com/valor.coffee⁠Subscribe to Riley's YouTube Channel: ⁠https://youtube.com/@rileywestbrook⁠Follow Riley:  ⁠https://instagram.com/rileywestbrook⁠Follow Ross: ⁠https://instagram.com/rosswalters⁠Follow Ethan's Parody Account:  ⁠https://instagram.com/ethanrivers77700:00:00 Start00:00:33 Intro 00:06:30 What is SEO? 00:10:10 H1? 00:14:19 UI/UX? 00:17:13 3 Things that make your website rank higher 00:27:07 How much is SEO Set It and Forget It? 00:29:08 Local vs E-Comerce SEO 00:31:21 Toxic Back-links?!?!?!?!?!?!? 00:32:43 Website SHRED (buckle up) 00:40:00 Social Proof 00:45:23 Google Busniess Profile 00:46:22 The PERFECT Google Review 00:48:16 Website #2 00:59:54 Website 3 (the reckoning)

Welcome back to Your Drone Questions. Answered. In this episode, we're diving into the exciting world of tethered drones—how they're being used today and where they're headed in the future.We cover:What tethered drones are and how they differ from traditional UAVsLegal and regulatory considerations in the U.S. as of Q1 2025The main benefits of tethering (continuous power, data streaming, mobility)Real-world use cases: public safety, temporary security, event coverage, and broadcastFreefly's innovative Flying Sun product for mobile aerial lightingChallenges and technical lessons from building tethered drone systemsThe future of tether tech, including UI/UX advancements and industry-specific solutions

In this episode, I'm once again joined by Daniel Sabanés Bové for a deep dive into one of the most impactful tools for statisticians working with data visualization—R-Shiny. We explore how interactive data visualizations can help you iterate faster, collaborate better across functions, and focus more on the actual scientific questions rather than just coding. Daniel shares some excellent examples from clinical trials and gives practical tips on how to avoid common pitfalls when building Shiny apps. Whether you're designing your first app or maintaining a more complex one, you'll find plenty of value in this conversation—from best practices around UI/UX design to strategies for modular development and testing.

In this episode of The Creative Shit Show, we dive deep into surviving—and thriving—in today's wild economic ride. From the feast-or-famine freelancing grind and pricing pressures to standing out with a killer portfolio, we've got you covered. We unpack how to niche down, turn past clients into a referral goldmine, and position your work to show real value. Plus, we tackle AI's big shake-up—Midjourney, Canva, and beyond—and how designers can lean into strategy, intuition, and storytelling to stay ahead. Tune in for raw talk on networking, portfolio power moves, and the skills (hello, UI/UX and brand strategy) that'll keep you in demand. Chaos? Sure. Opportunity? Hell yes. Listen now.

On the 329th episode of You Know I'm Right, Nick Durst and Joe Calabrese are joined by Harlem Globetrotter, TNT Lister to discuss:- Growing up in Colorado Springs?- Started playing basketball in middle school while also excelling in volleyball, track and field and setting Colorado state records in both the long jump and triple jump- Started collegiate career at New Mexico before transferring to Temple. Coached under the legendary Dawn Staley; What is she like? - In 2011 becoming the first female Harlem Globetrotter since 1993. What was the process of becoming a Globetrotter?- Side hobbies include Art and UI/UX designing- What were her original career aspirations?- Globetrotters are constantly performing all over the country and world. How does traveling affect personal lives?- Favorite cities she has traveled to? - Favorite people she had the chance to meet? - Fun experiences were made possible by being a Harlem Globetrotter- You Know I'm Right moment 

Discover the secrets to building and scaling a bootstrapped product-led business to seven-figure success. Our guest is Elie Khoury, the founder and CEO of Woopra, a company specializing in customer journey and product analytics.  Elie shares the nuances of when a product-led model makes sense (and when it doesn't), emphasizing the importance of swiftly establishing the perception of value. He also sheds light on AI's role in driving product-led growth strategies. Key Takeaways: [01:40] Strategic product-led evolution [07:50] AI Integration for quick value [15:00] AI as the next UI/UX iteration [18:00] Data control and AI [20:20] Reflecting on mistakes and learnings [28:45] Future of AI and product-led businesses About Elie Khoury: Elie is a product-first CEO who believes innovation and user experience are, above all else, the keys to creating great companies. Sales, marketing, recruiting, and every other aspect of a company is meaningless without an exceptional product. He co-founded Woopra, Inc., which Appier acquired in 2022.  Links:  Elie Khoury | LinkedIn

In this conversation, Krish Palaniappan reviews the Panera Bread mobile app, focusing on its user interface, experience, and functionality. He discusses the importance of user loyalty and how it affects app usage. Throughout the review, he identifies various bugs, issues with the app's workflow, and areas for improvement, particularly in terms of speed and user interaction. The conversation highlights the significance of a well-designed app in enhancing customer satisfaction and loyalty. In this conversation, Krish Palaniappan reviews the Panera app, discussing various aspects such as coffee subscriptions, user experience challenges, customization features, rewards and offers, and overall app navigation. He highlights the importance of user interface design and the need for improvements in speed and personalization. The conversation culminates in a reflection on the app's usability and the feedback process. Snowpal Products Backends as Services on ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠AWS Marketplace⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Mobile Apps on ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠App Store⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ and ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Play Store⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Web App⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Education Platform⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ for Learners and Course Creators

In questo episodio di **Techno Pillz**, Alex Raccuglia ci guida attraverso il suo frenetico flusso di coscienza, condividendo le sue riflessioni su app, icone e la quotidianità. Tra aneddoti personali e digressioni divertenti, Alex parla della sua insoddisfazione con le attuali applicazioni per la lista della spesa e condivide l'idea di una nuova applicazione che potrebbe migliorare l'esperienza di acquisto. Tra le sue riflessioni spicca il sogno di utilizzare l'intelligenza artificiale per generare icone personalizzate e risolvere problemi di interfaccia utente.

Genevieve Hayes Consulting Episode 54: The Hidden Productivity Killer Most Data Scientists Miss Why do some data scientists produce results at a rate 10X that of their peers?Many data scientists believe that better technologies and faster tools are the key to accelerating their impact. But the highest-performing data scientists often succeed through a different approach entirely.In this episode, Ben Johnson joins Dr Genevieve Hayes to discuss how productivity acts as a hidden multiplier for data science careers, and shares proven strategies to dramatically accelerate your results.This episode reveals:Why lacking clear intention kills productivity — and how to ensure every analysis drives real decisions. [02:11]A powerful “storyboarding” framework for turning vague requests into actionable projects. [09:51]How to deliver results faster using modern data architectures and raw data analysis. [13:19]The game-changing mindset shift that transforms data scientists from order-takers into trusted strategic partners. [17:05] Guest Bio Ben Johnson is the CEO and Founder of Particle 41, a development firm that helps businesses accelerate their application development, data science and DevOps projects. Links Connect with Ben on LinkedIn Connect with Genevieve on LinkedInBe among the first to hear about the release of each new podcast episode by signing up HERE Read Full Transcript [00:00:00] Dr Genevieve Hayes: Hello and welcome to Value Driven Data Science, the podcast that helps data scientists transform their technical expertise into tangible business value, career autonomy, and financial reward. I’m Dr. Genevieve Hayes, and today I’m joined by Ben Johnson, CEO and founder of Particle 41, a development firm that helps businesses accelerate their application development, data science, and DevOps projects.[00:00:30] In this episode, we’ll discuss strategies for accelerating your data science impact and results without sacrificing technical robustness. So get ready to boost your impact. Earn what you’re worth and rewrite your career algorithm. Ben, welcome to the show.[00:00:48] Ben Johnson: Yeah, thank you for having me.[00:00:50] Dr Genevieve Hayes: One of the most common misconceptions I see about data scientists is the mistaken belief that their worth within a business is directly linked to the technical complexity of the solutions they can produce.[00:01:04] And to a certain extent, this is true. I mean, if you can’t program, fit a model, or perform even the most basic statistical analysis, realistically, your days as a data scientist are probably numbered. However, while technical skills are certainly necessary to land a data science job, The data scientists I see making the biggest impact are the ones who are not necessarily producing the most complex solutions, but who can produce solutions to the most pressing business problems in the shortest possible time.[00:01:41] So in that sense, productivity can be seen as a hidden multiplier for data science careers. Ben, as the founder of a company that helps businesses accelerate their data science initiatives, it’s unsurprising that one of your areas of interest is personal productivity. Based on your experience, What are some of the biggest productivity killers holding data scientists back?[00:02:11] Ben Johnson: I don’t know for others. I know for myself that what kills my productivity is not having an intention or a goal or a direct target that I’m trying to go for. So when we solve the science problems, we’re really trying to figure out, like, what is that hunt statement or that question that key answer you know, the question that will bring the answer.[00:02:33] And also, what is the right level of information that would handle that at the asker’s level? So the ask is coming from a context or a person. And so we can know a lot. If that person is a fellow data scientist, then obviously we want to give them data. We want to answer them with data. But if that’s a results oriented business leader, then we need to make sure that we’re giving them information.[00:02:57] And we. Are the managers of the data, but to answer your question, I think that the biggest killer to productivity is not being clear on what question are we trying to answer?[00:03:08] Dr Genevieve Hayes: That, resonates with my own experience. One of the things I encountered early in my data science career was well, to take a step back. I originally trained as an actuary and worked as an actuary, and I was used to the situation where your boss would effectively tell you what to do. So, go calculate, calculate.[00:03:28] premiums for a particular product. So when I moved into data science, I think I expected the same from my managers. And so I would ask my boss, okay, what do you want me to do? And his answer would be something like, Oh here’s some data, go do something with it. And you can probably imagine the sorts of solutions that we got myself and my team would come up with something that was a model that looks like a fun fit[00:03:59] and those solutions tended to go down like a lead balloon. And it was only after several failures along those lines that it occurred to me, , maybe we should look at these problems from a different, point of view and figure out what is it that the senior management actually want to do with this data before starting to build a particular model from it.[00:04:24] Ben Johnson: Yeah. What decision are you trying to make? Just kind of starting with like the end in mind or the result in mind, I find in any kind of digital execution there are people who speak results language and there are people who speak solutions language. And when we intermix those two conversations,[00:04:41] it’s frustrating, it’s frustrating for the solution people to be like, okay, great. When are you going to give it to me? And it’s frustrating for the business folks, like hey, when am I going to get that answer when we want to talk about the solution? So I found like bifurcating like, okay, let’s have a results or planning discussion separate from a solution and asking for that right to proceed.[00:05:02] In the way that we communicate is super helpful., what your share reminds me of is some of the playbooks that we have around data QA, because in those playbooks, we’re doing analysis just for analysis sake. I feel like we’re looking for the outliers.[00:05:18] Okay. So if we look at this metric, these are the outliers. And really what we’re doing is we’re going back to the, originators of the data and say, like, sanity, check this for us. We want to run through a whole set of sanity checks to make sure that the pipeline that we’re about to analyze makes sense.[00:05:34] Are there any other exterior references that we can compare this to? And I do know that the first time we were participating in this concept of data QA, not having that playbook Was a problem, right? Like, well, okay. Yeah, the data is there. It’s good. It’s coming in, but you know, to really grind on that and make sure that it was reflective of the real world was an important step.[00:05:57] Dr Genevieve Hayes: So QA, I take your meaning quality assurance here? Is that right?[00:06:02] Ben Johnson: Yes. That’s the acronym quality assurance, but testing and doing QA around your data pipelines.[00:06:09] Dr Genevieve Hayes: Okay, so I get it. So actually making sure the pipelines work. And if you don’t understand what is it that you’re looking for with regard to performance, then you can end up going off in the wrong direction. Is that correct?[00:06:23] Ben Johnson: So if you were analyzing sales data, you would want to make sure that your totals reflected the financial reports. You just want to make sure that what you’ve. Accumulated in your analysis environment is reflective of the real world. There’s nothing missing. It generally makes sense. We just haven’t introduced any problem in just the organizing and collection of the data.[00:06:45] Dr Genevieve Hayes: Yeah, yeah. From my background in the insurance industry, those were all the sorts of checks that we used to have to do with the data as well.[00:06:52] Ben Johnson: Well, and oftentimes the folks that are asking these hard questions, they’re not asking the questions because they have any idea how clean the data they’ve collected. They just think there might be a chance. It’s like the dumb and dumber, you know, okay, so we think we have a chance, you know anyways awful movie reference, but they think that there might be a possibility that the answer to all of their questions or this hard decision that they need to make regularly is somewhere in that pile of stuff.[00:07:21] What we call a QA analysis Also is checking the data’s integrity if it’s even capable to solve the problem. So I think that’s a great first step and that sometimes that’s just kind of analysis for analysis sake or feels that way.[00:07:37] Dr Genevieve Hayes: One of the things you’ve touched on several times is the idea of the results oriented people and the solutions oriented people and I take it with the solutions oriented people, you’re talking about people like the data scientists. When the data scientists are talking to those results oriented people, Is there a framework that they can follow for identifying what sorts of results those results oriented people are looking for?[00:08:08] Ben Johnson: It’s very similar in the way that you approach like a UI UX design. We’ve taken kind of a storyboard approach, storyboard approach to what they want to see. Like, okay, What is the question? What are you expecting the answer to be? Like, what do you think would happen?[00:08:25] And then what kind of decisions are you going to do as a result of that? And you had some of those things as well. But kind of storyboarded out what’s the journey that they’re going to take, even if it’s just a logical journey through this data to go affect some change.[00:08:41] Dr Genevieve Hayes: So do you actually map this out on a whiteboard or with post it notes or something? So literally building a storyboard?[00:08:48] Ben Johnson: Most of the time , it’s bullets. It’s more of like written requirements. But when we think of it, we think of it , in a storyboard and often it’ll turn into like a PowerPoint deck or something because we’re also helping them with their understanding of the funding of the data science project, like connecting ROI and what they’re trying to do.[00:09:10] So yeah. Yeah, our firm isn’t just staff augmentation. We want to take a larger holistic ownership approach of the mission that we’re being attached to. So this is critical to like, okay, well, we’re going to be in a data science project together. Let’s make sure that we know what we’re trying to accomplish and what it’s for.[00:09:29] Because, you know, if you’re working on a complex project and six months in everybody forgets Why they’ve done this, like why they’re spending this money oftentimes you need to remind them and, show them where you are in the roadmap to solving those problems.[00:09:44] Dr Genevieve Hayes: With the storyboard approach, can you give me an example of that? Cause I’m still having a bit of trouble visualizing it.[00:09:51] Ben Johnson: Yeah, it’s really just a set of questions. What are you trying to accomplish? What do you expect to have happen? Where are you getting this data? It’s , just a discovery survey that we are thinking about when we’re establishing the ground rules of the particular initiative.[00:10:08] Dr Genevieve Hayes: And how do you go from that storyboard to the solution?[00:10:12] Ben Johnson: That’s a great question. So the solution will end up resolving in whatever kind of framework we’re using data bricks or whatever it’ll talk about the collection, the organization and the analysis. So we’ll break down how are we going to get this data is the data already in a place where we can start messing with it.[00:10:32] What we’re seeing is that a lot of. And I kind of going deep on the collection piece because that’s I feel like that’s like 60 percent of the work. We prefer a kind of a lake house type of environment where we’ll just leave a good portion of the data in its raw original format, analyze it.[00:10:52] Bring it into the analysis. And then, of course, we’re usually comparing that to some relational data. But all that collection, making sure we have access to all of that. And it’s in a in a methodology and pipelines that we can start to analyze it is kind of the critical first step. So we want to get our hands around that.[00:11:10] And then the organization. So is there, you know, anything we need to organize or is a little bit messy? And then what are those analysis? Like, what are those reports that are going to be needed or the visibility, the visualizations that would then be needed on top of that? And then what kind of decisions are trying to be made?[00:11:28] So that’s where the ML and the predictive analytics could come in to try to help assist with the decisions. And we find that most data projects. Follow those, centralized steps that we need to have answers for those.[00:11:43] Dr Genevieve Hayes: So a question that might need to be answered is, how much inventory should we have in a particular shop at a particular time? So that you can satisfy Christmas demand. And then you’d go and get the data about[00:11:59] Ben Johnson: Yeah. The purchase orders or yeah. Where’s the data for your purchase orders? Do you need to collect that from all your stores or do you already have that sitting in some place? Oh, yeah. It’s in all these, you know, disparate CSVs all over the place. We just did a. project for a leading hearing aid manufacturer.[00:12:18] And most of the data that they wanted to use was on a PC in the clinics. So we had to devise a collection mechanism in the software that the clinics were using to go collect all that and regularly import that into a place where We could analyze it, see if it was standardized enough to go into a warehouse or a lake.[00:12:39] And there were a lot of standardization problems, oddly, some of the clinics had kind of taken matters into their own hands and started to add custom fields and whatnot. So to rationalize all of that. So collection, I feel like is a 60 percent of the problem.[00:12:54] Dr Genevieve Hayes: So, we’ve got a framework for increasing productivity by identifying the right problem to solve, but the other half of this equation is how do you actually deliver results in a rapid fashion. because, as you know, A result today is worth far more than a result next year. What’s your advice around getting to those final results faster?[00:13:19] Ben Johnson: So That’s why I like the lake house architecture. We’re also finding new mechanisms and methodology. Some, I can’t talk about where they’re rather than taking this time to take some of the raw data and kind of continuously summarize it. So maybe you’re summarizing it and data warehousing it, but we like the raw data to stay there and just ask it the questions, but it takes more time and more processing power.[00:13:47] So what I’m seeing is we’re often taking that and organizing it into like a vector database or something that’s kind of right for the analysis. We’re also using vector databases in conjunction with AI solutions. So we’re asking the, we’re putting, we’re designing the vector database around the taxonomy, assuming that the user queries are going to match up with that taxonomy, and then using the LLM to help us make queries out of the vector database, and then passing that back to the LLM to test.[00:14:15] Talk about it to make rational sense about the story that’s being told from the data. So one way that we’re accelerating the answer is just to ask questions of the raw data and pay for the processing cost. That’s fast, and that also allows us to say, okay, do we have it?[00:14:32] Like, are we getting closer to having something that looks like the answer to your question? So we can be iterative that way, but at some point we’re starting to get some wins. In that process. And now we need to make those things more performant. And I think there’s a lot of innovation still happening in the middle of the problem.[00:14:51] Dr Genevieve Hayes: Okay, so you’re starting by questioning the raw data. Once you realize that you’re asking the right question and getting something that the results oriented people are looking for, would you then productionize this and start creating pipelines and asking questions of process data? Yeah.[00:15:11] Ben Johnson: Yeah. And we’d start figuring out how to summarize it so that the end user wasn’t waiting forever for an answer.[00:15:17] Dr Genevieve Hayes: Okay, so by starting with the raw data, you’re getting them answers sooner, but then you can make it more robust.[00:15:26] Ben Johnson: That’s right. Yes. More robust. More performant and then, of course, you could then have a wider group of users on the other side consuming that it wouldn’t just be a spreadsheet. It would be a working tool.[00:15:37] Dr Genevieve Hayes: Yeah, it’s one of the things that I was thinking about. I used to have a boss who would always say fast, cheap and good, pick two. Meaning that, you can have a solution now and it can be cheap, but it’s going to come at the cost of And it sounds like you focus on Fast and cheap first, with some sacrifice of quality because you are dealing with raw data.[00:16:00] But then, once you’ve got something locked in, you improve the quality of it, so then technical robustness doesn’t take a hit.[00:16:09] Ben Johnson: Yeah, for sure. I would actually say in the early stage, you’re probably sacrificing the cheap for good and fast because you’re trying to get data right off the logs, right off your raw data, whatever it is. And to get an answer really quickly on that without having to set up a whole lot of pipeline is fast.[00:16:28] And it’s it can be very good. It can be very powerful. We’ve seen many times where it like answers the question. You know, the question of, is that data worth? Mining further and summarizing and keeping around for a long time. So in that way, I think we addressed the ROI of it on the failures, right.[00:16:46] Being able to fail faster. Oh yeah. That data is not going to answer the question that we have. So we don’t waste all the time of what it would have been to process that.[00:16:55] Dr Genevieve Hayes: And what’s been the impact of taking this approach for the businesses and for the data scientists within your organisation who are taking this approach?[00:17:05] Ben Johnson: I think it’s the feeling of like. of partnership with us around their data where we’re taking ownership of the question and they’re giving us access to whatever they have. And there’s a feeling of partnership and the kind of like immediate value. So we’re just as curious about their business as they are.[00:17:27] And then we’re working shoulder to shoulder to help them determine the best way to answer those questions.[00:17:32] Dr Genevieve Hayes: And what’s been the change in those businesses between, before you came on board and after you came on board?[00:17:39] Ben Johnson: Well, I appreciate that question. So with many of the clients, they see that, oh, this is the value of the data. It has unlocked this realization that I, in the case of the hearing aid manufacturer that we work with, they really started finding that they could convert more clients and have a better brand relationship by having a better understanding of their data.[00:18:03] And they were really happy that they kept it. You know, 10 years worth of hearing test data around to be able to understand, their audience better and then turn that into. So they’ve seen a tremendous growth in brand awareness and that’s resulted in making a significant dent in maintaining and continuing to grow their market share.[00:18:26] Dr Genevieve Hayes: So they actually realize the true value of their data.[00:18:30] Ben Johnson: That’s right. And then they saw when they would take action on their data they were able to increase market share because they were able to affect people that truly needed to know about their brand. And like we’re seeing after a couple of years, their brand is like, you don’t think hearing aids unless you think of this brand.[00:18:48] So it’s really cool that they’ve been able to turn that data by really, Talking to the right people and sending their brand message to the right people.[00:18:56] Dr Genevieve Hayes: Yeah, because what this made me think of was one of the things I kept encountering in the early days of data science was a lot of Senior decision makers would bring in data scientists and see data science as a magic bullet. And then because the data scientists didn’t know what questions to answer, they would not be able to create the value that had been promised in the organization.[00:19:25] And the consequence after a year or two of this would be the senior decision makers would come to the conclusion that data science is just a scam. But it seems like by doing it right, you’ve managed to demonstrate to organizations such as this hearing aid manufacturer, that data science isn’t a scam and it can actually create value.[00:19:48] Ben Johnson: Absolutely. I see data sciences anytime that that loop works, right? Where you have questions. So even I have a small client, small business, he owns a glass manufacturing shop. And. The software vendor he uses doesn’t give him a inexpensive way to mark refer like who his salespeople are,[00:20:09] so he needs a kind of a salesperson dashboard. What’s really cool is that his software gives them, they get full access to a read only database. So putting a dashboard on top of. His data to answer this salesperson activities and commissions and just something like that. That’s data science.[00:20:28] And now he can monitor his business. He’s able to scale using his data. He’s able to make decisions on how many salespeople should I hire, which ones are performing, which ones are not performing. How should I pay them? That’s a lot of value to us as data scientists. It just seems like we just put a dashboard together.[00:20:46] But for that business, that’s a significant capability that they wouldn’t have otherwise had.[00:20:52] Dr Genevieve Hayes: So with all that in mind, what is the single most important change our listeners could make tomorrow? to accelerate their data science impact and results.[00:21:02] Ben Johnson: I would just say, be asking that question, Like what question am I trying to answer? What do you expect the outcome to be? Or what do you think the outcome is going to be? So that I’m not biased by that, but I’m sanity checking around that. And then what decisions are you going to make as a result?[00:21:19] I think always having that like in the front of your mind would help you be more consultative and help you work according to an intention. And I think that’s super helpful. Like don’t let the client Or the customer in your case, whether that be an internal person give you that assignment, like, just tell me what’s there.[00:21:38] Right. I just want insights. I think the have to push our leaders to give us a little more than that.[00:21:46] Dr Genevieve Hayes: the way I look at it is, don’t treat your job as though you’re someone in a restaurant who’s just taking an order from someone.[00:21:53] Ben Johnson: Sure.[00:21:54] Dr Genevieve Hayes: Look at it as though you’re a doctor who’s diagnosing a problem.[00:21:58] Ben Johnson: Yeah. And the data scientists that I worked with that have that like in their DNA, like they just can’t move forward unless they understand why they’re doing what they’re doing have been really impactful. In the organization, they just ask great questions and they quickly become an essential part of the team.[00:22:14] Dr Genevieve Hayes: So for listeners who want to get in contact with you, Ben, or to learn more about Particle 41, what can they do?[00:22:21] Ben Johnson: Yeah, I’m on LinkedIn. In fact I love talking to people about data science and DevOps and software development. And so I have a book appointment link on my LinkedIn profile itself. So I’m really easy to get into a call with, and we can discuss whatever is on your mind. I also offer fractional CTO services.[00:22:42] And I would love to help you with a digital problem.[00:22:45] Dr Genevieve Hayes: And there you have it. Another value packed episode to help turn your data science skills into serious clout, cash, and career freedom. If you enjoyed this episode, why not make it a double? Next week, catch Ben’s value boost, a quick five minute episode where he shares one powerful tip for getting real results real fast.[00:23:10] Make sure you’re subscribed so you don’t miss it. Thanks for joining me today, Ben.[00:23:16] Ben Johnson: Thank you. It was great being here. I enjoyed it[00:23:19] Dr Genevieve Hayes: And for those in the audience, thank you for listening. I’m Dr. Genevieve Hayes, and this has been value driven data science. The post Episode 54: The Hidden Productivity Killer Most Data Scientists Miss first appeared on Genevieve Hayes Consulting and is written by Dr Genevieve Hayes.

Send us a textWelcome to this week's episode of The Digital Restaurant Podcast! Carl is joined by special guest Olga Lopategui, a leading expert in restaurant loyalty and digital engagement, to break down the latest innovations shaping the restaurant industry.⏱ [01:07] – Just Salad Gets $200M InvestmentWhat makes Just Salad's tech stack unique?How will this funding impact digital transformation in restaurants?Will they use the investment for expansion, technology, or both?⏱ [04:42] – Just Eat Takeaway's Acquisition by ProcessWhat does this mean for global food delivery consolidation?How does it compare to previous acquisitions like Grubhub?Could DoorDash face challenges in global expansion?⏱ [09:09] – The Digital Guest Experience & UX InnovationHow should restaurant UI/UX evolve for better ordering?Why should apps customize the interface for individual users?What lessons can restaurants learn from brands like Taco Bell's Veggie Mode?⏱ [14:19] – What Are Digital Twins & Why Do They Matter?How do digital twins work in the restaurant industry?Can virtual simulations replace traditional prototype testing?How might predictive maintenance reduce restaurant downtime?Additional Paper here⏱ [19:53] – Dutch Bros, Panda Express & Domino's on Mobile OrderingHow did Dutch Bros perfect their mobile app launch?What improvements are Panda and Domino's making?Why is mobile ordering crucial for customer loyalty and convenience?Support the show

いつも聴いてくださってありがとうございます。更新頻度を月1回にすることにしました（やりたい内容が出たら、臨時で出すかもしれません）。やって欲しい内容などあれば、リクエストしていただけたら収録しますので、いつものフォームまで！https://forms.gle/87KqdJcShis7tBaw8Twitterアカウント始めました！質問やコメントなど受け付けています！https://x.com/trycatch_fmSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Rebecca Shaddix, a seasoned marketer and go-to-market strategist, joins the show to share her expertise in driving revenue growth across industries like education, healthcare, and SaaS. As a Forbes contributor and thought leader, Rebecca brings a unique blend of data-driven marketing, empathetic leadership, and a keen understanding of the evolving marketing landscape.Key Topics Discussed:1. The Role of Empathetic Leadership in MarketingHow balancing high expectations with trust fosters a strong marketing team.The power of letting small tests and failures lead to big wins.Why leaders must step back and allow data, not just personal preferences, to drive marketing decisions.2. Data-Driven Decision Making & Testing StrategiesWhy marketers must test and iterate rather than rely on assumptions.The importance of product-market fit and refining strategy over time.A case study on how Rebecca's team unseated an industry competitor by leveraging differentiation and UI/UX improvements.3. The Impact of AI & Technology on MarketingHow AI is changing the way businesses approach marketing.The importance of training AI tools for better results instead of relying on generic prompts.Why founders and marketers must integrate AI thoughtfully to maintain authenticity.4. Scaling Marketing Efforts Without Losing FocusThe risk of growing too fast and diluting brand messaging.How to avoid the mistake of jumping into too many marketing channels at once.Why companies should focus on a few, well-executed strategies before expanding.5. Acquisition vs. Retention: The Key to Sustainable GrowthWhy retaining customers is four times more impactful than acquiring new ones.The dangers of short-term promotions and discount cycles.Strategies for building long-term customer loyalty and brand trust.6. What Founders Need to Know Before Hiring a MarketerWhy most startups don't need a CMO as their first marketing hire.How to determine whether to hire in-house or work with an agency.The importance of setting clear goals and defining success before bringing in external help.Key Takeaways for Marketers & Founders:For marketers: Differentiation in marketing takes effort—using AI, tools, and strategies effectively requires training and intentionality.For founders: Don't chase trends blindly; focus on the right hires, the right tools, and a clear strategic direction to grow sustainably.Connect with Rebecca Shaddix:LinkedInFollow us on Instagram: Uncomplicate it! (@uncomplicate__it) • Instagram photos and videos Follow us on YouTube: UncomplicatedMarketing - YouTube

UI design is one of the most overlooked yet crucial aspects of game development. In this episode of Bonfire Conversations, I sit down with Fernando Forero, the legendary UI designer behind The Witcher 3, Cyberpunk 2077, and Diablo 4. We break down what makes great UI/UX, how it shapes our gaming experience, and the biggest challenges in designing immersive interfaces.

AIによって広告を見ずに色々なことができるようになる。そうなったら広告はどう変わるんだろう？Twitterアカウント始めました！質問やコメントなど受け付けています！⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://twitter.com/trycatch_fm⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

↓pap!に関する記事はこちら(英語記事です)https://www.ycombinator.com/companies/papTwitterアカウント始めました！質問やコメントなど受け付けています！⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://twitter.com/trycatch_fm⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

赤いきつねのCMを炎上したことにしたクレーマーがいたようですが、企業側が取り合わなかった結果、いい状態になっているみたい？Twitterアカウント始めました！質問やコメントなど受け付けています！⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://twitter.com/trycatch_fm⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

未来では、親と同じ言語を使う必要が必ずしもないのでは？という思考実験をしてみた。Twitterアカウント始めました！質問やコメントなど受け付けています！⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://twitter.com/trycatch_fm⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

In this episode of Flying High with Flutter, we're joined by Vadym Grin, author of Emotional Digital Design and Head of Product Design at Atolls. Vadym shares insights from his book, discusses the design process, explores the role of developers in crafting great user experiences, and more! Whether you're a designer, developer, or simply curious about UI/UX, this episode is packed with valuable insights!

Twitterアカウント始めました！質問やコメントなど受け付けています！⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://twitter.com/trycatch_fm⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Quatre sujets au sommaire de l'actualité sur les startups à Taïwan dans Graine de Business cette semaine: - Gogoro dévoile son nouveau plan commercial jusqu'en 2028 après une année 2024 difficile - Appier le géant de la martech prend un virage IA encore plus marqué et continue son ascension fulgurante en rachetant une startup française - MetAI, les spécialistes de la transformation et de modélisation 3D par IA se développe et vise de nouveaux marchés pour 2025 - Phase la startup sudcoréenne spécialisée dans l'UI/UX sans programmation arrive à Taïwan

↓会話していた日経の記事。無料会員でも月1回無料で読めます。https://www.nikkei.com/article/DGXZQOUC304YK0Q5A130C2000000/Twitterアカウント始めました！質問やコメントなど受け付けています！⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://twitter.com/trycatch_fm⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Everyone knows AI is the hottest narrative right now. Next, it'll be the crossover between gaming and AI.Imagine an app where you could:- scroll through mobile games like TikTok- create and launch your own games with an easy to use AI in less than a day- speculate & own the games with an infinite token ecosystemNow stop imagining and listen to their founder, Chuck, on 100x Podcast show you exactly that!Speakers this episode:Matthew Walker: https://x.com/MatthewWalker_XCesar Martinez: https://x.com/100xCesarFarcade: https://x.com/Farcade_AIChuck: https://x.com/0xChuckstockOur Current Partners:GAM3S.GG: ⁠https://gam3s.gg/⁠Avalanche: ⁠https://x.com/avax⁠⁠Disclosures:As always, we want to stress that nothing in this is financial investment advice.We're obviously super into crypto. But that doesn't mean you should buy something just to get rich quick. Crypto is extremely risky. We've made money and lost money. Please do your own research and make your own financial decisions. Don't just copy influencers or creators.100x Podcast Partners are not endorsements to purchase or invest. They are projects or brands who have (at a minimum) purchased ad space in our podcast (which is how we fund the podcast's operations). We meet with them, often have them on the podcast so you can hear from them directly, and often find additional ways to support each other (like introducing us to other cool guests). Please do your own research!Timestamps:00:00 - Intro to Farcade AI01:51 - How far along is Farcade AI in their development?05:34 - Why build Farcade AI with crypto/blockchain capabilities?09:38 - UI/UX of Farcade?11:50 - How easy will it be to create your OWN game in the Farcade?13:23 - How will making a game work & what happens once a game is launched?15:46 - What will you need to access the Farcade AI tools? (Farcade Token teaser)16:59 - Farcade Token airdrop live right now?17:59 - Will games built on Farcade have their own tokens?20:11 - What happens if a dev abandons their game?23:54 - How advanced will the games be inside of the Farcade?29:19 - Will games be able to hold the attention of players?31:03 - Will we see the Farcade on the App Store & Google Play Store?34:37 - Will game creators be able to incentivize gamers through their own earning mechanisms in their games?37:39 - Why is Farcade building on Base?40:52 - How is Farcade handling VC's and TGE?46:16 - Closing thoughts & how to engage with Farcade

Send us a textUnlock the secrets of blending speed and strategy for sustainable business growth. Join me, Zach Coleman, as I engage in a riveting conversation with a partner from Superfit Grow, where we analyze the traps of sprint-oriented goals that numerous businesses under the million-dollar mark often fall into. Through my own journey at Creative and Gym Mart, I unravel the crucial role of strategic planning and creativity in enhancing branding and operational success. Discover how a well-thought-out UI/UX roadmap can revolutionize project execution, saving both time and resources while fostering a more creative and stress-free work environment.Turn your attention to the 80-20 rule's magic in marketing and branding, emphasizing the importance of honing in on the strategies that yield the highest returns. By prioritizing the top 20% of tactics that generate 80% of the results, businesses can alleviate burnout and amplify their impacts. I share valuable insights into structured workflows and strategic pauses that prevent burnout and promote personal and team growth, underscoring the importance of timing and team dynamics. This episode offers visionary ideas that can seamlessly integrate into your routine, ensuring greater success and efficiency in your business ventures.Support the showSubscribe to our Youtube channel: https://www.youtube.com/channel/UCHHOVBghX_ENHwg2QhYUzlQDM us on Instagram at: https://www.instagram.com/creatitive/Connect on LinkedIn: https://www.linkedin.com/in/creatitive/View our Website: https://creatitive.com

In this electrifying episode of the Millionaire Car Salesman Podcast, hosts LA Williams and Sean V. Bradley dive deep into the innovations shaping the automotive CRM landscape with special guests Shane Born and Melissa Sinclair from NCC and ProMax.  "You're investing in one of the most important tools to help run all aspects of your business. You want to make sure that it's set up properly from the very beginning." - Melissa Sinclair As the automotive industry faces unprecedented changes, Shane and Melissa discuss how their companies are spearheading the credit-first approach in CRM solutions, creating streamlined and transparent processes for both dealers and consumers. The episode begins with the hosts addressing missed speaking opportunities at an industry event due to unforeseen circumstances and quickly shifts focus to the groundbreaking strategies being implemented by ProMax, setting a new bar for CRM systems integrated with National Credit Center resources. "Success involves partnering with the right people... ensure your team understands the what, the why, and the how, and then be flexible to pivot if a generational storm hits." - Shane Born The conversation is packed with insights into how dealerships can leverage modern CRM systems to improve customer experience, enhance fraud prevention, and streamline sales processes using accurate real-time credit data. Shane Born highlights the unique position of their CRM solution, emphasizing its ability to provide consistent, transparent, and frictionless service to consumers while maintaining a keen adaptability to market changes. Melissa Sinclair adds to this by discussing the newly launched open API, offering seamless integration capabilities with vendor partners to unify dealership operations. This episode is a must-listen for any automotive professional keen on harnessing cutting-edge CRM technologies to propel their business forward.   Key Takeaways: ✅ Credit-First CRM Approach: NCC and ProMax are revolutionizing the CRM space with a credit-first methodology, enhancing the buying process through accurate financing options and fraud prevention features. ✅ User Interface and Experience: The newly redesigned UI/UX of ProMax's CRM offers a modern, intuitive interface that simplifies processes for salespeople and management, improving efficiency and usability. ✅ Service and Sales Integration: By integrating service customer data with CRM strategies, dealerships can unlock unprecedented sales opportunities, targeting both existing and untapped customer bases. ✅ Open API for Seamless Integration: The introduction of the open API, Dex, allows for effortless connection with various dealership software, ensuring all operations are synchronized and efficient. ✅ Robust OEM Partnerships: ProMax's CRM is approved by most OEMs, including 100% co-op with General Motors, showcasing the platform's comprehensive capabilities and industry trust.     About Shane Born Shane Born is a prominent figure in the automotive industry, holding a significant position at NCC (National Credit Center) and ProMax. With over two decades of experience, Shane has been instrumental in driving technological advancements and fostering customer relations in the automotive sector. His focus lies in integrating credit solutions with CRM systems to enhance dealership efficiencies!   About Melissa Sinclair Melissa Sinclair at NCC and ProMax, bringing extensive experience and deep knowledge about CRM solutions. Melissa has contributed substantially to the development of innovative customer relationship management tools and has played a key role in ensuring that these tools meet the needs of modern dealerships. She is particularly focused on enhancing user experience and fostering partnerships within the automotive industry.     Unleashing the Power of CRM in Automotive Sales Key Takeaways The Millionaire Car Salesman Podcast dives into how CRM technology is revolutionizing the automotive industry, focusing on NCC's ProMax and its unique offerings. The discussion emphasizes the shift towards credit-first processes, enhancing both dealer and consumer experiences by leveraging advanced data management. An insider perspective on NADA reveals valuable insights into networking strategies and industry trends despite unexpected challenges. CRM Innovations in the Automotive Industry The Millionaire Car Salesman Podcast, hosted by LA Williams and Sean V. Bradley, recently featured Shane Born and Melissa Sinclair from NCC and ProMax, who discussed groundbreaking innovations in CRM technology, specifically tailored for the automotive industry. As the podcast episodes unravel, they explore how these technologies redefine dealer-consumer interactions and internal processes within dealerships. According to Shane Born, NCC is leveraging its dual expertise as both a data and software-as-a-service company: "We are both a DAS company and a SaaS company," he notes. Their end-to-end platform ensures a streamlined, credit-first approach that not only enhances dealer efficiency but also significantly improves the customer's buying journey. This dual focus allows NCC to provide a seamless workflow tied to a single database, an advantage that sets it apart from competitors relying on multiple integrations. From quote to contract, the process is designed to eliminate friction and bolster customer satisfaction by providing accurate financing solutions quickly. Melissa Sinclair elaborates on the customized experience ProMax delivers: "Any role in the dealership can benefit as the platform was designed specifically with them in mind." The conversations with dealers led to UI and UX improvements, focusing on easy navigation and relevant data presentation, ensuring that even complex tools are intuitive for users across all roles within the dealership. Strategies from the NADA Conference One of the intriguing segments of the podcast episode involved understanding the dynamics of the National Automobile Dealers Association (NADA) conference. Despite logistical hurdles due to inclement weather, vendors and attendees alike made the most of the opportunity to connect and explore industry advancements. Shane Born emphasized that despite a "50% pre-registration count," those who made it to the event were laser-focused on solving pertinent challenges, leading to higher closing rates on new dealer group deals. NADA's decision to open its welcome party to all attendees, not just paid registrants, was a strategic move to enhance networking despite lower turnout numbers. "It allows us to really have meaningful conversations about what's happening and where the industry is heading," Born shared, highlighting how such interactions lead to long-lasting partnerships and industry insights. This part of the podcast underscores the importance of adaptability and creativity in fostering networking opportunities, even in unforeseen circumstances. NADA highlighted industry trends, such as AI integration and credit-first approaches, showcased by innovative solutions like NCC's ProMax. Maximizing CRM for Dealer Success In detailing the capabilities of NCC's complete CRM, the podcast dives into how dealerships can maximize the tool for their success. At its core, ProMax's CRM offers a robust framework for both reactive and proactive dealership strategies—a point emphasized repeatedly throughout the discussion. "Any user can go in and build a custom list," explained Melissa Sinclair, illustrating the CRM's adaptability in creating targeted customer lists based on various criteria, such as unsold showroom traffic or service appointments. The system's Opportunities Dashboard is a game changer, automatically collating potential purchase opportunities, ensuring that even if a salesperson overlooks a prospect, the CRM does not. Sean V. Bradley highlighted common dealer pitfalls, such as under-utilizing CRM capabilities, which often leads to unnecessary marketing expenditures. "Why are they spending $65,000 in advertising per month when they could invest $5,000 to $10,000 in CRM?" he questioned, advocating for a full-time CRM manager to ensure optimal use of the system. Reflecting on trends discussed at the podcast, it's evident that leveraging comprehensive CRM tools like NCC's ProMax could save money and increase sales, making it essential for dealerships to embrace such technologies fully. Reflections on the Automotive Horizon As the podcast episode closes, the hosts and guests reflect on how the innovations discussed are reshaping the automotive sales landscape. The evolution of CRM technology, spearheaded by companies like NCC and solutions such as ProMax, shows an industry leaning heavily into data-driven, customer-centric approaches. The recurring theme remains clear: the automotive industry is poised for growth through technology adaptation and strategic partnerships. As Shane Born perfectly encapsulates, success in this field "comes down to consistent execution of your strategic vision," underscoring the importance of aligning technology with well-defined dealership goals. With ProMax's open API and partnership with AI leaders like Impel, NCC ensures they are not just evolving alongside industry changes, but leading the charge toward a more integrated and customer-focused sales experience. In the ever-evolving automotive market, insights from such discussions are invaluable, paving the way for dealerships to not only keep pace but thrive in an exciting era of digital transformation.     Resources: Podium: Discover how Podium's innovative AI technology can unlock unparalleled efficiency and drive your dealership's sales to new heights. Visit www.podium.com/mcs to learn more!   NCC: Credit-Driven Retailing - NCC delivers industry-best credit-driven retailing for auto dealerships, combining a powerful credit and compliance engine and fully integrated CRM/Desking platform for maximum profitability.   Complete CRM: Complete CRM is a streamlined, all-in-one system that simplifies your dealership software and processes so you can manage every aspect of your operation with ease; from tracking and following up on leads, desking deals, managing inventory, marketing to your customers, and more.   Dealer Synergy & Bradley On Demand: The automotive industry's #1 training, tracking, testing, and certification platform and consulting & accountability firm.   The Millionaire Car Salesman Facebook Group: Join the #1 Mastermind Group in the Automotive Industry! With over 28,000 members, gain access to successful automotive mentors & managers, the best industry practices, & collaborate with automotive professionals from around the WORLD! Join The Millionaire Car Salesman Facebook Group today!   Win the Game of Googleopoly: Unlocking the secret strategy of search engines.   The Millionaire Car Salesman Podcast is Proudly Sponsored By: Podium: Elevating Dealership Excellence with Intelligent Customer Engagement Solutions. Unlock unparalleled efficiency and drive sales with Podium's innovative AI technology, featured proudly on the Millionaire Car Salesman Podcast. Visit www.podium.com/mcs to learn more!   NCC: Powered by proprietary solutions such as Intelligent Credit Engine™ and LenderSelect™, NCC transforms the car-buying experience for dealers and their customers. From compliance and lender selection to CRM and desking, to marketing and data mining—NCC integrates them all in a single, seamless platform to deliver better customer experiences, maximum efficiency and maximum profit.   Complete CRM: As an innovative leader in the industry for the last 30 years, Complete CRM is designed to give your dealership the competitive edge in a demanding marketplace. Powered by Complete Credit™ and award-winning desking, Complete CRM™ is the industry's only credit and compliance-enabled CRM that lets dealers achieve maximum profitability on every deal. Built on modern technology, Complete CRM seamlessly integrates credit, compliance, inventory, data mining, lead generation, enterprise functionality, and customized reporting in one tool with a single login.   Dealer Synergy: The #1 Automotive Sales Training, Consulting, and Accountability Firm in the industry! With over two decades of experience in building Internet Departments and BDCs, we have developed the most effective automotive Internet Sales, BDC, and CRM solutions. Our expertise in creating phone scripts, rebuttals, CRM action plans, strategies, and templates ensures that your dealership's tools and personnel reach their full potential.   Bradley On Demand: The automotive sales industry's top Interactive Training, Tracking, Testing, and Certification Platform. Featuring LIVE Classes and over 9,000 training modules, our platform equips your dealership with everything needed to sell more cars, more often, and more profitably!    

Can a combo of Large Language Models (LLMs) and Domain-Specific Languages (DSLs) streamline development by automating repetitive patterns across teams? In this Mob Mentality Show episode, we dive deep into the intersection of AI-driven automation, code generation, and lean software development. Join us as we explore: ✅ The "Generator for the Generator" Concept – How AI-powered tools and Mob Programming can create DSLs that automate code generation at scale. ✅ Handling Cross-Domain Development with DSLs – How DSL arguments can be leveraged to generate applications across multiple domains while maintaining usability. ✅ Serverless Infrastructure as Code (IaC) & Auto-Generated Apps – How to use DSLs to automate cloud deployment with Angular or Streamlit apps. ✅ The Challenge of UI/UX in Generated Code – When UI is too generic, does it hurt usability? Can a DSL strike the right balance between automation and user experience? ✅ Regeneration vs. Continuous Development – Should teams work exclusively in the DSL, or also refine the code it generates? How to handle sync issues when regenerating applications. ✅ Turning Docs into Code with a DSL Converter – Automating workflows by transforming team documentation into executable code. ✅ Mob Automationist Role Inception – Is the next evolution of Mob Programming automating the automation? ✅ ZOMBIE Test Generation & Nested Python Dictionaries – How automated testing fits into the DSL-driven workflow and whether a DSL can be as simple as a structured Python dictionary.

There have been a number of UI/UX improvements on Sorare recently, some of which seem eerily similar to what's been available on SorareData for years. All of it begs the question: what should Sorare be providing to their users?

We're back with Season Three! In this season opener, we dive deep into the relationship between UI/UX design and storytelling with Kat Craig, a talented UI/UX designer who has contributed to some major titles in the gaming world. Kat walks us through her career journey—from graphic design to breaking into the gaming industry—and shares how the user interface and user experience impact player immersion, engagement, and emotional connection to the game's narrative. We discuss the importance of creating seamless experiences for players, how UI elements can be used to enhance storytelling (think of games like Fallout with diegetic UI elements), and how to balance complexity with accessibility. Kat also shares her insights on collaborating with other disciplines—narrative, art, and design teams—to ensure that the player's journey through a game is intuitive and enriching. Key Takeaways: The essential role of UI/UX design in enhancing narrative experience. How the graphical design elements and environmental design can amplify storytelling. Insights into the balance between complexity and accessibility for diverse player bases. Real-world examples from Kat's work, including contributions to Larian Studios' Baldur's Gate 3. How networking, internships, and personal projects can help aspiring designers break into the industry. If you're a storyteller, game designer, or just someone curious about the behind-the-scenes work in game development, this episode will offer valuable insights that bridge the gap between design and narrative. Kat's Links:⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ -> ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠LinkedIn⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ -> ⁠⁠ArtStation -> ⁠⁠Website/Portfolio -> Instagram -> Facebook The Corner of Story and Game: -> ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Discord⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ -> ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Facebook⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ -> ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Instagram⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ -> ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Bluesky⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ -> ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠LinkedIn⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ -> Email: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠gerald@storyandgame.com⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠

Mo Khazali, head of mobile and tech lead at Theodo UK, talks about the novel concept of Universal React. He discusses cross-platform development, overcoming performance challenges, and its impact on empowering small development teams to compete with big tech. Links https://x.com/mo__javad https://github.com/mojavad https://www.linkedin.com/in/mohammadkhazali We want to hear from you! How did you find us? Did you see us on Twitter? In a newsletter? Or maybe we were recommended by a friend? Let us know by sending an email to our producer, Emily, at emily.kochanekketner@logrocket.com (mailto:emily.kochanekketner@logrocket.com), or tweet at us at PodRocketPod (https://twitter.com/PodRocketpod). Follow us. Get free stickers. Follow us on Apple Podcasts, fill out this form (https://podrocket.logrocket.com/get-podrocket-stickers), and we'll send you free PodRocket stickers! What does LogRocket do? LogRocket provides AI-first session replay and analytics that surfaces the UX and technical issues impacting user experiences. Start understand where your users are struggling by trying it for free at [LogRocket.com]. Try LogRocket for free today.(https://logrocket.com/signup/?pdr) Special Guest: Mo Khazali.

This week Jun and Daniel dive into design differences between Korea and America, from social media and advertising to architecture and mobile apps. The hosts explore how and why Korean designs tend to be text-heavy and informative, while American designs focus more on visuals and artistic impact. Topics include YouTube thumbnails, movie posters, advertisements, mobile app UI/UX, building design, and book covers. They discuss how cultural values like collectivism, risk-averseness, and utilitarianism influence Korean design choices, while American designs often prioritize individual interpretation and bold statements.If you're interested in learning how clickbait, movie posters, mobile apps, and architecture differ between Korea and America, tune in to hear Daniel and Jun discuss all this and more! Also in this episode, Daniel and Jun teach each other English vocabulary, discuss the various brands of different countries, and make fun of Korean apartment naming conventions.Eye-Opening Moments PodcastEye-Opening Moments are stories of adversity, encounters, and perspectives. They are...Listen on: Apple Podcasts SpotifySupport the showAs a reminder, we record one episode a week in-person from Seoul, South Korea. We hope you enjoy listening to our conversation, and we're so excited to have you following us on this journey!Support us on Patreon:https://patreon.com/user?u=99211862Follow us on socials: https://www.instagram.com/koreanamericanpodcast/https://twitter.com/korampodcasthttps://www.tiktok.com/@koreanamericanpodcastQuestions/Comments/Feedback? Email us at: koreanamericanpodcast@gmail.com

With GenAI and LLMs comes great potential to delight and damage customer relationships—both during the sale, and in the UI/UX. However, are B2B AI product teams actually producing real outcomes, on the business side and the UX side, such that customers find these products easy to buy, trustworthy and indispensable?    What is changing with customer problems as a result of LLM and GenAI technologies becoming more readily available to implement into B2B software? Anything?   Is your current product or feature development being driven by the fact you might be able to now solve it with AI? The “AI-first” team sounds like it's cutting edge, but is that really determining what a customer will actually buy from you?    Today I want to talk to you about the interplay of GenAI, customer trust (both user and buyer trust), and the role of UX in products using probabilistic technology.     These thoughts are based on my own perceptions as a “user” of AI “solutions,” (quotes intentional!), conversations with prospects and clients at my company (Designing for Analytics), as well as the bright minds I mentor over at the MIT Sandbox innovation fund. I also wrote an article about this subject if you'd rather read an abridged version of my thoughts.   Highlights/ Skip to: AI and LLM-Powered Products Do Not Turn Customer Problems into “Now” and “Expensive” Problems (4:03) Trust and Transparency in the Sale and the Product UX: Handling LLM Hallucinations (Confabulations) and Designing for Model Interpretability (9:44) Selling AI Products to Customers Who Aren't Users (13:28) How LLM Hallucinations and Model Interpretability Impact User Trust of Your Product (16:10) Probabilistic UIs and LLMs Don't Negate the Need to Design for Outcomes (22:48) How AI Changes (or Doesn't) Our Benchmark Use Cases and UX Outcomes (28:41) Closing Thoughts (32:36)   Quotes from Today's Episode “Putting AI or GenAI into a product does not change the urgency or the depth of a particular customer problem; it just changes the solution space. Technology shifts in the last ten years have enabled founders to come up with all sorts of novel ways to leverage traditional machine learning, symbolic AI, and LLMs to create new products and disrupt established products; however, it would be foolish to ignore these developments as a product leader. All this technology does is change the possible solutions you can create. It does not change your customer situation, problem, or pain, either in the depth, or severity, or frequency. In fact, it might actually cause some new problems. I feel like most teams spend a lot more time living in the solution space than they do in the problem space. Fall in love with the problem and love that problem regardless of how the solution space may continue to change.” (4:51) “Narrowly targeted, specialized AI products are going to beat solutions trying to solve problems for multiple buyers and customers. If you're building a narrow, specific product for a narrow, specific audience, one of the things you have on your side is a solution focused on a specific domain used by people who have specific domain experience. You may not need a trillion-parameter LLM to provide significant value to your customer. AI products that have a more specific focus and address a very narrow ICP I believe are more likely to succeed than those trying to serve too many use cases—especially when GenAI is being leveraged to deliver the value. I think this can be true even for platform products as well. Narrowing the audience you want to serve also narrows the scope of the product, which in turn should increase the value that you bring to that audience—in part because you probably will have fewer trust, usability, and utility problems resulting from trying to leverage a model for a wide range of use cases.” (17:18) “Probabilistic UIs and LLMs are going to create big problems for product teams, particularly if they lack a set of guiding benchmark use cases. I talk a lot about benchmark use cases as a core design principle and data-rich enterprise products. Why? Because a lot of B2B and enterprise products fall into the game of ‘adding more stuff over time.' ‘Add it so you can sell it.' As products and software companies begin to mature, you start having product owners and PMs attached to specific technologies or parts of a product. Figuring out how to improve the customer's experience over time against the most critical problems and needs they have is a harder game to play than simply adding more stuff— especially if you have no benchmark use cases to hold you accountable. It's hard to make the product indispensable if it's trying to do 100 things for 100 people.“ (22:48) “Product is a hard game, and design and UX is by far not the only aspect of product that we need to get right. A lot of designers don't understand this, and they think if they just nail design and UX, then everything else solves itself. The reason the design and experience part is hard is that it's tied to behavior change– especially if you are ‘disrupting' an industry, incumbent tool, application, or product. You are in the behavior-change game, and it's really hard to get it right. But when you get it right, it can be really amazing and transformative.” (28:01) “If your AI product is trying to do a wide variety of things for a wide variety of personas, it's going to be harder to determine appropriate benchmarks and UX outcomes to measure and design against. Given LLM hallucinations, the increased problem of trust, model drift problems, etc., your AI product has to actually innovate in a way that is both meaningful and observable to the customer. It doesn't matter what your AI is trying to “fix.” If they can't see what the benefit is to them personally, it doesn't really matter if technically you've done something in a new and novel way. They're just not going to care because that question of what's in it for me is always sitting behind, in their brain, whether it's stated out loud or not.” (29:32)   Links Designing for Analytics mailing list

In this episode, Dave and Jamison answer these questions: After a decade as a Senior front-end engineer in companies stuck in legacy ways of working—paying lip service to true agility while clinging to control-heavy, waterfall practices—I'm frustrated and exhausted by meetings and largely apathetic, outsourced teams who don't match my enthusiasm for product-thinking or improving things. It seems allowed and normalised everywhere I go. How can I escape this cycle of big tech, unfulfilled as an engineer, and find a team with a strong product engineering culture where I can do high-impact work with similarly empowered teams? Thank you, and sorry if this is a bit verbose! Thanks guys. Martin ‌ How do you judge your competency in a technical skill and when should you include it on your resume? Should you include a skills that you haven't used in a while, skills you've only used in personal projects, or skills that you feel you only have a basic understanding of? I'm a frontend developer and I've seen some job descriptions include requirements (not nice-to-haves) like backend experience, Java, CI/CD, and UI/UX design using tools like Figma and Photoshop. I could make designs or write the backend code for a basic CRUD app, but it would take me some time, especially if I'm building things from scratch. I've seen some resumes where the writer lists a bunch of programming languages and technical skills, and I often wonder if they truly are competent in all of those skills.

When examining actual usage trends, it is evident that 46% of teachers and 48% of students report using ChatGPT or other forms of AI, at least once a week. Remarkably, student usage has surged by 27 percentage points compared to the previous year. Feedback from students has been largely positive, with 70% of K-12 students viewing AI chatbots favorably. This approval rate increases to 75% among undergraduates, while 68% of parents also express favorable views towards AI chatbots, as reported by CNBC.   Cristian Perry is the CEO of Undetectable AI, a software startup he founded in 2023, which has now gained over 14 million users worldwide. Under his leadership, the company has quickly ascended to rank among the top 10 generative AI writing tools globally, managing a team of 50 employees and maintaining profitability. Prior to launching Undetectable AI, Perry co-founded ChatterQuant in 2021, where he successfully raised institutional capital and grew revenue to nearly $1 million before the company was acquired by Money.net in 2023. At ChatterQuant, he led teams in sales, development, and UI/UX design while securing key partnerships and receiving industry recognition, including the TradeTech Europe Innovation Award and the Hackfort Pitch Competition.   Perry's professional experience includes a role as an Analyst at Janes Capital Partners in 2015, where he developed strong analytical skills and business fundamentals. His entrepreneurial journey began at the age of 13, inspired by his family of self-made business owners. At Undetectable AI, Perry oversees the strategic planning and development of three sub-brands, focusing on effective project execution and customer support. His growth strategy for both B2C and B2B markets integrates inbound sales tactics with targeted advertising campaigns and direct outreach. Cristian graduated from Boise State University in 2023 with a degree in Business Management.   LinkedIn: @ChristianPerry  Get in touch: Contact@Undetectable.AI  

Jay McKeown is the Director of Talent Acquisition at Red River, a defense contractor that brings together the ideal combination of talent, partners and products to disrupt the status quo in technology and drive success for business and government in ways previously unattainable. Red River serves organizations well beyond traditional technology integration, bringing more than 20 years of experience and mission-critical expertise in security, networking, analytics, collaboration, mobility and cloud solutions. Learn more at redriver.com. THE CHALLENGEIn today's candidate market post pandemic, we are dealing with back to office mandates and obviously for an industry that requires some travel to a SCIF or customer site. McKeown says, “I think for us and for everybody else, the challenges finding people that are willing to come in the office to some degree in a hybrid capacity… but there are still a ton of candidates out there looking for fully remote positions.”HOW CLEARANCEJOBS HELPSJay has a decade in the US Army and served a decade as a police officer and got into business about seven years ago. “And I have always been reluctant about joining this business world, coming from 2 tactical sides. I was a vice cop in DC working undercover for a decade…and was like what the heck is recruiting?” After starting his career and learning all about the different job boards and from the very beginning of working in the government contracting sector, he became the super user of ClearanceJobs.com. “Coming from that side of the industry and having a board that's dedicated towards clearances and tends to be military and government heavy - it almost feels comfortable. I guess when you're in there, it almost feels like a like a board made for prior service type of people.”For ClearanceJobs, McKeown loves the user friendliness and ease of functionality. “The UI / UX or the front end of ClearanceJobs has an ease of use and feel. You know, when I'm comparing it to the other boards, it is pretty self-explanatory where you can navigate around and buttons and pretty much find what you're looking for. I've noticed with the other boards some of the additional seem to be hidden or hard to find.”Red River's favorite functionality of the site is being able to build pipelines and tap into the most engaged talent to land a phone call and eventually extend an offer. Their recruiting team understands that the deadline is today when the government says they need a candidate today. “ClearanceJobs has bailed me out.” After using the Boolean or Intellisearch function to find qualified candidates, Red River sorts candidates by who was last active on the site to get a sense of who who's been on the board most recently. By pulling those last ten active candidates that are qualified and calling those individuals, they've improved their success rate to receiving call backs to the 90th percentile. “Just for that reason alone justifies your board. Much less all the other cool functionalities and features.”In any industry, but particularly the cleared space, it is important to act quickly and find that talent for national security programs. Is ClearanceJobs a top source for these types of missions? McKeown says, “Yeah, by far you're our top source for cleared candidates.” Hosted on Acast. See acast.com/privacy for more information.

Esben Friis-Jensen is the Co-founder and Chief Growth Officer at Userflow, a no-code builder for in-app onboarding and surveys that allows SaaS businesses to be more product-led. Userflow is 100% bootstrapped, and with just 3 people they have achieved 400+ customers and a 7-figure ARR (annual recurring revenue). Let's learn how they have been able to do this by having a product-led growth approach that focuses on the UI/UX of their product as well as building the strongest product possible. Show Notes [2:59] Do they just need a growth person, and how did the whole idea start? [5:35] Product-Led Growth facilitates the retention of direct customer feedback [8:13] What are the first big initial steps that he took to scale up his business? [11:43] You need to have a lot of integrity and certainty in what you're doing.You need to believe in the product that you're selling [14:15] How does he differentiate SEM from SEO? [17:12] What's the next big step that he took to 5x the business? [21:12] Esben walks us through how he refines value propositions [33:26] The more open your messaging is, the more different kinds of users you will have [42:44] How does his company maintain customer focus? [50:12] Esben's deliberate game plan for his business About Esben Friis-Jensen Esben Friis-Jensen is the co-founder of Userflow, a no-code platform for building onboarding guides and product tours.Before working on Userflow, he co-founded an application security platform called Cobalt. Additionally, he has a background as an Accenture consultant with more than three years of experience in test and deployment management of global IT implementations. Links Userflow Cobalt Monday Profile Esben's LinkedIn

In this exciting episode of the Mob Mentality Show, we sit down with Martin Christensen, a product transformation coach, to explore the pivotal power of mobbing in product discovery. What You'll Learn in This Episode: Mobbing Product Discovery What is Product Discovery? Understand the fundamentals user value, business value, and technical feasibility. Mob Style vs. Solo User Interviews: Learn how mobbing on user interviews enhances insights through diverse perspectives and how it contrasts with traditional solo interviews. The Benefits of Diversity: Discover why the mantra “Mob Anything” unlocks innovation, faster UI/UX iterations, and fewer lines of code while maintaining focus on user experience. Collaboration, Psychological Growth, and Transformation Barriers to New Methods: Dive into the psychological and organizational obstacles that can hinder teams from adopting mobbing or trying new approaches. Adult Development and Teaming: Martin shares insights on how stages of psychological development and life events can break down egocentrism and foster stronger collaboration. The "No Pain, No Gain" Paradox: Can growth happen without trauma? Discover the nuanced relationship between challenges, growth, and maturity in collaborative environments. Impact of Complexity on Happiness: Unpack how the complexity of problems and overall team happiness affect the ability to work effectively as a mob. Why Watch This Episode? If you're passionate about product development, user experience, or team collaboration, this episode is packed with actionable insights and relatable stories. From understanding the power of mobbing in product discovery to overcoming barriers to psychological maturity in teams, this conversation will leave you inspired to experiment and grow.

The purpose of the show is to transform your business and life with education and inspiration. I introduce busy business leaders to trends in business, technology, and marketing to highlight people you should know.First ParagraphAre you tired of feeling like your business is stuck in neutral, with your online presence failing to drive the results you need? As a business owner, you know that having a strong online presence is crucial for attracting and retaining customers, but it can be overwhelming to know where to start. In this episode, we're joined by the founder of NetMafia, a leading expert in crafting digital success stories for businesses of all sizes. With a proven track record of helping ventures thrive in the digital realm, our guest is here to share their insights on how to build a powerful online presence that drives real results.Second ParagraphAs the founder of NetMafia, our guest has a wealth of experience in building impactful websites, e-commerce stores, and driving traffic with SEO. With a background in web development, UI/UX, and marketing, they've helped numerous businesses scale their online presence and achieve their goals. But what really sets them apart is their passion for education and sharing their expertise with others. With over 35,000 students guided through their courses on Udemy, Skillshare, StackSkills, StackCommerce, and Packt publishing, our guest is dedicated to empowering entrepreneurs and businesses to succeed in the digital age. Join us as we dive into the strategies and tactics you need to take your online presence to the next level and drive real growth for your business.EpisodeDuring this episode, we'll do a deep dive into the changes and hot topics of scaling your online presence including its biggest challenges and growth. I will leverage the expertise of my guest and how to navigate the unique dynamics of the field. CTABy the end of this episode, you will be better equipped to know what to do, & I encourage you to contact my guest, Prerak Mehta, Founder at NetMafia.Here are resources and links for the audience to explore:NetMafia - My Web Design & SEO Marketing Agency:https://netmafia.co.in/free-30-minute-consultation-call/My Udemy Courses:AI Local SEO and Google My Business: AI SEO Marketing Course#1 WordPress Elementor Pro Course: Beginner to Advanced 2024Free SEO SOP Guide:https://netmafia.ck.page/seo-sopYouTube Channel:https://www.youtube.com/@PrerakMehta-NetMafiaSocial Media Links:https://www.facebook.com/netmafia.co.inhttps://www.instagram.com/netmafia.co.in/https://www.linkedin.com/in/prerak-mehta-51b282214/The Idea to Author Coach! https://www.facebook.com/groups/ideatoauthorcommunityHi there! Welcome to my page, where I help aspiring writers achieve their dreams of becoming published authors. My name is Mick, known online as The Doctor of Digital, and I'm thrilled to share my story with you.Growing up in a working-class family, I was surrounded by people who worked hard to provide for their families. My father was a factory worker, and my grandfather was a truck driver. Before that, our family had a long history of farming. But despite our humble beginnings, my parents were determined to break the cycle of poverty and create a better life for themselves and their children.My parents were the first in their respective families to graduate from high school, let alone college. In fact, other than a half-uncle, I was the first in my family to even attend college. And I was considered "not college material" by my teachers. But my parents instilled in me a love for reading, learning, and a strong work ethic, which helped me overcome the odds and achieve my academic goals.Throughout my academic journey, I wrote over 85 academic papers, earned three advanced degrees, including a PhD, and earned nine certificates in executive management, and educational technology. Not surprisingly, I became a professor, teaching 35 college-level courses. I even held leadership positions such as Campus Dean, Vice President, and Executive Director. But despite my many accomplishments, I never lost sight of my passion for writing.After years of writing and teaching, I decided to pursue my dream of becoming a published author. And when my first book was published as a novel, I followed that with a screenplay. Since then, I've written a non-fiction book, and I'm currently working on three more book proposals, on history, a book on music, and work-life balance, respectively. I am also active on three podcasts, have a voice talent, and am a favored speaker at conferences, sharing my expertise on educational technology. Regardless of your writing interests I can help.But my journey didn't come without its challenges. I faced many obstacles, including self-doubt, imposter syndrome, and the pressure to conform to societal expectations. However, I refused to let these challenges hold me back. Instead, I used them as opportunities to learn and grow, and to develop a growth mindset that has served me well throughout my career.As a book coach, I've had the privilege of working with many aspiring writers who are struggling to overcome their own challenges. And I've seen firsthand the transformative power of writing and storytelling. Whether you're a seasoned writer or just starting out, I believe that everyone has a story to tell, and that writing can be a powerful tool for personal growth and transformation.So, if you're ready to take your writing to the next level and achieve your publishing dreams, I invite you to join me on this journey. Let's work together to overcome your challenges, develop your writing skills, and bring your stories to life.Thank you for watching, and I look forward to working with you! Book a complimentary call now on my Calendy.Become a supporter of this podcast: https://www.spreaker.com/podcast/the-doctor-of-digital-gmick-smith-phd--1279468/support.

Vero arbeitet an der Uniklinik in Aachen als Spieleentwicklerin und ist dort für Grafik, UI/UX und Game Design verantwortlich. Gemeinsam mit dem Fachpersonal aus medizinischen Bereichen (z.B. Kieferchirurgie) hilft sie bei der Erstellung von interaktiven Lerninhalten, erstellt 3D-Scans von Leichenteilen und optimiert die Meshes für den Echtzeit-Einsatz. Vorher hat sie an der FH Aachen studiert und war dort als HiWi für das VR Lab verantwortlich.

For episode 185, we're excited to welcome Calanthia Mei, Co-Founder of Masa, a decentralized AI network where individuals can earn by contributing their data. Calanthia is a visionary leader with a rich history in fintech, having scaled successful companies and driven blockchain innovation. In this episode, we explore Masa's groundbreaking approach to democratizing AI through blockchain, and how it's paving the way for a future of Fair AI powered by people.We discuss:How blockchain can decentralize AI and empower Fair AI to create equitable opportunities for all,The growth of AI agents in crypto networks,Emerging trends to keep an eye on that are shaping the intersection of crypto and AI, andHow you can join the Masa community and run your own node.--Key Takeaways--The Four Stages of AI Agents - Calanthia made a bold prediction that AI agents will evolve through four key stages: from interactive JPGs to self-improving systems, utility-driven tools, and eventually a coordinated, competitive AI agent society. This progression highlights the transformative potential of AI in reshaping how we interact with technology and one another.Decentralizing AI for Fair and Inclusive Networks - Currently, AI development is dominated by big tech, limiting opportunities for smaller developers. Similarly, centralization in crypto could lead to inequality. Decentralizing AI through blockchain technologies can create fairer, safer, and more inclusive AI networks, ensuring opportunities for all stakeholders.AI Agents Solving Crypto's UX Challenges - AI agents are inherently platform-agnostic, which positions them to address crypto's UI/UX complexity. These agents can navigate interfaces and processes, simplifying the user experience and unlocking the full potential of blockchain applications for a wider audience.--Full shownotes with links available at--https://www.cryptoaltruism.org/blog/crypto-altruists-episode-185-crypto-powered-ai-agents-and-fair-ai-through-decentralizationThank you to PIPE gDAO for sponsoring the Crypto Altruism podcast!PIPE gDAO is leveraging blockchain for their University Real World Asset IP Launchpad that helps bring groundbreaking ideas from lab to market. By joining the Pipe Associate Network (aka PAN), associates can create a profile highlighting their skills, be notified of opportunities, and then contribute fractional work to pre-IPO companies in return for equity and tokens.--Support us with a Fiat or Crypto contribution--Learn more at cryptoaltruism.org/supportus--DISCLAIMER--While we may discuss specific web3 projects or cryptocurrencies on this podcast, please do not take any of this as investment advice, and please make sure to do your own research on potential investment opportunities, or any opportunity, before making an investment. We host a variety of guests on this podcast with the sole purpose of highlighting the social impact use cases of this technology. That being said, Crypto Altruism does not endorse any of these projects, and we recognize that, since this is an emerging sector, some may be operating in regulatory grey areas, and as such, we cannot confirm their legality in the jurisdictions in which they operate, especially as it pertains to decentralized finance protocols. So, before getting involved with any project, it's important that you do your own research and confirm the legality of the project. More info at cryptoaltruism.org

The full schedule for Latent Space LIVE! at NeurIPS has been announced, featuring Best of 2024 overview talks for the AI Startup Landscape, Computer Vision, Open Models, Transformers Killers, Synthetic Data, Agents, and Scaling, and speakers from Sarah Guo of Conviction, Roboflow, AI2/Meta, Recursal/Together, HuggingFace, OpenHands and SemiAnalysis. Join us for the IRL event/Livestream! Alessio will also be holding a meetup at AWS Re:Invent in Las Vegas this Wednesday. See our new Events page for dates of AI Engineer Summit, Singapore, and World's Fair in 2025. LAST CALL for questions for our big 2024 recap episode! Submit questions and messages on Speakpipe here for a chance to appear on the show!When we first observed that GPT Wrappers are Good, Actually, we did not even have Bolt on our radar. Since we recorded our Anthropic episode discussing building Agents with the new Claude 3.5 Sonnet, Bolt.new (by Stackblitz) has easily cleared the $8m ARR bar, repeating and accelerating its initial $4m feat.There are very many AI code generators and VS Code forks out there, but Bolt probably broke through initially because of its incredible zero shot low effort app generation:But as we explain in the pod, Bolt also emphasized deploy (Netlify)/ backend (Supabase)/ fullstack capabilities on top of Stackblitz's existing WebContainer full-WASM-powered-developer-environment-in-the-browser tech. Since then, the team has been shipping like mad (with weekly office hours), with bugfixing, full screen, multi-device, long context, diff based edits (using speculative decoding like we covered in Inference, Fast and Slow).All of this has captured the imagination of low/no code builders like Greg Isenberg and many others on YouTube/TikTok/Reddit/X/Linkedin etc:Just as with Fireworks, our relationship with Bolt/Stackblitz goes a bit deeper than normal - swyx advised the launch and got a front row seat to this epic journey, as well as demoed it with Realtime Voice at the recent OpenAI Dev Day. So we are very proud to be the first/closest to tell the full open story of Bolt/Stackblitz!Flow Engineering + Qodo/AlphaCodium UpdateIn year 2 of the pod we have been on a roll getting former guests to return as guest cohosts (Harrison Chase, Aman Sanger, Jon Frankle), and it was a pleasure to catch Itamar Friedman back on the pod, giving us an update on all things Qodo and Testing Agents from our last catchup a year and a half ago:Qodo (they renamed in September) went viral in early January this year with AlphaCodium (paper here, code here) beating DeepMind's AlphaCode with high efficiency:With a simple problem solving code agent:* The first step is to have the model reason about the problem. They describe it using bullet points and focus on the goal, inputs, outputs, rules, constraints, and any other relevant details.* Then, they make the model reason about the public tests and come up with an explanation of why the input leads to that particular output. * The model generates two to three potential solutions in text and ranks them in terms of correctness, simplicity, and robustness. * Then, it generates more diverse tests for the problem, covering cases not part of the original public tests. * Iteratively, pick a solution, generate the code, and run it on a few test cases. * If the tests fail, improve the code and repeat the process until the code passes every test.swyx has previously written similar thoughts on types vs tests for putting bounds on program behavior, but AlphaCodium extends this to AI generated tests and code.More recently, Itamar has also shown that AlphaCodium's techniques also extend well to the o1 models:Making Flow Engineering a useful technique to improve code model performance on every model. This is something we see AI Engineers uniquely well positioned to do compared to ML Engineers/Researchers.Full Video PodcastLike and subscribe!Show Notes* Itamar* Qodo* First episode* Eric* Bolt* StackBlitz* Thinkster* AlphaCodium* WebContainersChapters* 00:00:00 Introductions & Updates* 00:06:01 Generic vs. Specific AI Agents* 00:07:40 Maintaining vs Creating with AI* 00:17:46 Human vs Agent Computer Interfaces* 00:20:15 Why Docker doesn't work for Bolt* 00:24:23 Creating Testing and Code Review Loops* 00:28:07 Bolt's Task Breakdown Flow* 00:31:04 AI in Complex Enterprise Environments* 00:41:43 AlphaCodium* 00:44:39 Strategies for Breaking Down Complex Tasks* 00:45:22 Building in Open Source* 00:50:35 Choosing a product as a founder* 00:59:03 Reflections on Bolt Success* 01:06:07 Building a B2C GTM* 01:18:11 AI Capabilities and Pricing Tiers* 01:20:28 What makes Bolt unique* 01:23:07 Future Growth and Product Development* 01:29:06 Competitive Landscape in AI Engineering* 01:30:01 Advice to Founders and Embracing AI* 01:32:20 Having a baby and completing an Iron ManTranscriptAlessio [00:00:00]: Hey everyone, welcome to the Latent Space Podcast. This is Alessio, partner and CTO at Decibel Partners, and I'm joined by my co-host Swyx, founder of Smol.ai.Swyx [00:00:12]: Hey, and today we're still in our sort of makeshift in-between studio, but we're very delighted to have a former returning guest host, Itamar. Welcome back.Itamar [00:00:21]: Great to be here after a year or more. Yeah, a year and a half.Swyx [00:00:24]: You're one of our earliest guests on Agents. Now you're CEO co-founder of Kodo. Right. Which has just been renamed. You also raised a $40 million Series A, and we can get caught up on everything, but we're also delighted to have our new guest, Eric. Welcome.Eric [00:00:42]: Thank you. Excited to be here. Should I say Bolt or StackBlitz?Swyx [00:00:45]: Like, is it like its own company now or?Eric [00:00:47]: Yeah. Bolt's definitely bolt.new. That's the thing that we're probably the most known for, I imagine, at this point.Swyx [00:00:54]: Which is ridiculous to say because you were working at StackBlitz for so long.Eric [00:00:57]: Yeah. I mean, within a week, we were doing like double the amount of traffic. And StackBlitz had been online for seven years, and we were like, what? But anyways, yeah. So we're StackBlitz, the company behind bolt.new. If you've heard of bolt.new, that's our stuff. Yeah.Swyx [00:01:12]: Yeah.Itamar [00:01:13]: Excellent. I see, by the way, that the founder mode, you need to know to capture opportunities. So kudos on doing that, right? You're working on some technology, and then suddenly you can exploit that to a new world. Yeah.Eric [00:01:24]: Totally. And I think, well, not to jump, but 100%, I mean, a couple of months ago, we had the idea for Bolt earlier this year, but we haven't really shared this too much publicly. But we actually had tried to build it with some of those state-of-the-art models back in January, February, you can kind of imagine which, and they just weren't good enough to actually do the code generation where the code was accurate and it was fast and whatever have you without a ton of like rag, but then there was like issues with that. So we put it on the shelf and then we got kind of a sneak peek of some of the new models that have come out in the past couple of months now. And so once we saw that, once we actually saw the code gen from it, we were like, oh my God, like, okay, we can build a product around this. And so that was really the impetus of us building the thing. But with that, it was StackBlitz, the core StackBlitz product the past seven years has been an IDE for developers. So the entire user experience flow we've built up just didn't make sense. And so when we kind of went out to build Bolt, we just thought, you know, if we were inventing our product today, what would the interface look like given what is now possible with the AI code gen? And so there's definitely a lot of conversations we had internally, but you know, just kind of when we logically laid it out, we were like, yeah, I think it makes sense to just greenfield a new thing and let's see what happens. If it works great, then we'll figure it out. If it doesn't work great, then it'll get deleted at some point. So that's kind of how it actually came to be.Swyx [00:02:49]: I'll mention your background a little bit. You were also founder of Thinkster before you started StackBlitz. So both of you are second time founders. Both of you have sort of re-founded your company recently. Yours was more of a rename. I think a slightly different direction as well. And then we can talk about both. Maybe just chronologically, should we get caught up on where Kodo is first and then you know, just like what people should know since the last pod? Sure.Itamar [00:03:12]: The last pod was two months after we launched and we basically had the vision that we talked about. The idea that software development is about specification, test and code, etc. We are more on the testing part as in essence, we think that if you solve testing, you solve software development. The beautiful chart that we'll put up on screen. And testing is a really big field, like there are many dimensions, unit testing, the level of the component, how big it is, how large it is. And then there is like different type of testing, is it regression or smoke or whatever. So back then we only had like one ID extension with unit tests as in focus. One and a half year later, first ID extension supports more type of testing as context aware. We index local, local repos, but also 10,000s of repos for Fortune 500 companies. We have another agent, another tool that is called, the pure agent is the open source and the commercial one is CodoMerge. And then we have another open source called CoverAgent, which is not yet a commercial product coming very soon. It's very impressive. It could be that already people are approving automated pull requests that they don't even aware in really big open sources. So once we have enough of these, we will also launch another agent. So for the first one and a half year, what we did is grew in our offering and mostly on the side of, does this code actually works, testing, code review, et cetera. And we believe that's the critical milestone that needs to be achieved to actually have the AI engineer for enterprise software. And then like for the first year was everything bottom up, getting to 1 million installation. 2024, that was 2023, 2024 was starting to monetize, to feel like how it is to make the first buck. So we did the teams offering, it went well with a thousand of teams, et cetera. And then we started like just a few months ago to do enterprise with everything you need, which is a lot of things that discussed in the last post that was just released by Codelm. So that's how we call it at Codelm. Just opening the brackets, our company name was Codelm AI, and we renamed to Codo and we call our models Codelm. So back to my point, so we started Enterprise Motion and already have multiple Fortune 100 companies. And then with that, we raised a series of $40 million. And what's exciting about it is that enables us to develop more agents. That's our focus. I think it's very different. We're not coming very soon with an ID or something like that.Swyx [00:06:01]: You don't want to fork this code?Itamar [00:06:03]: Maybe we'll fork JetBrains or something just to be different.Swyx [00:06:08]: I noticed that, you know, I think the promise of general purpose agents has kind of died. Like everyone is doing kind of what you're doing. There's Codogen, Codomerge, and then there's a third one. What's the name of it?Itamar [00:06:17]: Yeah. Codocover. Cover. Which is like a commercial version of a cover agent. It's coming soon.Swyx [00:06:23]: Yeah. It's very similar with factory AI, also doing like droids. They all have special purpose doing things, but people don't really want general purpose agents. Right. The last time you were here, we talked about AutoGBT, the biggest thing of 2023. This year, not really relevant anymore. And I think it's mostly just because when you give me a general purpose agent, I don't know what to do with it.Eric [00:06:42]: Yeah.Itamar [00:06:43]: I totally agree with that. We're seeing it for a while and I think it will stay like that despite the computer use, et cetera, that supposedly can just replace us. You can just like prompt it to be, hey, now be a QA or be a QA person or a developer. I still think that there's a few reasons why you see like a dedicated agent. Again, I'm a bit more focused, like my head is more on complex software for big teams and enterprise, et cetera. And even think about permissions and what are the data sources and just the same way you manage permissions for users. Developers, you probably want to have dedicated guardrails and dedicated approvals for agents. I intentionally like touched a point on not many people think about. And of course, then what you can think of, like maybe there's different tools, tool use, et cetera. But just the first point by itself is a good reason why you want to have different agents.Alessio [00:07:40]: Just to compare that with Bot.new, you're almost focused on like the application is very complex and now you need better tools to kind of manage it and build on top of it. On Bot.new, it's almost like I was using it the other day. There's basically like, hey, look, I'm just trying to get started. You know, I'm not very opinionated on like how you're going to implement this. Like this is what I want to do. And you build a beautiful app with it. What people ask as the next step, you know, going back to like the general versus like specific, have you had people say, hey, you know, this is great to start, but then I want a specific Bot.new dot whatever else to do a more vertical integration and kind of like development or what's the, what do people say?Eric [00:08:18]: Yeah. I think, I think you kind of hit the, hit it head on, which is, you know, kind of the way that we've, we've kind of talked about internally is it's like people are using Bolt to go from like 0.0 to 1.0, like that's like kind of the biggest unlock that Bolt has versus most other things out there. I mean, I think that's kind of what's, what's very unique about Bolt. I think the, you know, the working on like existing enterprise applications is, I mean, it's crazy important because, you know, there's a, you look, when you look at the fortune 500, I mean, these code bases, some of these have been around for 20, 30 plus years. And so it's important to be going from, you know, 101.3 to 101.4, et cetera. I think for us, so what's been actually pretty interesting is we see there's kind of two different users for us that are coming in and it's very distinct. It's like people that are developers already. And then there's people that have never really written software and more if they have, it's been very, very minimal. And so in the first camp, what these developers are doing, like to go from zero to one, they're coming to Bolt and then they're ejecting the thing to get up or just downloading it and, you know, opening cursor, like whatever to, to, you know, keep iterating on the thing. And sometimes they'll bring it back to Bolt to like add in a huge piece of functionality or something. Right. But for the people that don't know how to code, they're actually just, they, they live in this thing. And that was one of the weird things when we launched is, you know, within a day of us being online, one of the most popular YouTube videos, and there's been a ton since, which was, you know, there's like, oh, Bolt is the cursor killer. And I originally saw the headlines and I was like, thanks for the views. I mean, I don't know. This doesn't make sense to me. That's not, that's not what we kind of thought.Swyx [00:09:44]: It's how YouTubers talk to each other. Well, everything kills everything else.Eric [00:09:47]: Totally. But what blew my mind was that there was any comparison because it's like cursor is a, is a local IDE product. But when, when we actually kind of dug into it and we, and we have people that are using our product saying this, I'm not using cursor. And I was like, what? And it turns out there are hundreds of thousands of people that we have seen that we're using cursor and we're trying to build apps with that where they're not traditional software does, but we're heavily leaning on the AI. And as you can imagine, it is very complicated, right? To do that with cursor. So when Bolt came out, they're like, wow, this thing's amazing because it kind of inverts the complexity where it's like, you know, it's not an IDE, it's, it's a, it's a chat-based sort of interface that we have. So that's kind of the split, which is rather interesting. We've had like the first startups now launch off of Bolt entirely where this, you know, tomorrow I'm doing a live stream with this guy named Paul, who he's built an entire CRM using this thing and you know, with backend, et cetera. And people have made their first money on the internet period, you know, launching this with Stripe or whatever have you. So that's, that's kind of the two main, the two main categories of folks that we see using Bolt though.Itamar [00:10:51]: I agree that I don't understand the comparison. It doesn't make sense to me. I think like we have like two type of families of tools. One is like we re-imagine the software development. I think Bolt is there and I think like a cursor is more like a evolution of what we already have. It's like taking the IDE and it's, it's amazing and it's okay, let's, let's adapt the IDE to an era where LLMs can do a lot for us. And Bolt is more like, okay, let's rethink everything totally. And I think we see a few tools there, like maybe Vercel, Veo and maybe Repl.it in that area. And then in the area of let's expedite, let's change, let's, let's progress with what we already have. You can see Cursor and Kodo, but we're different between ourselves, Cursor and Kodo, but definitely I think that comparison doesn't make sense.Alessio [00:11:42]: And just to set the context, this is not a Twitter demo. You've made 4 million of revenue in four weeks. So this is, this is actually working, you know, it's not a, what, what do you think that is? Like, there's been so many people demoing coding agents on Twitter and then it doesn't really work. And then you guys were just like, here you go, it's live, go use it, pay us for it. You know, is there anything in the development that was like interesting and maybe how that compares to building your own agents?Eric [00:12:08]: We had no idea, honestly, like we, we, we've been pretty blown away and, and things have just kind of continued to grow faster since then. We're like, oh, today is week six. So I, I kind of came back to the point you just made, right, where it's, you, you kind of outlined, it's like, there's kind of this new market of like kind of rethinking the software development and then there's heavily augmenting existing developers. I think that, you know, both of which are, you know, AI code gen being extremely good, it's allowed existing developers, it's allowing existing developers to camera out software far faster than they could have ever before, right? It's like the ultimate power tool for an existing developer. But this code gen stuff is now so good. And then, and we saw this over the past, you know, from the beginning of the year when we tried to first build, it's actually lowered the barrier to people that, that aren't traditionally software engineers. But the kind of the key thing is if you kind of think about it from, imagine you've never written software before, right? My co-founder and I, he and I grew up down the street from each other in Chicago. We learned how to code when we were 13 together and we've been building stuff ever since. And this is back in like the mid 2000s or whatever, you know, there was nothing for free to learn from online on the internet and how to code. For our 13th birthdays, we asked our parents for, you know, O'Reilly books cause you couldn't get this at the library, right? And so instead of like an Xbox, we got, you know, programming books. But the hardest part for everyone learning to code is getting an environment set up locally, you know? And so when we built StackBlitz, like kind of the key thesis, like seven years ago, the insight we had was that, Hey, it seems like the browser has a lot of new APIs like WebAssembly and service workers, et cetera, where you could actually write an operating system that ran inside the browser that could boot in milliseconds. And you, you know, basically there's this missing capability of the web. Like the web should be able to build apps for the web, right? You should be able to build the web on the web. Every other platform has that, Visual Studio for Windows, Xcode for Mac. The web has no built in primitive for this. And so just like our built in kind of like nerd instinct on this was like, that seems like a huge hole and it's, you know, it will be very valuable or like, you know, very valuable problem to solve. So if you want to set up that environments, you know, this is what we spent the past seven years doing. And the reality is existing developers have running locally. They already know how to set up that environment. So the problem isn't as acute for them. When we put Bolt online, we took that technology called WebContainer and married it with these, you know, state of the art frontier models. And the people that have the most pain with getting stuff set up locally is people that don't code. I think that's been, you know, really the big explosive reason is no one else has been trying to make dev environments work inside of a browser tab, you know, for the past if since ever, other than basically our company, largely because there wasn't an immediate demand or need. So I think we kind of find ourselves at the right place at the right time. And again, for this market of people that don't know how to write software, you would kind of expect that you should be able to do this without downloading something to your computer in the same way that, hey, I don't have to download Photoshop now to make designs because there's Figma. I don't have to download Word because there's, you know, Google Docs. They're kind of looking at this as that sort of thing, right? Which was kind of the, you know, our impetus and kind of vision from the get-go. But you know, the code gen, the AI code gen stuff that's come out has just been, you know, an order of magnitude multiplier on how magic that is, right? So that's kind of my best distillation of like, what is going on here, you know?Alessio [00:15:21]: And you can deploy too, right?Eric [00:15:22]: Yeah.Alessio [00:15:23]: Yeah.Eric [00:15:24]: And so that's, what's really cool is it's, you know, we have deployment built in with Netlify and this is actually, I think, Sean, you actually built this at Netlify when you were there. Yeah. It's one of the most brilliant integrations actually, because, you know, effectively the API that Sean built, maybe you can speak to it, but like as a provider, we can just effectively give files to Netlify without the user even logging in and they have a live website. And if they want to keep, hold onto it, they can click a link and claim it to their Netlify account. But it basically is just this really magic experience because when you come to Bolt, you say, I want a website. Like my mom, 70, 71 years old, made her first website, you know, on the internet two weeks ago, right? It was about her nursing days.Swyx [00:16:03]: Oh, that's fantastic though. It wouldn't have been made.Eric [00:16:06]: A hundred percent. Cause even in, you know, when we've had a lot of people building personal, like deeply personal stuff, like in the first week we launched this, the sales guy from the East Coast, you know, replied to a tweet of mine and he said, thank you so much for building this to your team. His daughter has a medical condition and so for her to travel, she has to like line up donors or something, you know, so ahead of time. And so he actually used Bolt to make a website to do that, to actually go and send it to folks in the region she was going to travel to ahead of time. I was really touched by it, but I also thought like, why, you know, why didn't he use like Wix or Squarespace? Right? I mean, this is, this is a solved problem, quote unquote, right? And then when I thought, I actually use Squarespace for my, for my, uh, the wedding website for my wife and I, like back in 2021, so I'm familiar, you know, it was, it was faster. I know how to code. I was like, this is faster. Right. And I thought back and I was like, there's a whole interface you have to learn how to use. And it's actually not that simple. There's like a million things you can configure in that thing. When you come to Bolt, there's a, there's a text box. You just say, I need a, I need a wedding website. Here's the date. Here's where it is. And here's a photo of me and my wife, put it somewhere relevant. It's actually the simplest way. And that's what my, when my mom came, she said, uh, I'm Pat Simons. I was a nurse in the seventies, you know, and like, here's the things I did and a website came out. So coming back to why is this such a, I think, why are we seeing this sort of growth? It's, this is the simplest interface I think maybe ever created to actually build it, a deploy a website. And then that website, my mom made, she's like, okay, this looks great. And there's, there's one button, you just click it, deploy, and it's live and you can buy a domain name, attach it to it. And you know, it's as simple as it gets, it's getting even simpler with some of the stuff we're working on. But anyways, so that's, it's, it's, uh, it's been really interesting to see some of the usage like that.Swyx [00:17:46]: I can offer my perspective. So I, you know, I probably should have disclosed a little bit that, uh, I'm a, uh, stack list investor.Alessio [00:17:53]: Canceled the episode. I know, I know. Don't play it now. Pause.Eric actually reached out to ShowMeBolt before the launch. And we, you know, we talked a lot about, like, the framing of, of what we're going to talk about how we marketed the thing, but also, like, what we're So that's what Bolt was going to need, like a whole sort of infrastructure.swyx: Netlify, I was a maintainer but I won't take claim for the anonymous upload. That's actually the origin story of Netlify. We can have Matt Billman talk about it, but that was [00:18:00] how Netlify started. You could drag and drop your zip file or folder from your desktop onto a website, it would have a live URL with no sign in.swyx: And so that was the origin story of Netlify. And it just persists to today. And it's just like it's really nice, interesting that both Bolt and CognitionDevIn and a bunch of other sort of agent type startups, they all use Netlify to deploy because of this one feature. They don't really care about the other features.swyx: But, but just because it's easy for computers to use and talk to it, like if you build an interface for computers specifically, that it's easy for them to Navigate, then they will be used in agents. And I think that's a learning that a lot of developer tools companies are having. That's my bolt launch story and now if I say all that stuff.swyx: And I just wanted to come back to, like, the Webcontainers things, right? Like, I think you put a lot of weight on the technical modes. I think you also are just like, very good at product. So you've, you've like, built a better agent than a lot of people, the rest of us, including myself, who have tried to build these things, and we didn't get as far as you did.swyx: Don't shortchange yourself on products. But I think specifically [00:19:00] on, on infra, on like the sandboxing, like this is a thing that people really want. Alessio has Bax E2B, which we'll have on at some point, talking about like the sort of the server full side. But yours is, you know, inside of the browser, serverless.swyx: It doesn't cost you anything to serve one person versus a million people. It doesn't, doesn't cost you anything. I think that's interesting. I think in theory, we should be able to like run tests because you can run the full backend. Like, you can run Git, you can run Node, you can run maybe Python someday.swyx: We talked about this. But ideally, you should be able to have a fully gentic loop, running code, seeing the errors, correcting code, and just kind of self healing, right? Like, I mean, isn't that the dream?Eric: Totally.swyx: Yeah,Eric: totally. At least in bold, we've got, we've got a good amount of that today. I mean, there's a lot more for us to do, but one of the nice things, because like in web container, you know, there's a lot of kind of stuff you go Google like, you know, turn docker container into wasm.Eric: You'll find a lot of stuff out there that will do that. The problem is it's very big, it's slow, and that ruins the experience. And so what we ended up doing is just writing an operating system from [00:20:00] scratch that was just purpose built to, you know, run in a browser tab. And the reason being is, you know, Docker 2 awesome things will give you an image that's like out 60 to 100 megabits, you know, maybe more, you know, and our, our OS, you know, kind of clocks in, I think, I think we're in like a, maybe, maybe a megabyte or less or something like that.Eric: I mean, it's, it's, you know, really, really, you know, stripped down.swyx: This is basically the task involved is I understand that it's. Mapping every single, single Linux call to some kind of web, web assembly implementation,Eric: but more or less, and, and then there's a lot of things actually, like when you're looking at a dev environment, there's a lot of things that you don't need that a traditional OS is gonna have, right?Eric: Like, you know audio drivers or you like, there's just like, there's just tons of things. Oh, yeah. Right. Yeah. That goes . Yeah. You can just kind, you can, you can kind of tos them. Or alternatively, what you can do is you can actually be the nice thing. And this is, this kind of comes back to the origins of browsers, which is, you know, they're, they're at the beginning of the web and, you know, the late nineties, there was two very different kind of visions for the web where Alan Kay vehemently [00:21:00] disagree with the idea that should be document based, which is, you know, Tim Berners Lee, you know, that, and that's kind of what ended up winning, winning was this document based kind of browsing documents on the web thing.Eric: Alan Kay, he's got this like very famous quote where he said, you know, you want web browsers to be mini operating systems. They should download little mini binaries and execute with like a little mini virtualized operating system in there. And what's kind of interesting about the history, not to geek out on this aspect, what's kind of interesting about the history is both of those folks ended up being right.Eric: Documents were actually the pragmatic way that the web worked. Was, you know, became the most ubiquitous platform in the world to the degree now that this is why WebAssembly has been invented is that we're doing, we need to do more low level things in a browser, same thing with WebGPU, et cetera. And so all these APIs, you know, to build an operating system came to the browser.Eric: And that was actually the realization we had in 2017 was, holy heck, like you can actually, you know, service workers, which were designed for allowing your app to work offline. That was the kind of the key one where it was like, wait a second, you can actually now run. Web servers within a [00:22:00] browser, like you can run a server that you open up.Eric: That's wild. Like full Node. js. Full Node. js. Like that capability. Like, I can have a URL that's programmatically controlled. By a web application itself, boom. Like the web can build the web. The primitive is there. Everyone at the time, like we talked to people that like worked on, you know Chrome and V8 and they were like, uhhhh.Eric: You know, like I don't know. But it's one of those things you just kind of have to go do it to find out. So we spent a couple of years, you know, working on it and yeah. And, and, and got to work in back in 2021 is when we kind of put the first like data of web container online. Butswyx: in partnership with Google, right?swyx: Like Google actually had to help you get over the finish line with stuff.Eric: A hundred percent, because well, you know, over the years of when we were doing the R and D on the thing. Kind of the biggest challenge, the two ways that you can kind of test how powerful and capable a platform are, the two types of applications are one, video games, right, because they're just very compute intensive, a lot of calculations that have to happen, right?Eric: The second one are IDEs, because you're talking about actually virtualizing the actual [00:23:00] runtime environment you are in to actually build apps on top of it, which requires sophisticated capabilities, a lot of access to data. You know, a good amount of compute power, right, to effectively, you know, building app in app sort of thing.Eric: So those, those are the stress tests. So if your platform is missing stuff, those are the things where you find out. Those are, those are the people building games and IDEs. They're the ones filing bugs on operating system level stuff. And for us, browser level stuff.Eric [00:23:47]: yeah, what ended up happening is we were just hammering, you know, the Chromium bug tracker, and they're like, who are these guys? Yeah. And, and they were amazing because I mean, just making Chrome DevTools be able to debug, I mean, it's, it's not, it wasn't originally built right for debugging an operating system, right? They've been phenomenal working with us and just kind of really pushing the limits, but that it's a rising tide that's kind of lifted all boats because now there's a lot of different types of applications that you can debug with Chrome Dev Tools that are running a browser that runs more reliably because just the stress testing that, that we and, you know, games that are coming to the web are kind of pushing as well, but.Itamar [00:24:23]: That's awesome. About the testing, I think like most, let's say coding assistant from different kinds will need this loop of testing. And even I would add code review to some, to some extent that you mentioned. How is testing different from code review? Code review could be, for example, PR review, like a code review that is done at the point of when you want to merge branches. But I would say that code review, for example, checks best practices, maintainability, and so on. It's not just like CI, but more than CI. And testing is like a more like checking functionality, et cetera. So it's different. We call, by the way, all of these together code integrity, but that's a different story. Just to go back to the, to the testing and specifically. Yeah. It's, it's, it's since the first slide. Yeah. We're consistent. So if we go back to the testing, I think like, it's not surprising that for us testing is important and for Bolt it's testing important, but I want to shed some light on a different perspective of it. Like let's think about autonomous driving. Those startups that are doing autonomous driving for highway and autonomous driving for the city. And I think like we saw the autonomous of the highway much faster and reaching to a level, I don't know, four or so much faster than those in the city. Now, in both cases, you need testing and quote unquote testing, you know, verifying validation that you're doing the right thing on the road and you're reading and et cetera. But it's probably like so different in the city that it could be like actually different technology. And I claim that we're seeing something similar here. So when you're building the next Wix, and if I was them, I was like looking at you and being a bit scared. That's what you're disrupting, what you just said. Then basically, I would say that, for example, the UX UI is freaking important. And because you're you're more aiming for the end user. In this case, maybe it's an end user that doesn't know how to develop for developers. It's also important. But let alone those that do not know to develop, they need a slick UI UX. And I think like that's one reason, for example, I think Cursor have like really good technology. I don't know the underlying what's under the hood, but at least what they're saying. But I think also their UX UI is great. It's a lot because they did their own ID. While if you're aiming for the city AI, suddenly like there's a lot of testing and code review technology that it's not necessarily like that important. For example, let's talk about integration tests. Probably like a lot of what you're building involved at the moment is isolated applications. Maybe the vision or the end game is maybe like having one solution for everything. It could be that eventually the highway companies will go into the city and the other way around. But at the beginning, there is a difference. And integration tests are a good example. I guess they're a bit less important. And when you think about enterprise software, they're really important. So to recap, like I think like the idea of looping and verifying your test and verifying your code in different ways, testing or code review, et cetera, seems to be important in the highway AI and the city AI, but in different ways and different like critical for the city, even more and more variety. Actually, I was looking to ask you like what kind of loops you guys are doing. For example, when I'm using Bolt and I'm enjoying it a lot, then I do see like sometimes you're trying to catch the errors and fix them. And also, I noticed that you're breaking down tasks into smaller ones and then et cetera, which is already a common notion for a year ago. But it seems like you're doing it really well. So if you're willing to share anything about it.Eric [00:28:07]: Yeah, yeah. I realized I never actually hit the punchline of what I was saying before. I mentioned the point about us kind of writing an operating system from scratch because what ended up being important about that is that to your point, it's actually a very, like compared to like a, you know, if you're like running cursor on anyone's machine, you kind of don't know what you're dealing with, with the OS you're running on. There could be an error happens. It could be like a million different things, right? There could be some config. There could be, it could be God knows what, right? The thing with WebConnect is because we wrote the entire thing from scratch. It's actually a unified image basically. And we can instrument it at any level that we think is going to be useful, which is exactly what we did when we started building Bolt is we instrumented stuff at like the process level, at the runtime level, you know, et cetera, et cetera, et cetera. Stuff that would just be not impossible to do on local, but to do that in a way that works across any operating system, whatever is, I mean, would just be insanely, you know, insanely difficult to do right and reliably. And that's what you saw when you've used Bolt is that when an error actually will occur, whether it's in the build process or the actual web application itself is failing or anything kind of in between, you can actually capture those errors. And today it's a very primitive way of how we've implemented it largely because the product just didn't exist 90 days ago. So we're like, we got some work ahead of us and we got to hire some more a little bit, but basically we present and we say, Hey, this is, here's kind of the things that went wrong. There's a fix it button and then a ignore button, and then you can just hit fix it. And then we take all that telemetry through our agent, you run it through our agent and say, kind of, here's the state of the application. Here's kind of the errors that we got from Node.js or the browser or whatever, and like dah, dah, dah, dah. And it can take a crack at actually solving it. And it's actually pretty darn good at being able to do that. That's kind of been a, you know, closing the loop and having it be a reliable kind of base has seemed to be a pretty big upgrade over doing stuff locally, just because I think that's a pretty key ingredient of it. And yeah, I think breaking things down into smaller tasks, like that's, that's kind of a key part of our agent. I think like Claude did a really good job with artifacts. I think, you know, us and kind of everyone else has, has kind of taken their approach of like actually breaking out certain tasks in a certain order into, you know, kind of a concrete way. And, and so actually the core of Bolt, I know we actually made open source. So you can actually go and check out like the system prompts and et cetera, and you can run it locally and whatever have you. So anyone that's interested in this stuff, I'd highly recommend taking a look at. There's not a lot of like stuff that's like open source in this realm. It's, that was one of the fun things that we've we thought would be cool to do. And people, people seem to like it. I mean, there's a lot of forks and people adding different models and stuff. So it's been cool to see.Swyx [00:30:41]: Yeah. I'm happy to add, I added real-time voice for my opening day demo and it was really fun to hack with. So thank you for doing that. Yeah. Thank you. I'm going to steal your code.Eric [00:30:52]: Because I want that.Swyx [00:30:52]: It's funny because I built on top of the fork of Bolt.new that already has the multi LLM thing. And so you just told me you're going to merge that in. So then you're going to merge two layers of forks down into this thing. So it'll be fun.Eric [00:31:03]: Heck yeah.Alessio [00:31:04]: Just to touch on like the environment, Itamar, you maybe go into the most complicated environments that even the people that work there don't know how to run. How much of an impact does that have on your performance? Like, you know, it's most of the work you're doing actually figuring out environment and like the libraries, because I'm sure they're using outdated version of languages, they're using outdated libraries, they're using forks that have not been on the public internet before. How much of the work that you're doing is like there versus like at the LLM level?Itamar [00:31:32]: One of the reasons I was asking about, you know, what are the steps to break things down, because it really matters. Like, what's the tech stack? How complicated the software is? It's hard to figure it out when you're dealing with the real world, any environment of enterprise as a city, when I'm like, while maybe sometimes like, I think you do enable like in Bolt, like to install stuff, but it's quite a like controlled environment. And that's a good thing to do, because then you narrow down and it's easier to make things work. So definitely, there are two dimensions, I think, actually spaces. One is the fact just like installing our software without yet like doing anything, making it work, just installing it because we work with enterprise and Fortune 500, etc. Many of them want on prem solution.Swyx [00:32:22]: So you have how many deployment options?Itamar [00:32:24]: Basically, we had, we did a metric metrics, say 96 options, because, you know, they're different dimensions. Like, for example, one dimension, we connect to your code management system to your Git. So are you having like GitHub, GitLab? Subversion? Is it like on cloud or deployed on prem? Just an example. Which model agree to use its APIs or ours? Like we have our Is it TestGPT? Yeah, when we started with TestGPT, it was a huge mistake name. It was cool back then, but I don't think it's a good idea to name a model after someone else's model. Anyway, that's my opinion. So we gotSwyx [00:33:02]: I'm interested in these learnings, like things that you change your mind on.Itamar [00:33:06]: Eventually, when you're building a company, you're building a brand and you want to create your own brand. By the way, when I thought about Bolt.new, I also thought about if it's not a problem, because when I think about Bolt, I do think about like a couple of companies that are already called this way.Swyx [00:33:19]: Curse companies. You could call it Codium just to...Itamar [00:33:24]: Okay, thank you. Touche. Touche.Eric [00:33:27]: Yeah, you got to imagine the board meeting before we launched Bolt, one of our investors, you can imagine they're like, are you sure? Because from the investment side, it's kind of a famous, very notorious Bolt. And they're like, are you sure you want to go with that name? Oh, yeah. Yeah, absolutely.Itamar [00:33:43]: At this point, we have actually four models. There is a model for autocomplete. There's a model for the chat. There is a model dedicated for more for code review. And there is a model that is for code embedding. Actually, you might notice that there isn't a good code embedding model out there. Can you name one? Like dedicated for code?Swyx [00:34:04]: There's code indexing, and then you can do sort of like the hide for code. And then you can embed the descriptions of the code.Itamar [00:34:12]: Yeah, but you do see a lot of type of models that are dedicated for embedding and for different spaces, different fields, etc. And I'm not aware. And I know that if you go to the bedrock, try to find like there's a few code embedding models, but none of them are specialized for code.Swyx [00:34:31]: Is there a benchmark that you would tell us to pay attention to?Itamar [00:34:34]: Yeah, so it's coming. Wait for that. Anyway, we have our models. And just to go back to the 96 option of deployment. So I'm closing the brackets for us. So one is like dimensional, like what Git deployment you have, like what models do you agree to use? Dotter could be like if it's air-gapped completely, or you want VPC, and then you have Azure, GCP, and AWS, which is different. Do you use Kubernetes or do not? Because we want to exploit that. There are companies that do not do that, etc. I guess you know what I mean. So that's one thing. And considering that we are dealing with one of all four enterprises, we needed to deal with that. So you asked me about how complicated it is to solve that complex code. I said, it's just a deployment part. And then now to the software, we see a lot of different challenges. For example, some companies, they did actually a good job to build a lot of microservices. Let's not get to if it's good or not, but let's first assume that it is a good thing. A lot of microservices, each one of them has their own repo. And now you have tens of thousands of repos. And you as a developer want to develop something. And I remember me coming to a corporate for the first time. I don't know where to look at, like where to find things. So just doing a good indexing for that is like a challenge. And moreover, the regular indexing, the one that you can find, we wrote a few blogs on that. By the way, we also have some open source, different than yours, but actually three and growing. Then it doesn't work. You need to let the tech leads and the companies influence your indexing. For example, Mark with different repos with different colors. This is a high quality repo. This is a lower quality repo. This is a repo that we want to deprecate. This is a repo we want to grow, etc. And let that be part of your indexing. And only then things actually work for enterprise and they don't get to a fatigue of, oh, this is awesome. Oh, but I'm starting, it's annoying me. I think Copilot is an amazing tool, but I'm quoting others, meaning GitHub Copilot, that they see not so good retention of GitHub Copilot and enterprise. Ooh, spicy. Yeah. I saw snapshots of people and we have customers that are Copilot users as well. And also I saw research, some of them is public by the way, between 38 to 50% retention for users using Copilot and enterprise. So it's not so good. By the way, I don't think it's that bad, but it's not so good. So I think that's a reason because, yeah, it helps you auto-complete, but then, and especially if you're working on your repo alone, but if it's need that context of remote repos that you're code-based, that's hard. So to make things work, there's a lot of work on that, like giving the controllability for the tech leads, for the developer platform or developer experience department in the organization to influence how things are working. A short example, because if you have like really old legacy code, probably some of it is not so good anymore. If you just fine tune on these code base, then there is a bias to repeat those mistakes or old practices, etc. So you need, for example, as I mentioned, to influence that. For example, in Coda, you can have a markdown of best practices by the tech leads and Coda will include that and relate to that and will not offer suggestions that are not according to the best practices, just as an example. So that's just a short list of things that you need to do in order to deal with, like you mentioned, the 100.1 to 100.2 version of software. I just want to say what you're doing is extremelyEric [00:38:32]: impressive because it's very difficult. I mean, the business of Stackplus, kind of before bulk came online, we sold a version of our IDE that went on-prem. So I understand what you're saying about the difficulty of getting stuff just working on-prem. Holy heck. I mean, that is extremely hard. I guess the question I have for you is, I mean, we were just doing that with kind of Kubernetes-based stuff, but the spread of Fortune 500 companies that you're working with, how are they doing the inference for this? Are you kind of plugging into Azure's OpenAI stuff and AWS's Bedrock, you know, Cloud stuff? Or are they just like running stuff on GPUs? Like, what is that? How are these folks approaching that? Because, man, what we saw on the enterprise side, I mean, I got to imagine that that's a huge challenge. Everything you said and more, like,Itamar [00:39:15]: for example, like someone could be, and I don't think any of these is bad. Like, they made their decision. Like, for example, some people, they're, I want only AWS and VPC on AWS, no matter what. And then they, some of them, like there is a subset, I will say, I'm willing to take models only for from Bedrock and not ours. And we have a problem because there is no good code embedding model on Bedrock. And that's part of what we're doing now with AWS to solve that. We solve it in a different way. But if you are willing to run on AWS VPC, but run your run models on GPUs or inferentia, like the new version of the more coming out, then our models can run on that. But everything you said is right. Like, we see like on-prem deployment where they have their own GPUs. We see Azure where you're using OpenAI Azure. We see cases where you're running on GCP and they want OpenAI. Like this cross, like a case, although there is Gemini or even Sonnet, I think is available on GCP, just an example. So all the options, that's part of the challenge. I admit that we thought about it, but it was even more complicated. And it took us a few months to actually, that metrics that I mentioned, to start clicking each one of the blocks there. A few months is impressive. I mean,Eric [00:40:35]: honestly, just that's okay. Every one of these enterprises is, their networking is different. Just everything's different. Every single one is different. I see you understand. Yeah. So that just cannot be understated. That it is, that's extremely impressive. Hats off.Itamar [00:40:50]: It could be, by the way, like, for example, oh, we're only AWS, but our GitHub enterprise is on-prem. Oh, we forgot. So we need like a private link or whatever, like every time like that. It's not, and you do need to think about it if you want to work with an enterprise. And it's important. Like I understand like their, I respect their point of view.Swyx [00:41:10]: And this primarily impacts your architecture, your tech choices. Like you have to, you can't choose some vendors because...Itamar [00:41:15]: Yeah, definitely. To be frank, it makes us hard for a startup because it means that we want, we want everyone to enjoy all the variety of models. By the way, it was hard for us with our technology. I want to open a bracket, like a window. I guess you're familiar with our Alpha Codium, which is an open source.Eric [00:41:33]: We got to go over that. Yeah. So I'll do that quickly.Itamar [00:41:36]: Yeah. A pin in that. Yeah. Actually, we didn't have it in the last episode. So, so, okay.Swyx [00:41:41]: Okay. We'll come back to that later, but let's talk about...Itamar [00:41:43]: Yeah. So, so just like shortly, and then we can double click on Alpha Codium. But Alpha Codium is a open source tool. You can go and try it and lets you compete on CodeForce. This is a website and a competition and actually reach a master level level, like 95% with a click of a button. You don't need to do anything. And part of what we did there is taking a problem and breaking it to different, like smaller blocks. And then the models are doing a much better job. Like we all know it by now that taking small tasks and solving them, by the way, even O1, which is supposed to be able to do system two thinking like Greg from OpenAI like hinted, is doing better on these kinds of problems. But still, it's very useful to break it down for O1, despite O1 being able to think by itself. And that's what we presented like just a month ago, OpenAI released that now they are doing 93 percentile with O1 IOI left and International Olympiad of Formation. Sorry, I forgot. Exactly. I told you I forgot. And we took their O1 preview with Alpha Codium and did better. Like it just shows like, and there is a big difference between the preview and the IOI. It shows like that these models are not still system two thinkers, and there is a big difference. So maybe they're not complete system two. Yeah, they need some guidance. I call them system 1.5. We can, we can have it. I thought about it. Like, you know, I care about this philosophy stuff. And I think like we didn't see it even close to a system two thinking. I can elaborate later. But closing the brackets, like we take Alpha Codium and as our principle of thinking, we take tasks and break them down to smaller tasks. And then we want to exploit the best model to solve them. So I want to enable anyone to enjoy O1 and SONET and Gemini 1.5, etc. But at the same time, I need to develop my own models as well, because some of the Fortune 500 want to have all air gapped or whatever. So that's a challenge. Now you need to support so many models. And to some extent, I would say that the flow engineering, the breaking down to two different blocks is a necessity for us. Why? Because when you take a big block, a big problem, you need a very different prompt for each one of the models to actually work. But when you take a big problem and break it into small tasks, we can talk how we do that, then the prompt matters less. What I want to say, like all this, like as a startup trying to do different deployment, getting all the juice that you can get from models, etc. is a big problem. And one need to think about it. And one of our mitigation is that process of taking tasks and breaking them down. That's why I'm really interested to know how you guys are doing it. And part of what we do is also open source. So you can see.Swyx [00:44:39]: There's a lot in there. But yeah, flow over prompt. I do believe that that does make sense. I feel like there's a lot that both of you can sort of exchange notes on breaking down problems. And I just want you guys to just go for it. This is fun to watch.Eric [00:44:55]: Yeah. I mean, what's super interesting is the context you're working in is, because for us too with Bolt, we've started thinking because our kind of existing business line was going behind the firewall, right? We were like, how do we do this? Adding the inference aspect on, we're like, okay, how does... Because I mean, there's not a lot of prior art, right? I mean, this is all new. This is all new. So I definitely am going to have a lot of questions for you.Itamar [00:45:17]: I'm here. We're very open, by the way. We have a paper on a blog or like whatever.Swyx [00:45:22]: The Alphacodeum, GitHub, and we'll put all this in the show notes.Itamar [00:45:25]: Yeah. And even the new results of O1, we published it.Eric [00:45:29]: I love that. And I also just, I think spiritually, I like your approach of being transparent. Because I think there's a lot of hype-ium around AI stuff. And a lot of it is, it's just like, you have these companies that are just kind of keep their stuff closed source and then just max hype it, but then it's kind of nothing. And I think it kind of gives a bad rep to the incredible stuff that's actually happening here. And so I think it's stuff like what you're doing where, I mean, true merit and you're cracking open actual code for others to learn from and use. That strikes me as the right approach. And it's great to hear that you're making such incredible progress.Itamar [00:46:02]: I have something to share about the open source. Most of our tools are, we have an open source version and then a premium pro version. But it's not an easy decision to do that. I actually wanted to ask you about your strategy, but I think in your case, there is, in my opinion, relatively a good strategy where a lot of parts of open source, but then you have the deployment and the environment, which is not right if I get it correctly. And then there's a clear, almost hugging face model. Yeah, you can do that, but why should you try to deploy it yourself, deploy it with us? But in our case, and I'm not sure you're not going to hit also some competitors, and I guess you are. I wanted to ask you, for example, on some of them. In our case, one day we looked on one of our competitors that is doing code review. We're a platform. We have the code review, the testing, et cetera, spread over the ID to get. And in each agent, we have a few startups or a big incumbents that are doing only that. So we noticed one of our competitors having not only a very similar UI of our open source, but actually even our typo. And you sit there and you're kind of like, yeah, we're not that good. We don't use enough Grammarly or whatever. And we had a couple of these and we saw it there. And then it's a challenge. And I want to ask you, Bald is doing so well, and then you open source it. So I think I know what my answer was. I gave it before, but still interestingEric [00:47:29]: to hear what you think. GeoHot said back, I don't know who he was up to at this exact moment, but I think on comma AI, all that stuff's open source. And someone had asked him, why is this open source? And he's like, if you're not actually confident that you can go and crush it and build the best thing, then yeah, you should probably keep your stuff closed source. He said something akin to that. I'm probably kind of butchering it, but I thought it was kind of a really good point. And that's not to say that you should just open source everything, because for obvious reasons, there's kind of strategic things you have to kind of take in mind. But I actually think a pretty liberal approach, as liberal as you kind of can be, it can really make a lot of sense. Because that is so validating that one of your competitors is taking your stuff and they're like, yeah, let's just kind of tweak the styles. I mean, clearly, right? I think it's kind of healthy because it keeps, I'm sure back at HQ that day when you saw that, you're like, oh, all right, well, we have to grind even harder to make sure we stay ahead. And so I think it's actually a very useful, motivating thing for the teams. Because you might feel this period of comfort. I think a lot of companies will have this period of comfort where they're not feeling the competition and one day they get disrupted. So kind of putting stuff out there and letting people push it forces you to face reality soon, right? And actually feel that incrementally so you can kind of adjust course. And that's for us, the open source version of Bolt has had a lot of features people have been begging us for, like persisting chat messages and checkpoints and stuff. Within the first week, that stuff was landed in the open source versions. And they're like, why can't you ship this? It's in the open, so people have forked it. And we're like, we're trying to keep our servers and GPUs online. But it's been great because the folks in the community did a great job, kept us on our toes. And we've got to know most of these folks too at this point that have been building these things. And so it actually was very instructive. Like, okay, well, if we're going to go kind of land this, there's some UX patterns we can kind of look at and the code is open source to this stuff. What's great about these, what's not. So anyways, NetNet, I think it's awesome. I think from a competitive point of view for us, I think in particular, what's interesting is the core technology of WebContainer going. And I think that right now, there's really nothing that's kind of on par with that. And we also, we have a business of, because WebContainer runs in your browser, but to make it work, you have to install stuff from NPM. You have to make cores bypass requests, like connected databases, which all require server-side proxying or acceleration. And so we actually sell WebContainer as a service. One of the core reasons we open-sourced kind of the core components of Bolt when we launched was that we think that there's going to be a lot more of these AI, in-your-browser AI co-gen experiences, kind of like what Anthropic did with Artifacts and Clod. By the way, Artifacts uses WebContainers. Not yet. No, yeah. Should I strike that? I think that they've got their own thing at the moment, but there's been a lot of interest in WebContainers from folks doing things in that sort of realm and in the AI labs and startups and everything in between. So I think there'll be, I imagine, over the coming months, there'll be lots of things being announced to folks kind of adopting it. But yeah, I think effectively...Swyx [00:50:35]: Okay, I'll say this. If you're a large model lab and you want to build sandbox environments inside of your chat app, you should call Eric.Itamar [00:50:43]: But wait, wait, wait, wait, wait, wait. I have a question about that. I think OpenAI, they felt that people are not using their model as they would want to. So they built ChatGPT. But I would say that ChatGPT now defines OpenAI. I know they're doing a lot of business from their APIs, but still, is this how you think? Isn't Bolt.new your business now? Why don't you focus on that instead of the...Swyx [00:51:16]: What's your advice as a founder?Eric [00:51:18]: You're right. And so going into it, we, candidly, we were like, Bolt.new, this thing is super cool. We think people are stoked. We think people will be stoked. But we were like, maybe that's allowed. Best case scenario, after month one, we'd be mind blown if we added a couple hundred K of error or something. And we were like, but we think there's probably going to be an immediate huge business. Because there was some early poll on folks wanting to put WebContainer into their product offerings, kind of similar to what Bolt is doing or whatever. We were actually prepared for the inverse outcome here. But I mean, well, I guess we've seen poll on both. But I mean, what's happened with Bolt, and you're right, it's actually the same strategy as like OpenAI or Anthropic, where we have our ChatGPT to OpenAI's APIs is Bolt to WebContainer. And so we've kind of taken that same approach. And we're seeing, I guess, some of the similar results, except right now, the revenue side is extremely lopsided to Bolt.Itamar [00:52:16]: I think if you ask me what's my advice, I think you have three options. One is to focus on Bolt. The other is to focus on the WebContainer. The third is to raise one billion dollars and do them both. I'm serious. I think otherwise, you need to choose. And if you raise enough money, and I think it's big bucks, because you're going to be chased by competitors. And I think it will be challenging to do both. And maybe you can. I don't know. We do see these numbers right now, raising above $100 million, even without havingEric [00:52:49]: a product. You can see these. It's excellent advice. And I think what's been amazing, but also kind of challenging is we're trying to forecast, okay, well, where are these things going? I mean, in the initial weeks, I think us and all the investors in the company that we're sharing this with, it was like, this is cool. Okay, we added 500k. Wow, that's crazy. Wow, we're at a million now. Most things, you have this kind of the tech crunch launch of initiation and then the thing of sorrow. And if there's going to be a downtrend, it's just not coming yet. Now that we're kind of looking ahead, we're six weeks in. So now we're getting enough confidence in our convictions to go, okay, this se

Wes and Scott talk with Cassidy Williams and Harald Kirschner about exciting new features in VS Code and GitHub Copilot, including custom instructions, UI/UX improvements, and the future of AI and Copilot within different editors. Show Notes 00:00 Welcome to Syntax! 00:32 Cassidy's keynote at GitHub Universe 03:23 New Copilot features 04:55 Use cases for prompt engineering 09:20 UI and UX enhancements 19:18 Copilot Extensions 20:38 Brought to you by Sentry.io 21:26 Multi-line suggestions? 27:00 How do you develop new ideas in this space? GitHub Next 35:42 Copilot in Xcode GitHub Copilot code completion in Xcode is now available in public preview 39:16 VS Code experimental features @code Hit us up on Socials! Syntax: X Instagram Tiktok LinkedIn Threads Wes: X Instagram Tiktok LinkedIn Threads Scott: X Instagram Tiktok LinkedIn Threads Randy: X Instagram YouTube Threads

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Kelly is a world traveling content creator and influencer, UI/UX designer, multiple business owner, and a mother of two. She gives amazing insight into the worlds of travel and entrepreneurship with kids, and best practices on how to thrive in every area of your life while doing it all!  

Zain's Bio: Zain Mustafa is the CEO of Geeks of Kolachi, a forward-thinking software development agency. With over a decade of experience in the tech industry, Zain has led numerous successful projects, specialising in web and mobile application development. His expertise spans across full-stack development, UI/UX design, and digital transformation, making him a versatile leader […]

"Adopt a fail-fast mentality. You don't have time for five-year plans. You can plan for a year, but be prepared to pivot quickly." - Amotz Harari   Amotz Harari leads a team of marketing gentlemen and women dedicated to eradicating Death-by-PowerPoint wherever it lurks. Their mission is to enable decision-making by removing the affliction of bad content from the inboxes of businesses and individuals worldwide. With years of intensive marketing experience, Amotz merges a well-rounded background in SEO, content development, social, outreach, SEM, and analytics, with knowledge in UI/UX, consumer psychology, product, and competitive research. In this interview, Amotz teaches us how Storydoc uses AI and innovative marketing strategies to create compelling business presentations.   Website: www.storydoc.com  LinkedIn: https://www.linkedin.com/in/amotz-harari/

Sometimes DIY UI/UX design only gets you so far—and you know it's time for outside help. One thing prospects from SAAS analytics and data-related product companies often ask me is how things are like in the other guy/gal's backyard. They want to compare their situation to others like them. So, today, I want to share some of the common “themes” I see that usually are the root causes of what leads to a phone call with me.      By the time I am on the phone with most prospects who already have a product in market, they're usually either having significant problems with 1 or more of the following: sales friction (product value is opaque); low adoption/renewal worries (user apathy), customer complaints about UI/UX being hard to use; velocity (team is doing tons of work, but leader isn't seeing progress)—and the like.      I'm hoping today's episode will explain some of the root causes that may lead to these issues — so you can avoid them in your data product building work!       Highlights/ Skip to: (10:47) Design != "front-end development" or analyst work (12:34)  Liking doing UI/UX/viz design work vs. knowing  (15:04)  When a leader sees lots of work being done, but the UX/design isn't progressing (17:31) Your product's UX needs to convey some magic IP/special sauce…but it isn't (20:25) Understanding the tradeoffs of using libraries, templates, and other solution's design as a foundation for your own  (25:28) The sunk cost bias associated with POCs and “we'll iterate on it” (28:31) Relying on UI/UX "customization" to please all customers (31:26) The hidden costs of abstraction of system objects, UI components, etc.  to make life easier for engineering and technical teams (32:32) Believing you'll know the design is good “when you see it” (and what you don't know you don't know) (36:43) Believing that because the data science/AI/ML modeling under your solution was, accurate, difficult, and/or expensive makes it automatically worth paying for      Quotes from Today's Episode The challenge is often not knowing what you don't know about a project. We often end up focusing on building the tech [and rushing it out] so we can get some feedback on it… but product is not about getting it out there so we can get feedback. The goal of doing product well is to produce value, benefits, or outcomes. Learning is important, but that's not what the objective is. The objective is benefits creation. (5:47) When we start doing design on a project that's not design actionable, we build debt and sometimes can hurt the process of design. If you start designing your product with an entire green space, no direction, and no constraints, the chance of you shipping a good v1 is small. Your product strategy needs to be design-actionable for the team to properly execute against it. (19:19) While you don't need to always start at zero with your UI/UX design, what are the parts of your product or application that do make sense to borrow , “steal” and cheat from? And when does it not?  It takes skill to know when you should be breaking the rules or conventions. Shortcuts often don't produce outsized results—unless you know what a good shortcut looks like.  (22:28) A proof of concept is not a minimum valuable product. There's a difference between proving the tech can work and making it into a product that's so valuable, someone would exchange money for it because it's so useful to them. Whatever that value is, these are two different things. (26:40) Trying to do a little bit for everybody [through excessive customization] can often result in nobody understanding the value or utility of your solution. Customization can hide the fact the team has decided not to make difficult choices. If you're coming into a crowded space… it's like'y not going to be a compelling reason to [convince customers to switch to your solution]. Customization can be a tax, not a benefit. (29:26) Watch for the sunk cost bias [in product development]. [Buyers] don't care how the sausage was made. Many don't understand how the AI stuff works, they probably don't need to understand how it works. They want the benefits downstream from technology wrapped up in something so invaluable they can't live without it.  Watch out for technically right, effectively wrong. (39:27)

Artificial Intelligence & Machine Learning Product Specialist, Ana Arriola-Kanada, grew up in ‘the valley' just north of LA, watching Robotech and working in the family shop. She moved to Japan just after HS to work in Anime. An autodidact driven by a powerful work ethic and growth mindset, she propelled through all facets of tech & design playing key roles in the development of web design, emoji (Adobe), mobile computing and the original iPhone (Apple), UI/UX, PlayStation (Sony)…etc. It was Elizabeth Holmes at Theranos who tripped her ethical alarm wire, which, as traumatic as that was, has led Ana to the forefront of ethical AI where she has led teams in designing ethical frameworks (Meta, Microsoft, IDEO) and advocates for the inclusion & intersectionality of all humans and the care of our planet in developing those data sets.Images and more from Ana on cleverpodcast.comPlease say Hi on social! Twitter, Instagram, Linkedin and Facebook - @CleverPodcast, @amydevers,If you enjoy Clever we could use your support! Please consider leaving a review, making a donation, becoming a sponsor, or introducing us to your friends! We love and appreciate you!Clever is hosted & produced by Amy Devers, with editing by Mark Zurawinski, production assistance from Ilana Nevins and Anouchka Stephan, and music by El Ten Eleven. Hosted on Acast. See acast.com/privacy for more information.