Podcasts about Saas

Wed, 29 Oct 2025 19:45:00 GMT http://relay.fm/clockwise/629 http://relay.fm/clockwise/629 The House is Just for the Robot 629 Dan Moren and Mikah Sargent What we use our Apple Watches for, moving to a new HomeKit home, the tech we use while cooking, and a new humanoid robot for the home. What we use our Apple Watches for, moving to a new HomeKit home, the tech we use while cooking, and a new humanoid robot for the home. clean 1780 What we use our Apple Watches for, moving to a new HomeKit home, the tech we use while cooking, and a new humanoid robot for the home. This episode of Clockwise is sponsored by: 1Password: Discover SaaS applications, automate lifecycle management, and optimize SaaS spend. Guest Starring: Guy English and Aleen Simms Links and Show Notes: Support Clockwise with a Relay Membership

Wed, 29 Oct 2025 19:45:00 GMT http://relay.fm/clockwise/629 http://relay.fm/clockwise/629 Dan Moren and Mikah Sargent What we use our Apple Watches for, moving to a new HomeKit home, the tech we use while cooking, and a new humanoid robot for the home. What we use our Apple Watches for, moving to a new HomeKit home, the tech we use while cooking, and a new humanoid robot for the home. clean 1780 What we use our Apple Watches for, moving to a new HomeKit home, the tech we use while cooking, and a new humanoid robot for the home. This episode of Clockwise is sponsored by: 1Password: Discover SaaS applications, automate lifecycle management, and optimize SaaS spend. Guest Starring: Guy English and Aleen Simms Links and Show Notes: Support Clockwise with a Relay Membership

In this episode, host Alexandra Takei, Director at Ruckus Games, sits down with Robert van Hoesel, co-founder and CEO of First Look, now part of Pragma, to explore how studios can own and scale their player relationships. Robert's journey from founding a SaaS company to building First Look began with one simple insight: game studios are some of the most passionate users a software builder could serve, and the games industry desperately needs the dream stack for connected distribution, player communications, and analytics. First Look acts as a CRM for games, helping studios streamline playtesting, gather player feedback, and grow grassroots communities. The pair discusses why these capabilities have become essential as publishers pull back, competition increases, and self-publishing becomes the norm. Robert shares how First Look enables small teams to punch above their weight by automating data capture across platforms like Steam and Discord, transforming scattered playtest feedback into actionable insights, and shares the full suite of offerings First Look provides for studios today.They also unpack First Look's acquisition by Pragma and what it means to unify the backend and frontend of game development. The episode closes with practical advice for studios: start community-building early, close the feedback loop with players, and reward engagement to create sustainable, loyal audiences.We'd also like to thank Levellr — the Discord community intelligence platform — for making this episode possible. Learn more about unlocking real-time community insights at levellr.com.If you like the episode, please help others find us by leaving a 5-star rating or review! And if you have any comments, requests, or feedback shoot us a note at podcast@naavik.co. Watch the episode: YouTube ChannelFor more episodes and details: Podcast WebsiteFree newsletter: Naavik DigestFollow us: Twitter | LinkedIn | WebsiteSound design by Gavin Mc Cabe

This week, Jack Sharry talks with Parker Ence, CEO & Co-founder of Jump Advisor AI, a fast-growing startup that brings an AI-enhanced client meeting cycle to financial advisors. Parker is an entrepreneur and operator with 12 years of CEO/Co-founder experience across advisortech, data/DaaS, AI, SaaS, and insurtech.  Jack and Parker discuss how Jump helps RIAs and broker-dealers slash client meeting admin time by up to 90%. From real-time meeting prep and automated CRM updates to actionable insights and compliance-ready workflows, Parker shares how Jump revolutionizes the client meeting cycle for financial advisors. He also explores the company's rapid growth, significant enterprise partnerships, and his vision for the future of AI in financial services. In this episode: (00:00) - Intro (01:39) - The origin of Jump Advisor AI (03:30) - Jump's most popular product and what it does (05:01) - Jump's enterprise-level partnerships (06:18) - Parker's startup journey (11:29) - Jump's three core products (13:35) - Parker's outlook on AI in financial services (15:29) - Parker's key takeaways (17:34) - Parker's interests outside of work Quotes "What we're best known for is our AI meeting assistant that's made for advisors. And whatever the compliance team has approved, that's the most popular." ~ Parker Ence "Don't worry so much about getting replaced by AI. Worry about getting outcompeted by other advisors who are adopting AI faster." ~ Parker Ence "Everything that is inside the Jump product is there because an advisor requested it. So, we love partnering with RIAs, broker-dealers, solo advisors, and any of our customers to co-create the future." ~ Parker Ence Links  Parker Ence on LinkedIn Jump AI Cetera Osaic LPL Financial Tim Chaves Stanford Graduate School of Business Google Cloud Salesforce Connect with our hosts LifeYield Jack Sharry on LinkedIn Jack Sharry on Twitter Subscribe and stay in touch Apple Podcasts Spotify LinkedIn Twitter Facebook

Today, we're talking with Curtis Stevens, who, until recently, was Tinder's Director of Product Consumer Insights, and prior to that held product leadership roles at Qualtrics, Amazon, and more. In this episode, Curtis shares: How AI can actually be a tool for human connection His process behind Tinder's transformation into customer-centricity, with real, measurable results How to balance short-term user joy with long-term product innovation and future features And how AI is driving customer experience changes faster than research can follow, and what you can do to keep up Links LinkedIn: https://www.linkedin.com/in/curtis-b-stevens/ Chapters 00:00: Intro 03:03: Curtis Stevens' product journey 7:40: Challenges and strategies in customer experience 14:54: Curtis' journey workshops 20:41: AI's role in customer research 27:41: Conclusion Follow LaunchPod on YouTube We have a new YouTube page (https://www.youtube.com/@LaunchPodPodcast)! Watch full episodes of our interviews with PM leaders and subscribe! What does LogRocket do? LogRocket's Galileo AI watches user sessions for you and surfaces the technical and usability issues holding back your web and mobile apps. Understand where your users are struggling by trying it for free at LogRocket.com (https://logrocket.com/signup/?pdr). Special Guest: Curtis Stevens.

Erik and Kelsey discuss the integral role of Customer Success (CS) in a SaaS company, particularly how it can be leveraged for marketing and client engagement. Kelsey shares her journey in building the CS team at Justuno, the importance of identifying and promoting client success stories, and the tools she uses for content creation. They explore the challenges faced in content marketing, the significance of educational content, and the collaboration with technology partners to enhance client relationships. The discussion emphasizes the unique value of Justuno's customer service and the future potential of CS as a driving force for the company's growth.Topics we discuss:takeawaysCustomer Success is a powerful marketing tool.Kelsey has built the CS team over eight years.Identifying client success stories is crucial for marketing.Educational content is prioritized in their strategy.Patience is essential in content creation.Collaboration with technology partners enhances client success.Full screen promotions outperform traditional methods.CS leaders should embrace humor and authenticity.Measuring content success is vital for improvement.Building strong client relationships fosters trust and collaboration.

Dans cet épisode, Paul Pinault, CEO de DM91.tech, explique concrètement ce qu'est l'IoT et démontre comment il devient une commodité dans l'industrie : la vraie valeur se joue désormais dans la donnée et l'optimisation des procédés. À travers des exemples concrets et une plongée dans les technologies, il illustre comment capteurs et réseaux rendent enfin accessible la collecte de données à grande échelle. Une évolution qui transforme l'usine en un système piloté par la donnée et orienté performance.Hosted by Ausha. See ausha.co/privacy-policy for more information.

Christian and Betty are here to debrief the Mexico City Grand Prix.*SPOILERS FOLLOW*Lando Norris took down the track to take the top step of the podium and out himself back on the top of the Drivers' Championship standings. Plenty to unpack from this weekend, including Ollie Bearman's hugely impressive 4th place finish, George Russell dominating Betty's Radio Radar, and Christian channelling his inner luchador with a surprise choice of outfit.EXCLUSIVE NordVPN Deal ➼ https://nordvpn.comtfatc Try it risk-free now with a 30-day money-back guarantee!Make sure you follow us on all the socials and hit subscribe right here as there are still more famous faces from the world of Formula 1 joining us before the season finishes… YouTube: @fastcuriouspodTwitter: @fastcuriouspodInstagram: @fastcuriouspodTikTok: @fastcuriouspod Hosted on Acast. See acast.com/privacy for more information.

What if the next breakthrough in AI doesn't come from a giant data center or another LLM, but from a small Pittsburgh startup that's building artificial intelligence modeled on the human brain? Hit PLAY to hear from Chris Paradise and Nick Retos of Digital Dynamics AI—two founders chasing an idea that could redefine what AI is capable of. In just a year, they've gone from concept to prototype, and their KARIOS platform already challenges the limits of traditional AI thinking. Be one of the first to learn about this potentially disruptive AI technology. Let's jump into a clip from the full TechVibe Radio interview where they explain how biomimicry and brain-inspired design could push AI to the next frontier. And if you have a few more minutes click here for the full interview. Produced by the Pittsburgh Technology Council, this is a podcast for tech and manufacturing  entrepreneurs exploring the tech ecosystem, from cyber security and AI to SaaS, robotics, and life sciences, featuring insights to satisfy the tech curious.

A lot of B2B SaaS startups drown in vanity metrics while missing the core metrics that actually drive revenue growth. This tutorial walks you through the exact marketing trended funnel dashboard I've used with various clients to build proper measurement infrastructure and track the metrics that actually move the needle for your business in the early stages of GTM growth.This systematic approach to marketing measurement has helped clients identify where they're overspending, where to scale down budgets, and where to scale up to influence pipeline generation - against performance. Some clients have discovered 2-3x more qualified opportunities simply by analysing their data through this tracking approach.In this video, you'll discover:- The core funnel metrics every B2B SaaS startup should track.- Critical conversion rates that reveal where your funnel is performing well or not.- Which vanity metrics to avoid early on.- Why optimising too early can harm growth.- How to implement this measurement infrastructure using Google Sheets and your CRM.Perfect for B2B SaaS founders who need to understand which GTM channels actually work, and aspiring marketers who want to learn the systematic measurement approach that separates strategic marketers from tactical executors. This video focuses on building marketing infrastructure, not isolating and understanding "feel-good" metrics.

At Big Data LDN (BDL) 2025, Keboola CEO Pavel Dolezal presented a new data agent designed for all business users, not just engineers. With a mission to make AI, automation, and data easy to access, relevant, and useful across the organisation, Dolezal revealed that the data agent has been embedded with contextual intelligence and generative AI.“While we typically assist data engineers with building the pipeline, we took the same data agent and built a different environment for it — a chat-like environment. By default, the chat has context, knows what to do, knows where not to go,” the Keboola CEO unveiled on the Don't Panic It's Just Data podcast. In the EM360Tech podcast recorded live at BDL, Dolezal spoke to Christina Stathopoulos, the Founder of Dare to Data in the recent episode of the Don't Panic It's Just Data podcast. They talked about the new Keboola Data Agent and it plays a key role in AI-backed change and the growth of large language models (LLMs) in business.Context for AI-Backed Data Strategy Matters More“Anyone can be technical now. It's context that matters,” stated Dolezal, also the co-founder of Keboola. He presented a strong argument for why enterprise data strategies are falling short and how a new wave of smart tools will change that.“The pipeline of what you can do is limitless if you build it for people in business,” he added. “You can't keep data and AI just in the hands of engineers anymore. That model doesn't scale.”As businesses face a growing number of data sources — sometimes over 300 SaaS platforms and more than 80 departments — managing, governing, and activating that data has become a challenge. The appealing promise of AI often adds another layer of complexity.When AI Adds More ComplexityEnterprise leaders were told that AI would simplify data workflows. Instead, many found themselves managing disconnected tools and failed pilot projects.“We all read the MIT study. 95 per cent of AI proofs of concept don't make it to production,” the CEO of Keboola highlights. “Why? Because large language models (LLMs) need context. And enterprise data environments are anything but simple.”At Keboola, context is crucial, he emphasised. It includes not just metadata but also event logs, debug trails, and orchestration details, including the complete story behind every data product.“LLMs thrive on context. The more relevant context you provide, the better the outcome. But in today's data stack, where your context is spread across 15 tools, that's nearly impossible.”This is where Keboola's new Data Agent comes in. It is a generative AI interface built directly into data workflows, capable of understanding and acting on both the structure and state of a company's data.Watch the podcast for further insights on EM360Tech. Key TakeawaysFocus on context and domain knowledge rather than technical skills.Ease of acquiring technical skills compared to the importance of understanding business processes.Agents will run business processes both internally and externally.Need for infrastructure to support...

saas.unbound is a podcast for and about founders who are working on scaling inspiring products that people love, brought to you by https://saas.group/, a serial acquirer of B2B SaaS companies. In episode #46 of season 5, Anna Nadeina talks with Alex, CEO and Founder of Competera, a pricing platform helping retailers increase their revenue. ----------- Episode's Chapters ----------- 00:00 - Meet Alex: From Medical Engineering to AI 02:33 - The Birth of Compra: Early Challenges and Innovations 07:47 - Navigating Enterprise Sales and AI Integration 10:13 - Overcoming API Roadblocks and Pivoting Strategies 15:18 - AI in Enterprise: Adoption and Challenges 30:02 - Discussing Pricing Strategies for Enterprise Customers 31:25 - Understanding Customer Acquisition Costs 32:51 - The Importance of Customer Feedback and Pricing Adjustments 37:26 - Challenges and Learnings in Enterprise Sales 39:40 - The Role of M&A Advisors and Strategic Partnerships 43:54 - Balancing Work and Life as a Founder Alex - https://www.linkedin.com/in/alexhalkin/ Competera - https://competera.ai/ Subscribe to our channel to be the first to see the interviews that we publish - https://www.youtube.com/@saas-group Stay up to date: Twitter: https://twitter.com/SaaS_group LinkedIn: https://www.linkedin.com/company/14790796

In the finale of our new miniseries, Vertical SaaS: Fintech Disruption by a Thousand Cuts (sponsored by our friends at Pipe), we confront the biggest questions yet, like: How can maturing vertical SaaS companies scale without losing the obsessive focus that made them indispensable?  Should they expand into adjacent markets, or double down on their niche? And, as AI transforms oversight from slow, sample-based audits into continuous real-time monitoring, who will own the responsibility for keeping these systems safe? With Luke Voiles (CEO of Pipe) as cohost, we welcome special guest Darragh Buckey (Founder and CEO of Increase – and, before that, the first employee at Stripe). Along the way, we get candid about the capital “S” Specialization that's making this ecosystem work: Vertical SaaS companies own the workflows, fintech partners like Pipe handle capital and risk, and infrastructure providers take on the tough, regulated money movement no one else wants to touch. Get a front-row seat to how the “lasagna” of financial services is being rebuilt, one specialized layer at a time. And how, if we get it right, it will serve small businesses, developers, and the broader economy far better than the systems it's replacing. Don't miss this closing chapter of our Vertical SaaS: Fintech Disruption by a Thousand Cuts miniseries. Thanks for listening!  This episode was brought to you by Pipe. Pipe helps vertical SaaS platforms unlock fast, flexible capital, right inside their product. Learn more at pipe.com/fintechtakes. Sign up for Alex's Fintech Takes newsletter for the latest insightful analysis on fintech trends, along with a heaping pile of pop culture references and copious footnotes. Every Monday and Thursday: https://workweek.com/brand/fintech-takes/ And for more exclusive insider content, don't forget to check out my YouTube page. Follow Alex:  YouTube: https://www.youtube.com/channel/UCJgfH47QEwbQmkQlz1V9rQA/videos LinkedIn: https://www.linkedin.com/in/alexhjohnson Twitter: https://www.twitter.com/AlexH_Johnson Follow Luke: https://www.linkedin.com/in/luke-voiles/ Follow Darragh: https://www.linkedin.com/in/darragh-buckley-56096312/ Learn more about Pipe here.

This week on the Digi-Tools in Accrual World we share the latest updates in accounting and fintech news.  We kick off with insights on the recent Digital Disruptor Awards and plans for next year's event.  App News segment covers big names like Iris Software, Telleroo, Xero, and Monzo, with notable updates on faster payments, MTD tools, and AI-driven solutions.  We explore evolving payroll systems, the impact of AI on product development, and integrating multi-functional solutions to streamline business processes and data security.  Don't miss our discussion on recent AWS outages and their impact on firms, plus the ongoing debate between Xero and QuickBooks users over bank reconciliation. Stay ahead in the world of accounting tech with this comprehensive and engaging episode.   Learn how to harness EVO in Unleashed pre client meetings. Join our Partner Product Webinar on the 17th November at 9pm GTM - https://hubs.la/Q03Q2dcL0   00:00 Introduction 04:44 AI's Role in Rapid Evolution: A Discussion with Ben Carter / Unleashed App News 15:03 AWS outage slows down multiple SaaS platforms 16:48 Debate: Cloud Dependency and Resilience 20:50 Xero vs QBO: accountants debate the best bank rec tool 27:11 Sage powers Monzo's new Making Tax Digital tool 28:44 IRIS partners with Telleroo for faster payments 30:31 Modulr's Confirmation of Payee for Batch Payments 32:14 Pleo launches embedded finance solution for SMEs 35:05 Apron's Accounts Receivable Tool 38:06 Appventory's New Onboarding Methods 41:25 Joiin's Live Data Integration with Excel 45:27 From Fragmentation to Integration: The Evolution of Employment Tools - Employment Hero 55:06 Like and Subscribe!

In this episode of The Business of Tech, host Dave Sobel engages in a conversation with Tammy Cannizzaro, the Chief Marketing Officer at Thrive, a company with over a century of experience that has transitioned from selling Yellow Pages ads to providing a comprehensive SaaS-enabled marketing solution for small businesses. Tammy outlines Thrive's mission to help small businesses grow by enhancing their online presence and competing effectively against larger enterprises. She emphasizes the importance of a structured approach to marketing, which includes getting found online, converting leads into customers, and fostering customer loyalty.As the discussion progresses, Tammy highlights the significant impact of artificial intelligence (AI) on small businesses, particularly in marketing. She shares insights from Thrive's research, indicating that a growing number of small business owners are adopting AI tools to improve their marketing strategies. Tammy explains how AI can assist in optimizing online visibility, managing customer reviews, and maintaining fresh website content, all of which are crucial for small businesses looking to thrive in a digital landscape increasingly dominated by AI technologies.Tammy also addresses the challenges small business owners face when integrating AI into their operations. She advocates for a gradual approach, suggesting that starting with simple AI applications can yield meaningful results without overwhelming business owners. By focusing on practical use cases, such as automated customer outreach and review responses, small businesses can leverage AI to enhance their marketing efforts and drive repeat business. This incremental strategy allows them to build confidence and familiarity with AI tools over time.Finally, the conversation touches on the importance of customer retention and the balance between marketing-driven and product-led growth. Tammy emphasizes that understanding customer needs and preferences is key to delivering effective SaaS solutions. Thrive aims to meet customers where they are, offering various engagement options, from hands-on support to self-service models. This flexibility ensures that small business owners can choose the approach that best suits their unique circumstances, ultimately fostering long-term relationships and driving growth.

This episode is sponsored by AGNTCY. Unlock agents at scale with an open Internet of Agents.  Visit https://agntcy.org/ and add your support. How is Coxwave Redefining AI Evaluation? In this episode of Eye on AI, host Craig Smith is joined by Yeop Lee, Head of Product at Coxwave. Together they explore how teams move beyond accuracy-only metrics to outcome focused evaluation with Coxwave's Align. We look at how Align measures satisfaction, trust, and task completion across chat, email, and voice, how LLM as judge pairs with human review, and how product teams search conversations to find hidden failure patterns that block adoption. Learn how leading companies design an evaluation stack that guides prompts, agents, and UX, which pitfalls to avoid when shipping updates, and which metrics matter most for success, including completion rate, CSAT, retention, and cost per resolution. You will also hear how to run experiment tracking with model and prompt change logs, set up governance that prevents regressions, and choose between SaaS and on premise deployments that meet security and compliance needs. Stay Updated: Craig Smith on X: https://x.com/craigss Eye on A.I. on X: https://x.com/EyeOn_AI

In this episode, we welcome Kevin Brockland, Managing Partner and Founder of Indelible Ventures. Kevin is a prominent investor dedicated to being an active, positive contributor to the Southeast Asian startup ecosystem, with a particular focus on the Philippines, Thailand, and Malaysia.Kevin takes us through his journey, starting from a small town in Missouri (the "Show-Me state"), where he developed his entrepreneurial mindset through an early hustle of reselling bulk candy at school. He shares how being kicked out of high school limited his options and forced him to hustle, working a full-time job at an automotive firm and an overnight hotel shift while attending night school. This led to a period of extensive world travel and study in Europe and Mexico before he pursued his MBA in finance and Master's in international relations at Seton Hall, just as the 2008 financial crisis hit. Kevin then discusses his investment thesis, which centers on addressing the geographic and stage gaps in Southeast Asian institutional capital. He explains why he believes the market is at a tipping point to shift from consumer tech to enterprise/B2B technology and how his philosophy of "give first, get later" is key to building an active ecosystem. Finally, he offers his perspective on the current wave of AI in Southeast Asia and how it is changing the "build versus buy" dynamic for corporate SaaS.Links/Sponsors:OneCFO: The Philippines' leading fractional CFO services provider. https://www.onecfoph.co/Hustleshare is powered by Podmachine Hosted on Acast. See acast.com/privacy for more information.

In this CPQ Podcast episode, Frank Sohn talks with Martin Johansen, founder of Mercura, a Denmark-based CPQ vendor focused on small to mid-sized manufacturers. With a background in finance and international business, Martin started Mercura straight out of college—initially building a configurator “by accident” for a customer request—and has since grown it into a SaaS platform used across Europe. We discuss Mercura's no-code setup and short implementation cycles (often 1–2 months), its support for cost-plus pricing, and partner/distributor workflows where channel users can upload and manage their own price lists. Martin explains how Mercura's in-browser 3D visualization enables room planning, snap-to placement, and collision detection in real time. While Mercura doesn't connect directly to CAD suites, customers can supply STEP files or drawings for CPQ-side visualization. A big portion of the conversation covers integrations—especially Microsoft Dynamics 365 Sales and Microsoft Business Central—plus experience with PIM solutions and HubSpot. Martin shares how Mercura applies AI on the admin side to speed configuration/rules setup, why headless is not a near-term priority, and the company's focus on manufacturers in sectors like playground equipment and healthcare (typical 5–200 users). We also touch on his sales mindset, weekly tennis/soccer routine, and how the book Work the System shapes Mercura's process discipline. Listen in for practical insights on delivering an easy-to-implement CPQ with modern visualization and tight Microsoft integrations.

Send us a textThis week, we're joined by Paul Dodd, Senior Operating Partner and Head of Go-to-Market Operations at Sixth Street, one of the most respected private credit and private equity firms in the world. This episode is Part 2 of our Business Operations 101 series, and we're digging into how firms like Sixth Street actually create value inside the companies they invest in. Paul specializes in helping tech and SaaS businesses scale efficiently, so instead of talking about dealmaking, we're talking about what happens after the deal closes: how to turn strategy into growth.Paul walks us through what “go-to-market” really means in practice, from aligning sales and marketing to optimizing customer retention and pricing. He explains how small operational improvements, like shortening onboarding time or using AI to coach sales teams, compound into massive enterprise value during the investment period. We also get into how Sixth Street's operating and deal teams work hand-in-hand, why culture and process discipline matter as much as capital, and how flexibility in capital structure allows them to back great companies through every stage of growth.And finally, we tackle the viral headline of the week: OpenAI is hiring ex–investment banking analysts and MBAs to remove the "drudgery" of junior banking work. We break down whether AI can really replace analysts, why building financial models is still critical to learning the business, and what it means for the future of entry-level Wall Street jobs.Paul Dodd is a Go-to-Market, Operating Partner at Sixth Street focused on providing core expertise to organizations in order to maximize revenue generation and profitable growth.Before joining Sixth Street, Paul served as Chief Growth Officer at SecureLink, SVP of Sales for Compeat Tech, Head of Sales for the GA360 Measurement Suite at Google, and previously served as Vice President of World Wide Sales at Adometry, a leading provider of multi-touch attribution & cross-channel intelligence, acquired by Google in 2014. Before Adometry, Paul served as Vice President of Sales for Retail at Bazaarvoice and as Chief Strategy & Global Sales Officers for Design Reactor/6Connex.He holds an MBA from Baylor University-Hankamer School of Business, an M.A. in Psychology from the University of Santa Monica, and a B.A. in Accounting from Kent State University.For 20% off Deleteme, use the code TWSS or click the link HERE! Shop our Self Paced Courses: Investment Banking & Private Equity Fundamentals HEREFixed Income Sales & Trading HERE Our content is for informational purposes only. You should not construe any such information or other material as legal, tax, investment, financial, or other advice. (Learn more HERE)

Send us a textIn this episode of The AI Advantage, Matt Brown speaks with Amelia Taylor, a revenue strategist helping SaaS and cybersecurity companies grow by combining human EQ, relationships, and artificial intelligence. Amelia explains how she builds “SWAT teams” within organizations to test bold ideas, prove value through data, and create change when others are stuck in old ways of selling.The conversation explores why many companies struggle to adopt AI, how to ask better questions that drive action today instead of speculation about tomorrow, and why the future of sales belongs to those who can merge technology with human intuition. Amelia shares how prompt design, trust, and iteration can transform entire sales operations, why SDR roles are evolving, and what it means to lead with curiosity in a world where innovation never stops.Support the show

Episode 171 of Open Tech Talks brings a powerful conversation with Marc Pickren, the turnaround CEO behind multiple successful SaaS revivals and now the driving force at Springbot. Host Kashif Manzoor explores how today's businesses can stay resilient, profitable, and human-centered amid the rapid evolution of AI and automation. Marc has spent the last decade reviving software companies between $5 million and $50 million in revenue, mastering the art of building “unkillable companies.” In 2025, he decided to take the leap from corporate turnarounds to entrepreneurship, rolling up multiple firms into the Springbot ecosystem. The result: a capital-efficient, profitable SaaS company thriving amid uncertainty. Their conversation goes deep into how AI is reshaping sales and marketing, not through hype but through measurable, real-world practices. Marc explains why most marketing dashboards lie, why pop-ups destroy conversion trust, and how AI-powered automation can help teams focus on what truly matters: genuine human conversations that drive revenue. He also shares how his team uses demo-video workflows to replace the traditional “demo call,” reducing friction and turning qualified interest into business faster. Kashif brings a personal perspective to the discussion, connecting Marc's approach with his own journey advising AI-first startups and building AI Tech Circle's Generative AI Maturity Framework. He recalls how curiosity, something Marc calls “the new survival skill”, became the foundation for building his own AI-driven playbooks and newsletters that reach global professionals every weekend. Episode # 171 Today's Guest: Marc Pickren, CEO, Springbot Marc Pickren, CEO and entrepreneur at Springbot.com, has achieved a 3X founder exit, has raised $50M in capital, was nominated for CEO of the Year in Austin, and was named Top CEO for Women in 2019. Website: MarcPickren What Listeners Will Learn: Design AI-enabled growth systems that prioritize efficiency and profit over vanity metrics Replace outdated funnels with conversation-centric sales frameworks Integrate AI automation and intelligent business agents without losing the human touch Identify go-to-market data priorities and build accurate ideal-customer profiles Avoid subscription clutter and AI-wrapper product fatigue while keeping focus on tangible outcomes Foster curiosity and adaptability as the most critical leadership mindset in 2025 Pivot continuously and let customers shape your product, not vanity feature roadmaps   Resources: MarcPickren

About Walid Amarir:Walid Amarir is the Co-founder and CEO of WaLead.ai, a LinkedIn automation tool built to solve the scalability problems he experienced firsthand running a LinkedIn marketing agency. At just 23, Walid has an unconventional background—he was a professional eSports player earning his parents' salaries by age 18, then studied Physics and Mathematics in the UK before realizing he preferred building businesses to academia. After identifying critical gaps in existing LinkedIn automation tools while scaling his agency, Walid made the jump from service provider to SaaS founder, building a lean, efficient platform that maintains authenticity while automating outreach at scale.About WaLead.ai:WaLead.ai is a LinkedIn automation and prospecting platform designed for B2B companies that need to scale their outbound sales without sacrificing personalization. Built by someone who lived the pain points of existing tools, WaLead solves the core problem that legacy platforms face: they're built for individual users, not for teams managing multiple accounts and campaigns. The platform integrates seamlessly with existing sales workflows, helping companies automate LinkedIn outreach while maintaining the human touch that drives real conversations and conversions.Show Notes:00:00 Introduction to Walid and His Journey02:48 Transition from Agency to Building WaLead.ai05:48 Strategies for LinkedIn Success09:04 Building a Scalable LinkedIn Tool11:59 Managing Integrations14:41 Geographical Advantages and Market Strategy18:01 Metrics and Follow-Up Strategies20:53 Building an Effective LinkedIn Profile23:44 Engagement and Community Building on LinkedIn26:37 Final Thoughts and Future Directions

Darryl Pahl is the co-founder of DFnet, a Seattle-based company providing clinical trial data management software and services. Along with his wife and co-founder, Lisa Andrzejczyk, Darryl started the company more than 20 years ago after careers at Fred Hutchinson Cancer Research Center. They built DFnet around long-term client relationships in global health and clinical research. The company runs DFdiscover, an enterprise-grade electronic data capture and management platform used in clinical studies worldwide. With offices in the U.S., Canada, and South Africa, DFnet has grown to more than 50 employees and is approaching $10M in revenue. Clients range from the U.S. Department of Veterans Affairs to nonprofits like PATH and major universities. Still independent and bootstrapped, DFnet has made key moves to prepare for the future—such as bringing in a growth-focused CEO, diversifying beyond single-client risk, and shifting legacy software to SaaS and services. Darryl shares the lessons from running conservatively under debt, buying rather than building, and building a global company rooted in relationships and practical execution. Key Takeaways Stability First Growth – Carrying a 10-year SBA loan forced conservative growth and taught the discipline of stability over risky expansion. Buying Not Building – Acquiring DataFax brought 35+ new clients overnight and proved that buying legacy software can be smarter than reinventing. Services Plus Software – Unlike pure SaaS, DFnet thrives by combining consulting, hosting, and software in a regulated field. Spouse Founders Structure – Their 51/49 ownership split avoided deadlocks and kept marriage and business aligned. This Interview Is Perfect For SaaS founders balancing growth and control Founders considering succession or sale Bootstrapped entrepreneurs in niche B2B markets Anyone curious about global health data and impact-driven tech Quote from Darryl Pahl, co-founder of DFnet "The best position to be in is to say that in three to five years, we would be crazy to sell this company. It's doing so well. That would be the perfect thing. And what we're not looking for is a giant payout. We have a very modest lifestyle. “But is an asset, it is a business, and there's a business aspect. It would have to be the right type of buyer. It has to be the right fit. It has to be the right person or group that is respectful to our clients, our employees, and us as owners.  “So the ideal would be to have the luxury of either not selling or being more selective rather than responding to random emails from some financial buyer or search funder.” Links Darryl Paul on LinkedIn DFnet on LinkedIn DFnet website Podcast Sponsor – Fraction This podcast is sponsored by Fraction. Fraction gives you access to senior US-based engineers and CTOs — without full-time costs or hiring risks. Get 10 to 30 hours per week from vetted and experienced US-based talent. Find your next fractional senior engineer or CTO at fraction.work. You can start with a one-week, risk-free trial to test it out. The Practical Founders Podcast Tune into the Practical Founders Podcast for weekly in-depth interviews with founders who have built valuable software companies without big funding. Subscribe to the Practical Founders Podcast using your favorite podcast app or view on our YouTube channel. Get the weekly Practical Founders newsletter and podcast updates at practicalfounders.com. Practical Founders CEO Peer Groups Be part of a committed and confidential group of practical founders creating valuable software companies without big VC funding.  A Practical Founders Peer Group is a committed and confidential group of founders/CEOs who want to help you succeed on your terms. Each Practical Founders Peer Group is personally curated and moderated by Greg Head.

In this episode of TECHtonic, host Thomas Lah, Executive Director of TSIA, speaks to Doug Duker, Global Leader of Customer Success at You.com, to unpack what truly sets AI-native startups apart from traditional SaaS companies. Doug shares how You.com evolved from a consumer search product into an enterprise-focused AI platform—emphasizing data security, multi-model agility, hallucination control, and personalized AI training for knowledge workers.Together, they dive into the massive transformation facing today's businesses: how to close the “last mile” of AI adoption, re-skill workforces, measure ROI, and redefine the role of customer success in an AI-first world. It's a candid look at how AI-native startups are reshaping what enterprise success means in the digital era.

We have been deep into the AI ecosystem looking for solutions to operational problems both in our own agency and for our clients.We've also noticed other agency owners and SaaS businesses jumping on the AI bandwagon and building their own AI tools and reselling them wrapped as a service.Tony Small from HeyLibby joins us on this episode and gives us insight into why and how he started his AI call agent and receptionist, why he positioned it in the niche he did, and how he actually goes about selling it to businesses.----------------------------------JOIN THE FREE DISCORDhttps://discord.gg/uvHRRRFVRDOur recommended agency tools:everbrospodcast.com/recommended-tools/----------------------------------⭐⭐⭐⭐⭐As always, if you enjoyed this episode or this podcast in general and want to leave us a review or rating, head over to Apple and let us know what you like! It helps us get found and motivates us to keep producing this free content.----------------------------------Want to connect with us? Reach out to us on the everbrospodcast.com website, subscribe to us on YouTube, or connect with us on socials:YouTube: @agencygrowthpodcastTwitter/X: @theagency_uLinkedIn: linkedin.com/company/agencypodcastFacebook: facebook.com/theagencyuInstagram: @theagencyuReddit: r/agency & u/JakeHundleyTikTok: @agency.u

We sit down with Jeff Perry, CRO at Carta, to explore how growth leaders redefine success when capital tightens, buyers get smarter, and AI reshapes cost structures.  We unpack how growth has changed, why IPO-ready now means post-IPO durable, and how Carta scaled from a cap table tool to an ERP-like platform for private capital while staying efficient and customer-first. Jeff shares concrete tactics for moving upmarket, using AI wisely, and building teams that perform under pressure.• redefining fast growth and IPO readiness in private markets• evolving from SMB velocity to enterprise endurance• expanding from cap tables to fund admin and private credit• measuring meetings as a leading productivity indicator• using curated events and customer proofs over vanity metrics• aligning sales, marketing and product around shared pipeline• adding K-1 tax and LP data products to deepen value• AI as a force for 10x productivity, not headcount cuts• disciplined acquisitions to accelerate the CFO ERP vision• leadership choices: pausing sales, saying no when not readyIPO dreams used to hinge on hitting 100 million ARR. That world is gone.  Jeff takes us from Carta's earliest days digitizing stock certificates to building a networked platform that now powers cap tables, fund administration, LP data, and private credit—an evolving ERP for the office of the private capital CFO.We dig into the hard pivots after the 2021 surge: why “more capacity” stopped working, how meetings per AE became a reliable leading indicator, and where curated events and customer-led storytelling outperform saturated digital tactics. Jeff explains the move upmarket into venture and private equity, the new enterprise seller profile it requires, and the partnership with marketing to identify real switching intent. He also shares how acquisitions like Accelex and Sirvatus support an end-to-end vision across funds, LPs, and loan servicing.AI looms large throughout. Jeff contrasts application-layer SaaS with AI-native companies carrying heavy compute costs, and why that bifurcation changes CAC, payback, and headcount plans. Rather than using AI to cut roles, he shows how Carta uses it to 10x productivity—accelerating RFPs, territory coverage, and performance workflows—while standardizing experiments so wins become reusable process. Along the way, we unpack bold leadership choices: pausing sales to protect implementation quality, and walking away from a marquee IPO transition when the product wasn't ready.If you care about efficient growth, enterprise GTM, and building products that compound value across a connected market, this conversation delivers practical playbooks and memorable lessons on performing under pressure. Follow, share with a teammate, and leave a quick review to help more operators find the show.Jeff Perry: https://www.linkedin.com/in/jeff-perry-380233/Jeff is a proven revenue superstar, whose career journey spans Oracle and DocuSign.  Under his leadership as CRO at Carta, Carta's annual recurring revenue scaled from approximately $20 million ARR to $450 million ARR. Jeff attended Santa Clara University where he received a B.S. in Political Science and where he also played NCAA baseball.Website: https://www.position2.com/podcast/Rajiv Parikh: https://www.linkedin.com/in/rajivparikh/Sandeep Parikh: https://www.instagram.com/sandeepparikh/Email us with any feedback for the show: sparkofages.podcast@position2.com

For many ambitious founders, bootstrapping is a slow death. After building a profitable, high seven-figure SaaS company for 10 years, Sameer Narkar realized his self-funded model was no longer enough to win. In this interview, Sameer explains why the AI revolution is forcing successful bootstrapped companies into raising funds to move faster. He breaks down his decision to seek investment after a decade of profitability, why he believes thinking about an exit is a distraction from building a great product, and how he plans to use the new capital to "buy growth" by investing in experienced sales teams and partnerships rather than burning cash on ads. Check out the company: https://konnectinsights.comBook a 1-on-1 advisory session with me to apply these principles to your business: https://calendly.com/wltb/advisory

How does the resident experience tie back to property operating economics? What were the contributing factors to the early serial entrepreneur ventures that David dabbled in? Where did David's early interest in technology stem from? How is the origin story of DoorLoop tied to David's prior startup PracticePanther even though these two companies are in completely unrelated industries? Why is the property management software space filled with so much competition and despite this why are there more entrants each year? How do easy-to-use software development tools fuel the creation of products that are in fact not viable businesses? Why is having a founding team so important when starting a new SaaS business? How was launching in Covd different than expected for DoorLoop? Why is it important to capture customer feedback from all engagement systems and not just through annual customer surveys? How is DoorLoop integrating AI across its solution stack?David Bitton - Co-founder of DoorLoop, joins Proptech Espresso to answer these questions and discuss how real estate investing alongside his parents after college led to a brief career as a realtor and ultimately set the stage for becoming a proptech founder.

Suneera Madhani built Stax from an idea her employer rejected into a $1B fintech unicorn processing over $25B in payments. In this interview, the Stax co-founder shares how she went from selling credit card terminals out of her car to pioneering the first subscription-based payment processor, raising over $500M in capital, and scaling a company now generating $120M+ in revenue. From turning down a $17.5M acquisition offer to building an omnichannel platform before “fintech” was even a word, Suneera breaks down the strategies, resilience, and leadership lessons that took her from a scrappy founder to one of the most successful female entrepreneurs in tech. What you'll learn from this interview: • How Suneera turned a rejected idea into a billion-dollar company • The scrappy marketing tactics that got her first 250 customers • Why she turned down a $17.5M acquisition offer early on • The lessons from raising over $500M in funding and navigating investors • How to build an MVP using white-label solutions and customer feedback • The importance of execution and focus over “big ideas” • Why resilience, intuition, and community are critical for long-term success • The rebrand from FatMerchant to Stax and what it taught her about scaling By the end of this interview, you'll walk away with proven insights for scaling a fintech or SaaS company from zero to unicorn status—so you can apply the same strategies to grow your own business with focus and resilience. SAVE 50% ON OMNISEND FOR 3 MONTHS Get 50% off your first 3 months of email and SMS marketing with Omnisend with the code FOUNDR50. Just head to https://your.omnisend.com/foundrhttps://your.omnisend.com/foundr to get started. HOW WE CAN HELP YOU SCALE YOUR BUSINESS FASTER Learn directly from 7, 8 & 9-figure founders inside Foundr+ Start your $1 trial → https://www.foundr.com/startdollartrial PREFER A CUSTOM ROADMAP AND 1-ON-1 COACHING? → Starting from scratch? Apply here → https://foundr.com/pages/coaching-start-application → Already have a store? Apply here → https://foundr.com/pages/coaching-growth-application CONNECT WITH NATHAN CHAN Instagram → https://www.instagram.com/nathanchan LinkedIn → https://www.linkedin.com/in/nathanhchan/ CONNECT WITH SUNEERA MADHANI Website → https://staxpayments.com/ Instagram → https://www.instagram.com/suneeramadhani/ LinkedIn → https://www.linkedin.com/in/suneeramadhani/ FOLLOW FOUNDR FOR MORE BUSINESS GROWTH STRATEGIES YouTube → https://bit.ly/2uyvzdt Website → https://www.foundr.com Instagram → https://www.instagram.com/foundr/ Facebook → https://www.facebook.com/foundr Twitter → https://www.twitter.com/foundr LinkedIn → https://www.linkedin.com/company/foundr/ Podcast → https://www.foundr.com/podcast

What happens when a tech leader with a background in democratizing design at companies like Figma turns their attention to architecture? This week, we're joined by Radhika Parashar Narain, Head of Marketing at Arcol, a software company reimagining how architects design and collaborate.Coming from the world of Software as a Service (SaaS), Radhika offers a fresh and insightful perspective on a profession she finds fascinatingly complex and creative, yet overdue for better tools. She shares her initial shock at the fragmented, inefficient, and often joyless workflows architects are forced to navigate. Radhika discusses the cultural and practical hurdles to tech adoption in an industry rooted in tradition, from the high "cost of change" after years spent learning legacy software to a scarcity mindset around collaboration. The conversation explores how Arcol, founded with a "Figma for BIM" ethos, aims to bring simplicity, accessibility, and collaboration to the earliest stages of design.Ultimately, Radhika's vision is not about disruption for its own sake, but about empowerment. She argues that by embracing intuitively designed, cloud-based tools, architects can reduce friction, foster collaboration, and rediscover the joy in their craft. Her hope is for architects to raise their standards for the software they use every day."My hope for the profession is for architects to have as high expectations as we have of the tools that we can foresee and we can kind of imagine can bring that joy back to the process." - Radhika Parashar NarainThis episode concludes with a call for the profession to see technology as a leverage point. Radhika encourages architects, especially students and smaller firms, to experiment early, build collaboration as a muscle, and use new tools to "punch above their weight." By democratizing access to powerful, well-designed software, the next generation can move beyond the limitations of legacy systems and focus on what they do best: creating the built world.Guest:Radhika Parashar Narain is the Head of Marketing at Arcol, a software company building a new generation of design and collaboration tools for architects. With a background in SaaS and design technology, including a tenure at Figma, she is passionate about empowering creators with better tools and making design more accessible to everyone.Is This Episode for You?This episode is for you if:✅ You are an architect frustrated with your current software and workflows. ✅ You are curious about how the mindset of Silicon Valley (SaaS) applies to the AEC industry. ✅ You want to understand the challenges and opportunities of tech adoption in architecture. ✅ You believe in the power of technology to democratize design and empower smaller firms. ✅ You are a student or educator looking for the next wave of tools that will shape the future of practice.

How can construction finally break free from silos and unlock the full power of connected data? Recorded live at Autodesk University 2025 in Nashville, this conversation with Lalith Subramanian, Global VP of Product & Engineering, explores the future of an end-to-end industry cloud — where design, preconstruction, and operations all work from the same living data. Lalith shares insights on creating trust in AI, practical collaboration frameworks, and how selective data sharing is redefining what's possible for teams across the built environment.

How can customer connection transform your marketing strategy and drive authentic growth?In this episode of The Hard Corps Marketing Show, I sat down with Lina Tonk, CMO at Recurly and seasoned marketing leader. Lina shares her expertise on why regular, direct conversations with customers are essential to building meaningful marketing strategies that truly resonate.Lina breaks down the myth that marketing strategies can succeed without customer interaction and explains how repeated engagement uncovers evolving customer needs. She dives into the importance of tailoring events and campaigns based on customer preferences, balancing virtual and in-person connections, and fostering a community that turns customers into authentic brand advocates.In this episode, we cover:Why talking to your customers frequently is critical for effective marketingHow to personalize engagement based on deep customer insightsThe power of in-person vs. virtual events and respecting customer preferencesMeasuring ROI beyond leads, including sentiment and sales alignmentThe human element at the core of SaaS marketing and leadershipIf you're ready to build a customer-first marketing approach that drives long-term growth, this episode is packed with actionable insights you won't want to miss!

Aydin sits down with Filip Skrzesinski, co-founder of Subframe, to unpack how AI and code-native design tools are collapsing the classic PM → design → engineering handoffs. Filip explains why “pictures to code” is an unfair ask of engineers, shows how Subframe lets teams design directly in the same material as production code, and demos building a Fellow feature—from screenshot → design system match → working prototype—without access to Fellow's codebase. They close on what's next: organizations training their own “house models” to reflect product taste, patterns, and constraints so more people across the company can truly build.Key takeawaysDesign in the same material as code: Subframe treats UI work as editable code, eliminating fidelity loss from design handoffs.Fewer stages, faster loops: PMs, designers, and engineers collaborate in one artifact; prototypes look and behave like the real app.AI as a trained teammate, not a slot machine: Teams will shape models with system prompts, snippets, and feedback—like mentoring a junior designer.Front-end ownership shifts: Designers can own front-end structure and components; engineers wire up backends and complex logic.Prototype to PRD: High-fidelity prototypes beat docs for alignment, user testing, and speed.Timestamps00:00 - Introduction 01:00 Fil's path: audio engineering → CS → design → startup co-founder03:48 Builders everywhere: from Dreamweaver → Webflow → Shopify → now “apps”04:01 What Subframe is: a design tool rooted in code05:48 Bridging LLMs (great at code) with visual design context08:09 The architect vs. printer analogy for product design12:23 Back to the show: “The new way” is collapsing steps and handoffs14:07 “Five-year” vision (sooner than you think): design → code with agents in the loop16:31 Training models on your org's taste: like raising a puppy—examples & theory19:15 Today's demo plan: build a Fellow feature in Subframe without codebase access21:04 Recreating Fellow's UI: import colors/typography; screenshot → layout23:07 Don't fight the AI: let it rough-in, then designers perfect in visual mode24:11 Why prototypes should look native (not “off-brand” sandboxes)26:07 Syncing components to codebases; where Subframe stops (front-end) and engineers continue (backend)28:33 Programmatic (deterministic) UI code & generative for visuals30:00 PMs in the tool: prompt to add a Share dialog with transcript and video context35:08 Exploring multiple design variations; mix-and-match patterns (“snippets”)37:57 From design to interactive prototype via annotations (“do this on click…”)45:22 First build runs: working Share flow; alert updates after sending47:02 Export code → Cursor/GitHub; hand off real components48:08 The next 12 months: more ideas shipped, more makers, less gatekeepingTools & technologies MentionedSubframe — Code-native design tool for building UI/UX; designs directly edit the underlying code; syncs components to your repo.Fellow.ai — AI meeting assistant with privacy controls; accurate summaries, actions, decisions; broad SaaS integrations.Cursor — AI-assisted code editor; good for continuing from exported Subframe code to production.GitHub — Repo hosting and collaboration for shipping the generated/edited UI code.AI code agents — Used by engineers to wire front-end to backend services and data.Squarespace / Webflow / Dreamweaver — Prior waves that democratized web creation; backdrop for today's “apps layer.”Shopify — Example of no-code/low-code e-commerce; analogy for app building's democratization.Lovable / Bolts / V0 — AI code/prototyping tools referenced as peers for generating working app scaffolds.Slack / Asana / HubSpot / Salesforce / Linear / Jira / Confluence — Systems Fellow integrates with to push notes, actions, and records.Subscribe at⁠ thisnewway.com⁠ to get the step-by-step playbooks, tools, and workflows.

Sumit Rai, Chief Product Officer of elevate.io, was recently interviewed by Cirina Catania, OWC Radio's Showrunner and Host. Elevate.io is Blackbird's new SaaS platform, a revolutionary online video editor and content creation solution aimed at the fast-growing creator economy. ABOUT OWC: Other World Computing, under the leadership of Larry O'Connor since he was 15 years old, has expanded to all corners of the world and works every day to create hardware and software that make the lives of creatives and business-oriented companies faster, more efficient and more stable.  Go to MacSales.com for more information and to discover an ecosystem that serves your needs.  ABOUT CIRINA CATANIA: Cirina Catania, is a successful filmmaker, former Sr Vice President of Worldwide Marketing at MGM-UA and United Artists and one of the co-founders and former director of the Sundance Film Festival. She is the founder, CEO and Executive Director of the non-profit, High School Media Collective. Cirina is Founder/Lead Creative at the Catania Group Global, Showrunner and Host of OWC RADiO and partner, Lumberjack System, as well as Tech Ambassador for companies such as Blackmagic Design.  She is a long-time member of the Producers Guild, Writers Guild, Cinematographers Guild, the National Press Club, National Press Photographer's Association, and more. She has worked as a writer, director, supervising producer, cinematographer, post-producer, or marketing exec on over 150 film, television and new media projects for the big screen as well as for networks such as National Geographic and Discovery.  

In this episode, Jeff Mains sits down with Casey Woo, a renowned tech operator, investor, and co-founder of the Operators Guild. Casey introduces the concept of the “Scaler”—an elite generalist who thrives in the chaotic, ever-changing environment of early-stage SaaS startups. The conversation dives deep into what makes scalers indispensable, why specialists often struggle in startup settings, and how AI is shifting the landscape for operators and business leaders. Casey offers practical frameworks, shares battle-tested leadership lessons, and explains how founders can build more resilient and focused teams to avoid the burnout common among high-performing scalers and ops leaders.Key Takeaways00:00 "From Loneliness to Operators Guild"03:25 "Misleading Job Titles and Roles"09:47 "AI Reshapes Roles, Specialists Evolve"11:08 "Rise of Special Forces in Business"15:04 "Balancing Focus and Ambition"19:45 "Focus on Core Business Metrics"21:05 Pitfalls of Over-Hiring Too Early27:06 "Quality Checks, Trust, and Community"27:57 "Staying Engaged to Master AI Tools"33:07 "AI Fluency as Essential Skillset"37:11 "Understanding Diverse Business Languages"39:23 Operators Guild & FOG Investing CommunityTweetable Quotes“We are not defined by titles—we are multidisciplinary, and we are elite specialists at being generalists.” — Casey Woo“The earlier you go, the more change there is per day. You need people who can adapt and wear multiple hats.” — Casey Woo“AI isn't replacing the scaler—it's making the generalist even more indispensable.” — Casey Woo“Special Forces in business are the cross-functional scalers—the people who get dropped in and get it done.” — Casey Woo“Valuations aren't free. Be careful what you raise at, because expectations get baked into every round.” — Casey Woo“If you give someone 15 things to do, that's a lot. Do they need to do all 15? Prioritize ruthlessly.” — Casey WooSaaS Leadership LessonsEmbrace Generalism: In the early stage, leadership isn't about titles—learn to thrive by solving whatever needs attention, from product to operations.Ruthless Prioritization: Success comes from choosing the right battles. Cut down initiatives to what truly moves the needle.Build and Rely on Community: Leverage peer networks like Operators Guild for continuous learning, sharing, and staying ahead of rapid changes (especially with AI).Adapt Your Communication: Learn to “Google Translate” your messaging for different internal stakeholders—speak to engineers, marketers, and founders in their language.Invest in Scalable Systems Early: Upgrade infrastructure in anticipation of growth, not after; it's easier and more cost-effective to implement before complexity grows.Balance Aggression and Prudence: Being aggressive can win markets, but unchecked overextension leads to down rounds and organizational pain. Stay grounded in business fundamentals.Guest Resourcescasey.woo@gmail.comhttps://www.operators-guild.com/https://www.linkedin.com/in/caseywooEpisode SponsorThe Captain's KeysSmall Fish, Big Pond –

This episode was recorded live at SaaStock Europe 2025. Alex Theuma sits down with Mariam Hakobyan, CEO and Co-founder of Softr, to explore the evolution of app building in the AI era. Mariam explains why Softr is focusing on AI-powered no-code and why the companies that focus on solving real, hard problems will define the next generation of SaaS. Alex and Mariam discuss how Softr's journey to over 1 million non-technical builders, the debate around vibe-coded apps, how AI is transforming no-code, and what it really takes to build a product that lasts. - The difference between vibe code and no-code platforms - How AI and no-code together are changing how teams build software - Softr's organic growth story: 1M builders, zero sales team - Why solving fundamental problems still wins - The hardest challenge for SaaS founders today: distribution Guest links: LinkedIn - https://www.linkedin.com/in/mariamhakobyan/ Website - https://www.softr.io/       Check out the other ways SaaStock is helping SaaS founders move their business forward: 

In this essential episode, we sit down with Florin Simovici, CEO of TrafficManager and author of the industry's most comprehensive guide to building and managing affiliate programs. With 15 years of experience across multiple verticals—from iGaming to e-commerce—Florin shares the hard-won lessons that separate scaling programs from struggling ones.Florin pulls back the curtain on what actually drives sustainable growth, revealing why most networks fail before they even begin and how the industry's smartest operators are positioning themselves for the seismic shifts ahead. Whether you're managing your first program or your fiftieth, this episode will challenge your assumptions and equip you with actionable strategies to thrive in an increasingly competitive market.Talking points include: Why 80% of your revenue comes from just 20% of your affiliates—and how to structure your team accordinglyThe critical onboarding mistakes that doom new networks from day oneHow AI is fundamentally reshaping affiliate marketing (and why you need to start preparing now)Listen to find out more about: How to identify and protect the core affiliates who drive your network's growthThe automation tools that free affiliate managers from repetitive tasks so they can focus on relationshipsThe emerging "waves" in affiliate marketing—and how to position yourself to ride them rather than get swept awayKey segments of this podcast and where you can tune in to go direct: [00:52] Background on TrafficManager and Florin's journey from affiliate to network owner to SaaS provider[02:00] The story behind writing a 519-page book on affiliate program management (without AI assistance)[30:52] Final advice for affiliates: Give up the ego and communicate your needsWant to dive deeper into Florin's proven strategies? His comprehensive guide covers everything from post-back integration to fraud prevention to affiliate relationship management. Purchase How to Build and Manage an Affiliate Program or Network here.Would you like to talk about sponsoring our podcast, or gaining a brand mention? Take a look here.Send me a text with your questions

Welcome to The SaaS CFO Podcast! In this episode, host Ben Murray sits down with Ali Hussain, CEO and co-founder of Tabs, for an insightful conversation about the evolving landscape of finance technology. Ali shares his journey as an entrepreneur and operator, discusses the genesis and growth of Tabs, and dives deep into the world of revenue automation for B2B companies. Tune in as Ali explains how Tabs leverages AI and automation to streamline everything from order-to-cash and revenue recognition to forecasting and metrics reporting. You'll hear about the company's impressive growth since its founding in 2023, the state of AI adoption among CFOs and finance teams, and Ali's perspective on the dynamic ERP space. Ben and Ali also talk shop about fundraising milestones, go-to-market strategies, and key financial metrics for SaaS companies scaling from Series A to Series B. Whether you're interested in the future of AI-driven finance operations, the rise of best-of-breed finance tech stacks, or practical insights on team building and product innovation, this episode is packed with actionable advice for finance leaders and SaaS founders alike. Show Notes: 00:00 AI-Driven Finance Automation Platform 04:36 B2B Growth Focused on Sales 08:13 CFOs Embracing AI Adoption Shift 12:18 "Modern ERP Collaboration Overlegacy" 15:23 "Sales-Finance Integration via AI" 19:30 Finance Expansion and Accountant Channels 21:58 "ERP Market Ripe for Disruption" 25:53 "AI Business Fundamentals & Metrics" 27:45 Automation, Margins, and Customer Focus 31:48 Cash Forecasting Insights for CEOs 34:20 "Finance Innovation & Future Outlook" 37:23 "Making Systems Transparent" Links: SaaS Fundraising Stories: https://www.thesaasnews.com/news/tabs-raises-7-million-in-seed-round https://www.thesaasnews.com/news/tabs-secures-25-million-in-series-a-funding https://www.thesaasnews.com/news/tabs-raises-55-million-in-series-b Ali Hussain's LinkedIn: https://www.linkedin.com/in/ali-hussain786/ Tabs' LinkedIn: https://www.linkedin.com/company/teamtabs/ Tabs' Website: https://tabs.inc/ To learn more about Ben check out the links below: Subscribe to Ben's daily metrics newsletter: https://saasmetricsschool.beehiiv.com/subscribe Subscribe to Ben's SaaS newsletter: https://mailchi.mp/df1db6bf8bca/the-saas-cfo-sign-up-landing-page SaaS Metrics courses here: https://www.thesaasacademy.com/ Join Ben's SaaS community here: https://www.thesaasacademy.com/offers/ivNjwYDx/checkout Follow Ben on LinkedIn: https://www.linkedin.com/in/benrmurray

On today's episode, we're talking with Rajitha Chaparala, VP of Product at Procore, a construction management solution and one of the most successful examples of vertical SaaS out there today. In this episode, we discuss: How Rajitha and her team are using LLMs to streamline complex processes like requests for information (RFIs), project revisions, and construction site walkthroughs Why building trust and showing real, immediate value were key to getting AI buy-in from construction professionals, historically hesitant to adopt new tech Why Rajitha believes this is construction's moment for AI, and how the shift from skepticism to curiosity happened almost overnight Links LinkedIn: https://www.linkedin.com/in/rajithachaparala/ Procore: www.procore.com Chapters 00:00 Introduction 00:48: The complexity of construction and technology adoption 02:00: AI streamlining Requests for Information (RFIs) in construction 04:00: Why LLMs are ideal for construction's unstructured data 06:00: Building trust for AI adoption 08:00: The future of construction thanks to AI adoption Follow LaunchPod on YouTube We have a new YouTube page (https://www.youtube.com/@LaunchPodPodcast)! Watch full episodes of our interviews with PM leaders and subscribe! What does LogRocket do? LogRocket's Galileo AI watches user sessions for you and surfaces the technical and usability issues holding back your web and mobile apps. Understand where your users are struggling by trying it for free at LogRocket.com (https://logrocket.com/signup/?pdr). Special Guest: Rajitha Chaparala.

The Four T's of Startup Investing Hello, this is Hall T. Martin with the Startup Funding Espresso -- your daily shot of startup funding and investing. There are many ways to evaluate a startup. For investors funding SaaS startups, here are the four T's to consider: Team.   Does the team have the skills to build the proposed startup? Are they in place, working on the business now? Have they proven themselves yet? Timing. Is now the right time for the startup? Is the market ready for this idea? Traction Does the startup have revenue growth? Will the growth continue? Technology. Does the startup have the right technology for the market? Can the technology scale? Does it provide a moat for the business? Use the four T's to determine if the startup is ready for an investment.   Thank you for joining us for the Startup Funding Espresso where we help startups and investors connect for funding. Let's go startup something today. _________________________________________________________ For more episodes from Investor Connect, please visit the site at:   Check out our other podcasts here:   For Investors check out:   For Startups check out:   For eGuides check out:   For upcoming Events, check out    For Feedback please contact info@tencapital.group    Please , share, and leave a review. Music courtesy of .

Our analysts Brian Nowak, Keith Weiss and Matt Bombassei break down the most important tech insights from Morgan Stanley's Spark Private Company Conference and industry shifts that will likely shape 2026 and beyond. Read more insights from Morgan Stanley.----- Transcript ----- Brian Nowak: Welcome to Thoughts on the Market. I'm Brian Nowak, Morgan Stanley's Head of U.S. Internet Research. I'm joined today by Keith Weiss, Head of U.S. Software Research and Matt Bombassei from my team.Today we're going to talk about private companies and technology – and how they're showing us the direction of travel for disruptive technologies and emerging investment opportunities.It's Wednesday, October 22nd at 10am in New York.Keith and Matt, we just returned from Morgan Stanley's Spark Private Company Conference last week in Los Angeles. It had over 85 private tech companies, 150 plus investor firms. There were a lot of themes that were discussed across the entire tech space impacting a lot of different sectors, including energy, healthcare, financial services, and cybersecurity.Keith, what were some of the biggest takeaways you took away from Spark this year?Keith Weiss: I'd say just to start off with, the Spark Conference is one of my favorite conferences of the year. It's a more intimate conference where you really get to spend time with both the private company executives and founders, as well as investors from the VC community and public company investors. And the conversations are more broad ranging; they're more about the thematics in the industry. They're more long term in nature.So, it's not just a conversation about what's next quarter going to look like, or what data points are you drumming up. You're having these thoughtful conversations about what's going on in the industry and how that's going to impact business models, how it's going to impact innovation cycles, how it's going to impact pricing models, within these companies. So, it tends to be a very interesting conference for me to attend.So, for me, some of the key takeaways. Typically, when we're in these innovation cycles, it feels like everybody's rowing in the same direction. We all understand where the technology's heading, we're all understanding how it's going to be delivered, and it's a race to get there. And you're having a conversation about who's doing best in that race, who's best positioned, who's got a better motor in their race car, if you will.So, to me, one of the big takeaways was we don't have that agreement today, right? There's different players that are looking at this market evolution differently. On one side of the equation, the application vendors – and a lot of this debate is in SaaS based applications. They see SaaS based applications having a very big role in taking these models that are inherently in-determinative and making them to be more determinative and useful within an enterprise context.Bringing them the data that they need to get the job done and the right data; bringing them the context of the business process being solved; bringing the governance that's necessary to use in an enterprise environment. But most importantly, to make it effective and efficient for the large enterprise.On the other side of the equation, you have venture capital investors and more early-stage investors who are looking at this as a huge phase shift, right? This is going to fundamentally change how we build software, how we utilize software, and they worry about a deprecation of that SaaS application layer. They think the model itself is going to start to encompass, it's going to start to subsume a lot more of that application functionality, a lot more of that analytics. And they see a lot more disruption going forward.So that debate within the marketplace, that's something that's interesting to me. It's something that we don't typically see in these innovation cycles. So that's takeaway number one.Takeaway number two, we're still really early days, and that's a little bit implied in in the first statement; I definitely hear a lot of it when I talk to the end customer. When I talk to CIOs. This wasn't necessarily at Spark, but earlier in the week, I was at a CIO conference, there was 150 CIOs in the room. One of the gentlemen on stage asked a question. ‘Who in the room has a good understanding of what we're talking about when we mean Agentic AI, when we mean agentic computing within our enterprise.' Of the 150 CIOs, four raised their hands. Still very early days in understanding how this is going to evolve, how we're going to actually deliver these capabilities into the enterprise.And the last takeaway I would say is more excitement about the federal government becoming a better customer for software companies overall. People are more interested in new avenues into that federal government. There's been some very successful companies that have opened the door to getting into these federal government contracts without going through the primes, without doing the typical federal government procurement cycles.And that's very interesting to the startup community, which tends to move faster, which tends to drive on innovation versus relationship building; versus being in an existing kind of incumbent prime. So, I thought that opening was – it was pretty interesting as well.Brian Nowak: it sounds like it's still very early, there are a lot of different points of view and no real consensus as to where technologies could go next. However, one theme with an enterprise software – [it] does seem like cybersecurity has a little more of a unified view.So maybe walk us through what you learned from a cybersecurity perspective and what should we be focused on there?Keith Weiss: Yeah, absolutely. If there is a consensus, the consensus is that generative AI and these innovations and the fast pace of innovation is going to be a positive for cybersecurity spending, right? The reason being, there's three main factors that are driving that overall spending.One is expansion of surface area, right? Cybersecurity in one dimension, you can think of how much is there to be protected, right? And if we think about the major themes that we're talking about, we're going to be developing a lot more software, right? The code generation tools are improving software developer productivity. You have an expanding capability of what you can actually automate.We'll be building a lot more software. That software needs to be protected, right? We have new entities that are going to be operating inside of enterprises, and that's the agents. So, CIOs are thinking about this future state where you have tens, thousands, maybe hundreds of thousands of agents operating in the environment, doing work on behalf of end users, but having permissions and having ability to execute business processes. How do we secure that side of the equation? We're talking about outside of just the four walls of the large enterprise, going into more operational technologies, being able to automate more of that work. That needs to be secured as well.So, an expanding surface area is definitely good for the cybersecurity budget. You can almost think of cybersecurity as a tax on that surface area. We generally think about it; somewhere between 4 and 6 percent of IT spend is going to be spent on overall security. So, that's one big driver.The second big driver is the elevated threat environment. So, while we're excited to get our hands on these extended capabilities of generative AI, the bad guys are already there, right? They're taking advantage of this. The sophistication, the volume and the velocity of these attacks is all increasing. That makes a harder job for the existing infrastructure to keep up, and it's going to likely necessitate more spending on cybersecurity to tackle these newer challenges; the newer dynamism within the cybersecurity threat appropriately. So, you're going to have to use generative AI to counter the generative AI.And then the last component of it; the last driver would be the regulatory environment. Regulatory tends to have some cybersecurity angles. If we think about it here, we're seeing it in terms of data governance is probably the big one. Where does this data go when it goes into the model? Are we putting the right controls around it? Do we have the right governance on it? So that's a big area of concern.A lot of complaining going on at the conference about the lack of consistency in that regulatory environment. All these different initiatives coming up from the state – really creates a challenging environment to navigate. But that's all good-ness for cybersecurity vendors that can help you get into compliance with these new regulations that are coming up. So overall, a lot of positivity around cybersecurity spending and startups definitely look to take advantage of that.Brian Nowak: Matt, so Keith says there's lack of consensus and boats being rode in every direction on what should be adopted first. And only 3 percent of CIOs know what agentic AI means. What did you learn about early signal on adoption? And some of the barriers to adoption? And hurdles that companies are talking about that they need to overcome to really adopt some of these new tools?Matt Bombassei: Yeah. Well, to Keith's point, it is really early, right? And that was a consistent theme that we heard from our companies at the conference. They are seeing early signs of cost efficiency, making employees more productive as opposed to maybe broad scale layoffs. But it's the deployment of these model technologies into specific sub-verticals – so accounting, legal engineering – where that adoption is driving greater efficiency within the organization.These companies are also adopting models that are smaller and a bit more fine tuned to their specific work product. And so that comes at a lower cost. We heard companies talking about costs at 1/50 of the cost of the broader foundational models when they're deploying it within the organization. And so, cost efficiency is something that we're seeing.At the same time, to speak to how early it is, one of the biggest hurdles here is change management and actually adoption. Getting people to use these products, getting them to learn the new technologies, that is a big hurdle. You know, you can lead a horse to water, you can't make it drink, right? And so, getting people to actually deploy these technologies is something that organizations are thinking through. How do we approach [it]?Brian Nowak: And you make an autonomous car drive? I know you've been doing a lot of work on autonomous driving more broadly. There were some autonomous driving and autonomous driving technology companies at Spark. What were your takeaways on autonomous driving from last week?Matt Bombassei: Yeah, well, not only can you make an autonomous car drive, you can make a truck drive and a bunch of other physical equipment. I think that was one of the takeaways here was that these neural nets that are powering autonomous vehicles are actually becoming much more generalizable. The integration of the transformer architecture into these neural nets is allowing them to take the context from one sub-vertical and deploy it in another vertical.So, we heard that 80 to 90 percent of the software, the underlying neural net, is applicable across these verticals. So, think applicable from autonomous ride sharing to autonomous trucking, right? What that means from our point of view is that it's important to get the scale of total miles driven – to establish that kind of safety hurdle if you're these companies.But also, don't necessarily think of these companies as defined by the vertical that they're operating in. If these models truly are generalizable, a company that's successful and scaled and autonomous ride hailing can switch or navigate verticals to also become successful potentially in trucking and other industries as well. So, the generalization of these models is particularly interesting for scale, and long-term market position for these companies.Brian Nowak: It's fascinating. Well, from consumer and enterprise adoption, the future of agentic computing and autonomous driving, there will be a lot more themes we all have to stay on top of. Keith, Matt, thanks so much for taking the time today.Keith Weiss: Great speaking with you Brian.Matt Bombassei: Thanks for having us.Brian Nowak: And thanks for listening. If you enjoy Thoughts on the Market, please leave us a review wherever you listen and share the podcast with a friend or colleague today.

In this comprehensive session, SaaStr CEO and Founder Jason Lemkin dives into the latest trends and developments in AI, particularly in the go-to-market (GTM) sector. The session outlines how innovative AI tools are transforming businesses, from AI SDRs and BDRs to forward-deployed engineers. Leaders in the industry are pushing the boundaries, showing higher growth rates and superior marketing efficiency. We also discuss the importance of hands-on deployment and training of AI tools to achieve success, and analyze the current and future impact of AI on B2B companies. Tune in for detailed insights and learn how to stay ahead in the rapidly evolving world of AI. --------------------- 

This episode is Sponsored in part by Salesforce:

 Connect data, automate busywork and empower teams like nobody's business with the one platform that grows with you, every step of the way. Learn how Salesforce works for Startups at salesforce.com/smb.   --------------------- This episode is Sponsored in part by Intercom:
 Fin is the #1 AI Agent for resolving complex queries like refunds, transaction disputes, and technical troubleshooting—all with speed and reliability. See how Fin can deliver the highest resolution rates and highest-quality customer experience at fin.ai/saastr.  --------------------- If you're serious about B2B and AI, you need to be in London this December.   SaaStr AI London is bringing together more than 2,000 leaders and founders for two days of practical advice on scaling into the new year.    We'll have speakers flying in from OpenAI, Wiz, Clay, Intercom, and all your favorite SaaS companies, including yours truly with Harry Stebbings for a live 20VC podcast. It'll be fun, and it's all in the heart of London.    Don't miss out: get your tickets with my exclusive discount by going to podcast.saastrlondon.com   ---------------------   Hey everybody, the biggest B2B + AI event of the year will be back - SaaStr AI in the SF Bay Area, aka the SaaStr Annual, will be back in May 2026.    With 68% VP-level and above, 36% CEOs and founders and a growing 25% AI-first professional, this is the very best of the best S-tier attendees and decision makers that come to SaaStr each year.     But here's the reality, folks: the longer you wait, the higher ticket prices can get. Early bird tickets are available now, but once they're gone, you'll pay hundreds more so don't wait.    Lock in your spot today by going to podcast.saastrannual.com to get my exclusive discount SaaStr AI SF 2026. We'll see you there.

In this episode of The Product Experience, Lily and Randy speak with Dan Dalton (Director of Product Management at Sage) about the current state of product management, and how the role must evolve in today's climate.Chapters0:00 Introduction: product management at a crossroads1:00 Dan Dalton's background and path into product3:00 The evolution of product management: 2010 to today8:15 Framework‐fundamentalism, the broken ladder & career expectations13:45 Why many product careers are being set up to fail19:20 Responding to disruption: returning to basics, focusing on impact24:40 The role of soft skills and mindset in product leadership28:55 How Dan's team operates: fast prototyping, design system, code assets31:10 Hiring and developing product talent: soft skills over tick‐boxes35:30 AI, hype and bubbles: what product leaders need to keep in mind40:15 The mental flywheel: pragmatism, curiosity, resilience, detachment45:00 Wrap up & closing remarksFeatured Links: Follow Dan on LinkedIn | Sage | 'Why is everyone hating on Product Managers?' feature by Peter YangWe're taking Community Questions for The Product Experience podcast.Got a burning product question for Lily, Randy, or an upcoming guest? Submit it here. Our HostsLily Smith enjoys working as a consultant product manager with early-stage and growing startups and as a mentor to other product managers. She's currently Chief Product Officer at BBC Maestro, and has spent 13 years in the tech industry working with startups in the SaaS and mobile space. She's worked on a diverse range of products – leading the product teams through discovery, prototyping, testing and delivery. Lily also founded ProductTank Bristol and runs ProductCamp in Bristol and Bath. Randy Silver is a Leadership & Product Coach and Consultant. He gets teams unstuck, helping you to supercharge your results. Randy's held interim CPO and Leadership roles at scale-ups and SMEs, advised start-ups, and been Head of Product at HSBC and Sainsbury's. He participated in Silicon Valley Product Group's Coaching the Coaches forum, and speaks frequently at conferences and events. You can join one of communities he runs for CPOs (CPO Circles), Product Managers (Product In the {A}ether) and Product Coaches. He's the author of What Do We Do Now? A...

In this episode of In-Ear Insights, the Trust Insights podcast, Katie and Chris discuss the stark reality of the future of work presented at the Marketing AI Conference, MAICON 2025. You’ll learn which roles artificial intelligence will consume fastest and why average employees face the highest risk of replacement. You’ll master the critical thinking and contextual skills you must develop now to transform yourself into an indispensable expert. You’ll understand how expanding your intellectual curiosity outside your specific job will unlock creative problem solving essential for survival. You’ll discover the massive global AI blind spot that US companies ignore and how this shifting landscape affects your career trajectory. Watch now to prepare your career for the age of accelerated automation! Watch the video here: Can’t see anything? Watch it on YouTube here. Listen to the audio here: https://traffic.libsyn.com/inearinsights/tipodcast-maicon-2025-generative-ai-for-marketers.mp3 Download the MP3 audio here. Need help with your company’s data and analytics? Let us know! Join our free Slack group for marketers interested in analytics! [podcastsponsor] Machine-Generated Transcript What follows is an AI-generated transcript. The transcript may contain errors and is not a substitute for listening to the episode. Christopher S. Penn – 00:00 In this week’s In Ear Insights, we are at the Marketing AI Conference, Macon 2025 in Cleveland with 1,500 of our best friends. This morning, the CEO of SmartRx, formerly the Marketing AI Institute, Paul Ritzer, was talking about the future of work. Now, before I go down a long rabbit hole, Dave, what was your immediate impressions, takeaways from Paul’s talk? Katie Robbert – 00:23 Paul always brings this really interesting perspective because he’s very much a futurist, much like yourself, but he’s a futurist in a different way. Whereas you’re on the future of the technology, he’s focused on the future of the business and the people. And so his perspective was really, “AI is going to take your job.” If we had to underscore it, that was the bottom line: AI is going to take your job. However, how can you be smarter about it? How can you work with it instead of working against it? Obviously, he didn’t have time to get into every single individual solution. Katie Robbert – 01:01 The goal of his keynote talk was to get us all thinking, “Oh, so if AI is going to take my job, how do I work with AI versus just continuing to fight against it so that I’m never going to get ahead?” I thought that was a really interesting way to introduce the conference as a whole, where every individual session is going to get into their soldiers. Christopher S. Penn – 01:24 The chart that really surprised me was one of those, “Oh, he actually said the quiet part out loud.” He showed the SaaS business chart: SaaS software is $500 billion of economic value. Of course, AI companies are going, “Yeah, we want that money. We want to take all that money.” But then he brought up the labor chart, which is $12 trillion of money, and says, “This is what the AI companies really want. They want to take all $12 trillion and keep it for themselves and fire everybody,” which is the quiet part out loud. Even if they take 20% of that, that’s still, obviously, what is it, $2 trillion, give or take? When we think about what that means for human beings, that’s basically saying, “I want 20% of the workforce to be unemployed.” Katie Robbert – 02:15 And he wasn’t shy about saying that. Unfortunately, that is the message that a lot of the larger companies are promoting right now. So the question then becomes, what does that mean for that 20%? They have to pivot. They have to learn new skills, or—the big thing, and you and I have talked about this quite a bit this year—is you really have to tap into that critical thinking. That was one of the messages that Paul was sharing in the keynote: go to school, get your liberal art degree, and focus on critical thinking. AI is going to do the rest of it. Katie Robbert – 02:46 So when we look at the roles that are up for grabs, a lot of it was in management, a lot of it was in customer service, a lot of it was in analytics—things that already have a lot of automation around them. So why not naturally let agentic AI take over, and then you don’t need human intervention at all? So then, where does that leave the human? Katie Robbert – 03:08 We’re the ones who have to think what’s next. One of the things that Paul did share was that the screenwriter for all of the Scorsese films was saying that ChatGPT gave me better ideas. We don’t know what those exact prompts looked like. We don’t know how much context was given. We don’t know how much background information. But if that was sue and I, his name was Paul. Paul Schrader. Yes, I forgot it for a second. If Paul Schrader can look at Paul Schrader’s work, then he’s the expert. That’s the thing that I think needed to also be underscored: Paul Schrader is the expert in Paul Schrader. Paul Schrader is the expert in screenwriting those particular genre films. Nobody else can do that. Katie Robbert – 03:52 So Paul Schrader is the only one who could have created the contextual information for those large language models. He still has value, and he’s the one who’s going to take the ideas given by the large language models and turn them into something. The large language model might give him an idea, but he needs to be the one to flush it out, start to finish, because he’s the one who understands nuance. He’s the one who understands, “If I give this to a Leonardo DiCaprio, what is he gonna do with the role? How is he gonna think about it?” Because then you’re starting to get into all of the different complexities where no one individual ever truly works alone. You have a lot of other humans. Katie Robbert – 04:29 I think that’s the part that we haven’t quite gotten to, is sure, generative AI can give you a lot of information, give you a lot of ideas, and do a lot of the work. But when you start incorporating more humans into a team, the nuance—it’s very discreet. It’s very hard for an AI to pick up. You still need humans to do those pieces. Christopher S. Penn – 04:49 When you take a look, though, at something like the Tilly Norwood thing from a couple weeks ago, even there, it’s saying, “Let’s take fewer humans in there,” where you have this completely machine generated actor avatar, I guess. It was very clearly made to replace a human there because they’re saying, “This is great. They don’t have to pay union wages. The actor never calls in sick. The actor never takes a vacation. The actor’s not going to be partying at a club unless someone makes it do that.” When we look at that big chart of, “Here’s all the jobs that are up for grabs,” the $12 trillion of economic value, when you look at that, how at risk do you think your average person is? Katie Robbert – 05:39 The key word in there is average. An average person is at risk. Because if an average person isn’t thinking about things creatively, or if they’re just saying, “Oh, this is what I have to do today, let me just do it. Let me just do the bare minimum, get through it.” Yes, that person is at risk. But someone who looks at a problem or a task that’s in front of them and thinks, “What are the five different ways that I could approach this? Let me sit down for a second, really plan it out. What am I not thinking of? What have I not asked? What’s the information I don’t have in front of me? Let me go find that”—that person is less at risk because they are able to think beyond what’s right in front of them. Katie Robbert – 06:17 I think that is going to be harder to replace. So, for example, I do operations, I’m a CEO. I set the vision. You could theoretically give that to an AI to do. I could create CEO Katie GPT. And GPT Katie could set the vision, based on everything I know: “This is the direction that your company should go in.” What that generative AI doesn’t know is what I know—what we’ve tried, what we haven’t tried. I could give it all that information and it could still say, “Okay, it sounds like you’ve tried this.” But then it doesn’t necessarily know conversations that I’ve had with you offline about certain things. Could I give it all that information? Sure. But then now I’m introducing another person into the conversation. And as predictable as humans are, we’re unpredictable. Katie Robbert – 07:13 So you might say, “Katie would absolutely say this to something.” And I’m going to look at it and go, “I would absolutely not say that.” We’ve actually run into that with our account manager where she’s like, “Well, this is how I thought you would respond. This is how I thought you would post something on social media.” I’m like, “Absolutely not. That doesn’t sound like me at all.” She’s like, “But that’s what the GPT gave me that is supposed to sound like you.” I’m like, “Well, it’s wrong because I’m allowed to change my mind. I’m a human.” And GPTs or large language models don’t have that luxury of just changing its mind and just kind of winging it, if that makes sense. Christopher S. Penn – 07:44 It does. What percentage, based on your experience in managing people, what percentage of people are that exceptional person versus the average or the below average? Katie Robbert – 07:55 A small percentage, unfortunately, because it comes down to two things: consistency and motivation. First, you have to be consistent and do your thing well all the time. In order to be consistent, you have to be motivated. So it’s not enough to just show up, check the boxes, and then go about your day, because anybody can do that; AI can do that. You have to be motivated to want to learn more, to want to do more. So the people who are demonstrating a hunger for reaching—what do they call it?—punching above their weight, reaching beyond what they have, those are the people who are going to be less vulnerable because they’re willing to learn, they’re willing to adapt, they’re willing to be agile. Christopher S. Penn – 08:37 For a while now we’ve been saying that either you’re going to manage the machines or the machines are going to manage you. And now of course we are at the point the machine is just going to manage the machines and you are replaced. Given so few people have that intrinsic motivation, is that teachable or is that something that someone has to have—that inner desire to want to better, regardless of training? Katie Robbert – 09:08 “Teachable” I think is the wrong word. It’s more something that you have to tap into with someone. This is something that you’ve talked about before: what motivates people—money, security, blah, blah, whatever, all those different things. You can say, “I’m going to motivate you by dangling money in front of you,” or, “I’m going to motivate you by dangling time off in front of you.” I’m not teaching you anything. I’m just tapping into who you are as a person by understanding your motives, what motivates you, what gets you excited. I feel fairly confident in saying that your motivations, Chris, are to be the smartest person in the room or to have the most knowledge about your given industry so that you can be considered an expert. Katie Robbert – 09:58 That’s something that you’re going to continue to strive for. That’s what motivates you, in addition to financial security, in addition to securing a good home life for your family. That’s what motivates you. So as I, the other human in the company, think about it, I’m like, “What is going to motivate Chris to get his stuff done?” Okay, can I position it as, “If you do this, you’re going to be the smartest person in the room,” or, “If you do this, you’re going to have financial security?” And you’re like, “Oh, great, those are things I care about. Great, now I’m motivated to do them.” Versus if I say, “If you do this, I’ll get off your back.” That’s not enough motivation because you’re like, “Well, you’re going to be on my back anyway.” Katie Robbert – 10:38 Why bother with this thing when it’s just going to be the next thing the next day? So it’s not a matter of teaching people to be motivated. It’s a matter of, if you’re the person who has to do the motivating, finding what motivates someone. And that’s a very human thing. That’s as old as humans are—finding what people are passionate about, what gets them out of bed in the morning. Christopher S. Penn – 11:05 Which is a complex interplay. If you think about the last five years, we’ve had a lot of discussions about things like quiet quitting, where people show up to work to do the bare minimum, where workers have recognized companies don’t have their back at all. Katie Robbert – 11:19 We have culture and pizza on Fridays. Christopher S. Penn – 11:23 At 5:00 PM when everyone wants to just— Katie Robbert – 11:25 Go home and float in that day. Christopher S. Penn – 11:26 Exactly. Given that, does that accelerate the replacement of those workers? Katie Robbert – 11:37 When we talk about change management, we talk about down to the individual level. You have to be explaining to each and every individual, “What’s in it for me?” If you’re working for a company that’s like, “Well, what’s in it for you is free pizza Fridays and funny hack days and Hawaiian shirt day,” that doesn’t put money in their bank account. That doesn’t put a roof over their head; that doesn’t put food on their table, maybe unless they bring home one of the free pizzas. But that’s once a week. What about the other six days a week? That’s not enough motivation for someone to stay. I’ve been in that position, you’ve been in that position. My first thought is, “Well, maybe stop spending money on free pizza and pay me more.” Katie Robbert – 12:19 That would motivate me, that would make me feel valued. If you said, “You can go buy your own pizza because now you can afford it,” that’s a motivator. But companies aren’t thinking about it that way. They’re looking at employees as just expendable cogs that they can rip and replace. Twenty other people would be happy to do the job that you’re unhappy doing. That’s true, but that’s because companies are setting up people to fail, not to succeed. Christopher S. Penn – 12:46 And now with machinery, you’re saying, “Okay, since there’s a failing cog anyway, why don’t we replace it with an actual cog instead?” So where does this lead for companies? Particularly in capitalist markets where there is no strong social welfare net? Yeah, obviously if you go to France, you can work a 30-hour week and be just fine. But we don’t live in France. France, if you’re hiring, we’re available. Where does it lead? Because I can definitely see one road where this leads to basically where France ended up in 1789, which is the Guillotines. These people trot out the Guillotines because after a certain point, income inequality leads to that stuff. Where does this lead for the market as you see it now? Katie Robbert – 13:39 Unfortunately, nowhere good. We have seen time and time again, as much as we want to see the best in people, we’re seeing the worst in people today, as of this podcast recording—not at Macon. These are some of the best people. But when you step outside of this bubble, you’re seeing the worst in people. They’re motivated by money and money only, money and power. They don’t care about humanity as a whole. They’re like, “I don’t care if you’re poor, get poorer, I’m getting richer.” I feel like, unfortunately, that is the message that is being sent. “If you can make a dollar, go ahead and make a dollar. Don’t worry about what that does to anybody else. Go ahead and be in it for yourself.” Katie Robbert – 14:24 And that’s unfortunately where I see a lot of companies going: we’re just in it to make money. We no longer care about the welfare of our people. I’ve talked on previous shows, on previous podcasts. My husband works for a grocery store that was bought out by Amazon a few years ago, and he’s seeing the effects of that daily. Amazon bought this grocery chain and said basically, “We don’t actually care about the people. We’re going to automate things. We’re going to introduce artificial intelligence.” They’ve gotten rid of HR. He still has to bring home a physical check because there is no one to give him paperwork to do direct deposit. Christopher S. Penn – 15:06 He’s been—ironic given the company. Katie Robbert – 15:08 And he’s been at the company for 25 years. But when they change things over, if he has an assurance question, there’s no one to go to. They probably have chatbots and an email distribution list that goes to somebody in an inbox that never. It’s so sad to see the decline based on where the company started and what the mission originally was of that company to where it is today. His suspicion—and this is not confirmed—his suspicion is that they are gearing up to sell this business, this grocery chain, to another grocery chain for profit and get rid of it. Flipping it, basically. Right now, they’re using it as a distribution center, which is not what it’s meant to be. Katie Robbert – 15:56 And now they’re going to flip it to another grocery store chain because they’ve gotten what they needed from it. Who cares about the people? Who cares about the fact that he as an individual has to work 50 hours a week because there’s nobody else? They’ve flattened the company. They’re like, “No, based on our AI scheduler, there’s plenty of people to cover all of these hours seven days a week.” And he’s like, “Yeah, you have me on there for seven of the seven days.” Because the AI is not thinking about work-life balance. It’s like, “Well, this individual is available at these times, so therefore he must be working here.” And it’s not going to do good things for people in services industries, for people in roles that cannot be automated. Katie Robbert – 16:41 So we talk about customer service—that’s picking up the phone, logging a plate—that can be automated. Walking into a brick and mortar, there are absolutely parts of it that can be automated, specifically the end purchase transaction. But the actual ordering and picking of things and preparing it—sure, you could argue that eventually robots could be doing that, but as of today, that’s all humans. And those humans are being treated so poorly. Christopher S. Penn – 17:08 So where does that end for this particular company or any large enterprise? Katie Robbert – 17:14 They really have—they have to make decisions: do they want to put the money first or the people first? And you already know what the answer to that is. That’s really what it comes down to. When it ends, it doesn’t end. Even if they get sold, they’re always going to put the money first. If they have massive turnover, what do they care? They’re going to find somebody else who’s willing to do that work. Think about all of those people who were just laid off from the white-collar jobs who are like, “Oh crap, I still have a mortgage I have to pay, I still have a family I have to feed. Let me go get one of those jobs that nobody else is now willing to do.” Katie Robbert – 17:51 I feel like that’s the way that the future of work for those people who are left behind is going to turn over. Katie Robbert – 17:59 There’s a lot of people who are happy doing those jobs. I love doing more of what’s considered the blue-collar job—doing things manually, getting their hands in it, versus automating everything. But that’s me personally; that’s what motivates me. That I would imagine is very unappealing to you. Not that for almost. But if cooking’s off the table, there’s a lot of other things that you could do, but would you do them? Katie Robbert – 18:29 So when we talk about what’s going to happen to those people who are cut and left behind, those are the choices they’re going to have to make because there’s not going to be more tech jobs for them to choose from. And if you are someone in your career who has only ever focused on one thing, you’re definitely in big trouble. Christopher S. Penn – 18:47 Yeah, I have a friend who’s a lawyer at a nonprofit, and they’re like, “Yeah, we have no funding anymore, so.” But I can’t pick up and go to England because I can’t practice law there. Katie Robbert – 18:59 Right. I think about people. Forever, social media was it. You focus on social media and you are set. Anybody will hire you because they’re trying to learn how to master social media. Guess where there’s no jobs anymore? Social media. So if all you know is social media and you haven’t diversified your skill set, you’re cooked, you’re done. You’re going to have to start at ground zero entry level. If there’s that. And that’s the thing that’s going to be tough because entry-level jobs—exactly. Christopher S. Penn – 19:34 We saw, what was it, the National Labor Relations Board publish something a couple months ago saying that the unemployment rate for new college graduates is something 60% higher than the rest of the workforce because all the entry-level jobs have been consumed. Katie Robbert – 19:46 Right. I did a talk earlier this year at WPI—that’s Worcester Polytech in Massachusetts—through the Women in Data Science organization. We were answering questions basically like this about the future of work for AI. At a technical college, there are a lot of people who are studying engineering, there are a lot of people who are studying software development. That was one of the first questions: “I’m about to get my engineering degree, I’m about to get my software development degree. What am I supposed to do?” My response to that is, you still need to understand how the thing works. We were talking about this in our AI for Analytics workshop yesterday that we gave here at Macon. In order to do coding in generative AI effectively, you have to understand the software development life cycle. Katie Robbert – 20:39 There is still a need for the expertise. People are asking, “What do I do?” Focus on becoming an expert. Focus on really mastering the thing that you’re passionate about, the thing that you want to learn about. You’ll be the one teaching the AI, setting up the AI, consulting with the people who are setting up the AI. There’ll be plenty of practitioners who can push the buttons and set up agents, but they still need the experts to tell them what it’s supposed to do and what the output’s supposed to be. Christopher S. Penn – 21:06 Do you see—this is kind of a trick question—do you see the machines consuming that expertise? Katie Robbert – 21:15 Oh, sure. But this is where we go back to what we were talking about: the more people, the more group think—which I hate that term—but the more group think you introduce, the more nuanced it is. When you and I sit down, for example, when we actually have five minutes to sit down and talk about the future of our business, where we want to go or what we’re working on today, the amount of information we can iterate on because we know each other so well and almost don’t have to speak in complete sentences and just can sort of pick up what the other person is thinking. Or I can look at something you’re writing and say, “Hey, I had an idea about that.” We can do that as humans because we know each other so well. Katie Robbert – 21:58 I don’t think—and you’re going to tell me this is going to happen—unless we can actually plug or forge into our brains and download all of the things. That’s never going to happen. Even if we build Katie GPT and Chris GPT and have them talk to each other, they’re never going to brainstorm the way you and I brainstorm in real life. Especially if you give me a whiteboard. I’m good. I’m going to get so much done. Christopher S. Penn – 22:25 For people who are in their career right now, what do they do? You can tell somebody, “You need to be a good critical thinker, a creative thinker, a contextual thinker. You need to know where your data lives and things like that.” But the technology is advancing at such a fast rate. I talk about this in the workshops that we do—which, by the way, Trust Insights is offering workshops at your company, if we like one. But one of the things to talk about is, say, with the model’s acceleration in terms of growth, they’re growing faster than any technology ever has. They went from face rolling idiot in 2023 right to above PhD level in everything two years later. Christopher S. Penn – 23:13 So the people who, in their career, are looking at this, going, “It’s like a bad Stephen King movie where you see the thing coming across the horizon.” Katie Robbert – 23:22 There is no such thing as a bad Stephen King movie. Sometimes the book is better, but it’s still good. But yes, maybe *Creepshow*. What do you mean in terms of how do they prepare for the inevitable? Christopher S. Penn – 23:44 Prepare for the inevitable. Because to tell somebody, “Yeah, be a critical thinker, be a contextual thinker, be a creative thinker”—that’s good in the abstract. But then you’re like, “Well, my—yeah, my—and my boss says we’re doing a 10% headcount reduction this week.” Katie Robbert – 24:02 This is my personal way of approaching it: you can’t limit yourself to just go, “Okay, think about it. Okay, I’m thinking.” You actually have to educate yourself on a variety of different things. I am a voracious reader. I read all the time when I’m not working. In the past three weeks, I’ve read four books. And they’re not business books; they are fiction books and on a variety of things. But what that does is it keeps my brain active. It keeps my brain thinking. Then I give myself the space and time. When I walk my dog, I sort of process all of it. I think about it, and then I start thinking about, “What are we doing as our company today?” or, “What’s on the task list?” Katie Robbert – 24:50 Because I’ve expanded my personal horizons beyond what’s right in front of me, I can think about it from the perspective of other people, fictional or otherwise, “How would this person approach it?” or, “What would I do in that scenario?” Even as I’m reading these books, I start to think about myself. I’m like, “What would I do in that scenario? What would I do if I was finding myself on a road trip with a cannibal who, at the end of the road trip, was likely going to consume all of me, including my bones?” It was the last book I read, and it was definitely not what I thought I was signing up for. But you start to put yourself in those scenarios. Katie Robbert – 25:32 That’s what I personally think unlocks the critical thinking, because you’re not just stuck in, “Okay, I have a math problem. I have 1 + 1.” That’s where a lot of people think critical thinking starts and ends. They think, “Well, if I can solve that problem, I’m a critical thinker.” No, there’s only one way to solve that problem. That’s it. I personally would encourage people to expand their horizons, and this comes through having hobbies. You like to say that you work 24/7. That’s not true. You have hobbies, but they’re hobbies that help you be creative. They’re hobbies that help you connect with other people so that you can have those shared experiences, but also learn from people from different cultures, different backgrounds, different experiences. Katie Robbert – 26:18 That’s what’s going to help you be a stronger, fitable thinker, because you’re not just thinking about it from your perspective. Christopher S. Penn – 26:25 Switching gears, what was missing, what’s been missing, and what is absent from this show in the AI space? I have an answer, but I want to hear yours. Katie Robbert – 26:36 Oh, boy. Really putting me on the spot here. I know what is missing. I don’t know. I’m going to think about it, and I am going to get back to you. As we all know, I am not someone who can think on my feet as quickly as you can. So I will take time, I will process it, but I will come back to you. What do you think is missing? Christopher S. Penn – 27:07 One of the things that is a giant blind spot in the AI space right now is it is a very Western-centric view. All the companies say OpenAI and Anthropic and Google and Meta and stuff like that. Yet when you look at the leaderboards online of whose models are topping the charts—Cling Wan, Alibaba, Quinn, Deepseek—these are all Chinese-made models. If you look at the chip sets being used, the government of China itself just issued an edict: “No more Nvidia chips. We are going to use Huawei Ascend 920s now,” which are very good at what they do. And the Chinese models themselves, these companies are just giving them away to the world. Christopher S. Penn – 27:54 They’re not trying to lock you in like a ChatGPT is. The premise for them, for basically the rest of the world that is in America, is, “Hey, you could take American AI where you’re locked in and you’re gonna spend more and more money, or here’s a Chinese model for free and you can build your national infrastructure on the free stuff that we’re gonna give you.” I’ve seen none of that here. That is completely absent from any of the discussions about what other nations are doing with AI. The EU has Mistral and Black Forest Labs, Sub-Saharan Africa has Lilapi AI. Singapore has Sea Lion, Korea has LG, the appliance maker, and their models. Of course, China has a massive footprint in the space. I don’t see that reflected anywhere here. Christopher S. Penn – 28:46 It’s not in the conversations, it’s not in the hallways, it’s not on stage. And to me, that is a really big blind spot if you think—as many people do—that that is your number one competitor on the world stage. Katie Robbert – 28:57 Why do you think? Christopher S. Penn – 29:01 That’s a very complicated question. But it involves racism, it involves a substantial language barrier, it involves economics. When your competitor is giving away everything for free, you’re like, “Well, let’s just pretend they’re not there because we don’t want to draw any attention to them.” And it is also a deep, deep-seated fear. When you look at all of the papers that are being submitted by Google and Facebook and all these other different companies and you look at the last names of the principal investigators and stuff, nine out of 10 times it’s a name that’s coded as an ethnic Chinese name. China produces more PhDs than I think America produces students, just by population dynamics alone. You have this massive competitor, and it almost feels like people just want to put their heads in the sand and say they’re not there. Christopher S. Penn – 30:02 It’s like the boogeyman, they’re not there. And yet if we’re talking about the deployment of AI globally, the folks here should be aware that is a thing that is not just the Sam Alton Show. Katie Robbert – 30:18 I think perhaps then, as we’re talking about the future of work and big companies, small companies, mid-sized companies, this goes sort of back to what I was saying: you need to expand your horizons of thinking. “Well, we’re a domestic company. Why do I need to worry about what China’s doing?” Take a look at your tech stack, and where are those software packages created? Who’s maintaining them? It’s probably not all domestic; it’s probably more of a global firm than you think you are. But we think about it in terms of who do we serve as customers, not what we are using internally. We know people like Paul has talked about operating systems, Ginny Dietrich has talked about operating systems. Katie Robbert – 31:02 That’s really sort of where you have to start thinking more globally in terms of, “What am I actually bringing into my organization?” Not just my customer base, not just the markets that I’m going after, not just my sales team territories, but what is actually powering my company. That’s, I think, to your point—that’s where you can start thinking more globally even if your customer base isn’t global. That might theoretically help you with that critical thinking to start expanding beyond your little homogeneous bubble. Christopher S. Penn – 31:35 Even something like this has been a topic in the news recently. Rare earth minerals, which are not rare, they’re actually very commonplace. There’s just not much of them in any one spot. But China is the only economy on the planet that has figured out how to industrialize them safely. They produce 85% of it on the planet. And that powers your smartphone, that powers your refrigerator, your car and, oh by the way, all of the AI chips. Even things like that affect the future of work and the future of AI because you basically have one place that has a monopoly on this. The same for the Netherlands. The Netherlands is the only country on the planet that produces a certain kind of machine that is used to create these chips for AI. Christopher S. Penn – 32:17 If that company goes away or something, the planet as a whole is like, “Well, I figured they need to come up with an alternative.” So to your point, we have a lot of these choke points in the AI value chain that could be blockers. Again, that’s not something that you hear. I’ve not heard that at any conference. Katie Robbert – 32:38 As we’re thinking about the future of work, which is what we’re talking about on today’s podcast at Macon, 1,500 people in Cleveland. I guarantee they’re going to do it again next year. So if you’re not here this year, definitely sign up for next year. Take a look at the Smarter X and their academy. It’s all good stuff, great people. I think—and this was the question Paul was asking in his keynote—”Where do we go from here?” The— Katie Robbert – 33:05 The atmosphere. Yes. We don’t need—we don’t need to start singing. I do not need. With more feeling. I do get that reference. You’re welcome. But one of the key takeaways is there are more questions than answers. You and I are asking each other questions, but there are more questions than answers. And if we think we have all of the answers, we’re wrong. We have the answers that are sufficient enough for today to keep our business moving forward. But we have to keep asking new questions. That also goes into that critical thinking. You need to be comfortable not knowing. You need to be comfortable asking questions, and you need to be comfortable doing that research and seeking it out and maybe getting it wrong, but then continuing to learn from it. Christopher S. Penn – 33:50 And the future of work, I mean, it really is a very cloudy crystal wall. We have no idea. One of the things that Paul pointed out really well was you have different scaling laws depending on where you are in AI. He could have definitely spent some more time on that, but I understand it was a keynote, not a deep dive. There’s more to that than even that. And they do compound each other, which is what’s creating this ridiculously fast pace of AI evolution. There’s at least one more on the way, which means that the ability for these tools to be superhuman across tasks is going to be here sooner than people think. Paul was saying by 2026, 2027, that’s what we’ll start to see. Robotics, depends on where you are. Christopher S. Penn – 34:41 What’s coming out of Chinese labs for robots is jaw dropping. Katie Robbert – 34:45 I don’t want to know. I don’t want to know. I’ve seen *Ex Machina*, and I don’t want to know. Yeah, no. To your point, I think a lot of people bury their head in the sand because of fear. But in order to, again, it sort of goes back to that critical thinking, you have to be comfortable with the uncomfortable. I’m sort of joking: “I don’t want to know. I’ve seen *Ex Machina*.” But I do want to know. I do need to know. I need to understand. Do I want to be the technologist? No. But I need to play with these tools enough that I feel I understand how they work. Yesterday I was playing in Opal. I’m going to play in N8N. Katie Robbert – 35:24 It’s not my primary function, but it helps me better understand where you’re coming from and the questions that our clients are asking. That, in a very simple way to me, is the future of work: that at least I’m willing to stretch myself and keep exploring and be uncomfortable so that I can say I’m not static. Christopher S. Penn – 35:46 I think one of the things that 3M was very well known for in the day was the 20% rule, where an employee, as part of their job, could have 20% of the time just work on side projects related to the company. That’s how Post-it Notes got invented, I think. I think in the AI forward era that we’re in, companies do need to make that commitment again to the 20% rule. Not necessarily just messing around, but specifically saying you should be spending 20% of your time with AI to figure out how to use it, to figure out how to do some of those tasks yourself, so that instead of being replaced by the machine, you’re the one who’s at least running the machine. Because if you don’t do that, then the person in the next cubicle will. Christopher S. Penn – 36:33 And then the company’s like, “Well, we used to have 10 people, we only need two. And you’re not one of the two who has figured out how to use this thing to do that. So out you go.” Katie Robbert – 36:41 I think that was what Paul was doing in his AI for Productivity workshop yesterday, was giving people the opportunity to come up with those creative ideas. Our friend Andy Crestadino was relaying a story yesterday to us of a very similar vein where someone was saying, “I’ll give you $5,000. Create whatever you want.” And the thing that the person created was so mind-blowing and so useful that he was like, “Look what happens when I just let people do something creative.” But if we bring it sort of back whole circle, what’s the motivation? Why are people doing it in the first place? Katie Robbert – 37:14 It has to be something that they’re passionate about, and that’s going to really be what drives the future of work in terms of being able to sustain while working alongside AI, versus, “This is all I know how to do. This is all I ever want to know how to do.” Yes, AI is going over your job. Christopher S. Penn – 37:33 So I guess wrapping up, we definitely want you thinking creatively, critically, contextually. Know where your data is, know where your ideas come from, broaden your horizons so that you have more ideas, and be able to be one of the people who knows how to call BS on the machines and say, “That’s completely wrong, ChatGPT.” Beyond that, everyone has an obligation to try to replace themselves with the machines before someone else does it to you. Katie Robbert – 38:09 I think again, to plug Macon, which is where we are as we’re recording this episode, this is a great starting point for expanding your horizons because the amount of people that you get to network with are from different companies, different experiences, different walks of life. You can go to the sessions, learn it from their point of view. You can listen to Paul’s keynote. If you think you already know everything about your job, you’re failing. Take the time to learn where other people are coming from. It may not be immediately relevant to you, but it could stick with you. Something may resonate, something might spark a new idea. Katie Robbert – 38:46 I feel like we’re pretty far along in our AI journey, but in sitting in Paul’s keynote, I had two things that stuck out to me: “Oh, that’s a great idea. I want to go do that.” That’s great. I wouldn’t have gotten that otherwise if I didn’t step out of my comfort zone and listen to someone else’s point of view. That’s really how people are going to grow, and that’s that critical thinking—getting those shared experiences and getting that brainstorming and just community. Christopher S. Penn – 39:12 Exactly. If you’ve got some thoughts about how you are approaching the future of work, pop on by our free Slack group. Go to trust insights AI analysts for marketers, where you and over 4,500 other marketers are asking and answering each other’s questions every single day. Wherever you watch or listen to the show, if there’s a channel you’d rather have it on instead, go to Trust Insights AI Ti Podcast, where you can find us all the places fine podcasts are served. Thanks for tuning in. I’ll talk to you on the next one. Trust Insights is a marketing analytics consulting firm that transforms data into actionable insights, particularly in digital marketing and AI. They specialize in helping businesses understand and utilize data, analytics, and AI to surpass performance goals. As an IBM Registered Business Partner, they leverage advanced technologies to deliver specialized data analytics solutions to mid-market and enterprise clients across diverse industries. Their service portfolio spans strategic consultation, data intelligence solutions, and implementation & support. Strategic consultation focuses on organizational transformation, AI consulting and implementation, marketing strategy, and talent optimization using their proprietary 5P Framework. Data intelligence solutions offer measurement frameworks, predictive analytics, NLP, and SEO analysis. Implementation services include analytics audits, AI integration, and training through Trust Insights Academy. Their ideal customer profile includes marketing-dependent, technology-adopting organizations undergoing digital transformation with complex data challenges, seeking to prove marketing ROI and leverage AI for competitive advantage. Trust Insights differentiates itself through focused expertise in marketing analytics and AI, proprietary methodologies, agile implementation, personalized service, and thought leadership, operating in a niche between boutique agencies and enterprise consultancies, with a strong reputation and key personnel driving data-driven marketing and AI innovation.

Please enjoy this encore of Word Notes. The deployment of rules to the security stack across all data islands, cloud, SaaS applications, data centers, and mobile devices designed to manifest an organization's cybersecurity first principle strategies of zero trust, intrusion kill chain prevention, resilience, and risk forecasting.  CyberWire Glossary link: ⁠https://thecyberwire.com/glossary/policy-orchestration⁠ Audio reference link: “⁠The Value of Using Security Policy Orchestration and Automation⁠,” by David Monahan, uploaded by EMAResearch, 3 April, 2018

Discover Regpack: The Ultimate Onboarding and Payment Solution with Asaf Darash Regpacks.com About the Guest(s): Dr. Asaf Darash is the founder and CEO of Regpack, a leading registration and payments platform designed to enhance how organizations automate their operations. With a PhD from UC Berkeley focused on the intersection of technology and human behavior, Dr. Darash transformed his academic research into Regpack's adaptive architecture that simplifies complex onboarding systems. Under his leadership, Regpack processes billions in payments and optimizes workflows for a variety of sectors, including education, events, and non-profits. Dr. Darash is also a frequent speaker on automation and SaaS innovation. Episode Summary: In this engaging episode of The Chris Voss Show, host Chris Voss sits down with Dr. Asaf Darash, the visionary founder behind Regpack. They dive into the intricacies of Regpack, a robust SaaS platform revolutionizing registration and payment systems for businesses and organizations worldwide. Dr. Darash shares insights into the founding and evolution of Regpack, highlighting how it simplifies complex onboarding processes and enhances automation for its users. The conversation covers the technical prowess and unique services offered by Regpack, including its groundbreaking conditional logic engine and API capabilities. Dr. Darash discusses the importance of creating seamless and intuitive user experiences, emphasizing how Regpack's customization options help businesses effectively engage with clients while saving time and cost. With a keen focus on the service-based market, this episode delves into the challenges faced by businesses in managing onboarding processes and how Regpack's innovative solutions can help overcome them. Key Takeaways: Revolutionizing Onboarding: Regpack's adaptive software transforms the onboarding process for service-based businesses, offering a flexible and efficient solution. Conditional Logic Engine: The platform's distinctive feature allows users to experience a streamlined process tailored to their specific needs, enhancing customer satisfaction. Cost-Effective Payment Processing: Dr. Darash reveals how Regpack reduces payment processing costs using a proprietary method that identifies card types and offers lower rates. Integrations and Customization: With robust API and webhook capabilities, Regpack easily integrates into existing systems, providing extensive customization for clients. Automation and Growth: Businesses leveraging Regpack's automation tools witness an average 30% growth in their revenue as a result of improved efficiency and user experience. Notable Quotes: "Think of a mother that's super tired, end of day, needs to register their kid… While making dinner, it needs to be that simple." — Dr. Asaf Darash "Regpack makes everything just flow." — Dr. Asaf Darash "From my perspective, it's like I'm connecting the two — my business side and my passion for educational services." — Dr. Asaf Darash "The whole thing is made to make sure that you understand how Regpack is gonna help you." — Dr. Asaf Darash "What I was trying to do was figure out a system that had no constraints in it." — Dr. Asaf Darash

Can you just use Claude Code or another LLM to "vibe code" your way into building an AI SOC? In this episode, Ariful Huq, Co-Founder and Head of Product at Exaforce spoke about the reality being far more complex than the hype suggests. He explains why a simple "bolt-on" approach to AI in the SOC is insufficient if you're looking for real security outcomes.We speak about foundational elements required to build a true AI SOC, starting with the data. It's "well more than just logs and event data," requiring the integration of config, code, and business context to remove guesswork and provide LLMs with the necessary information to function accurately . The discussion covers the evolution beyond traditional SIEM capabilities, the challenges of data lake architectures for real-time security processing, and the critical need for domain-specific knowledge to build effective detections, especially for SaaS platforms like GitHub that lack native threat detection .This is for SOC leaders and CISOs feeling the pressure to integrate AI. Learn what it really takes to build an AI SOC, the unspoken complexities, and how the role of the security professional is evolving towards the "full-stack security engineer".Guest Socials -⁠ ⁠⁠⁠⁠⁠Ariful's LinkedinPodcast Twitter - ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠@CloudSecPod⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠If you want to watch videos of this LIVE STREAMED episode and past episodes - Check out our other Cloud Security Social Channels:-⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Cloud Security Podcast- Youtube⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠- ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Cloud Security Newsletter ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠- ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Cloud Security BootCamp⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠If you are interested in AI Cybersecurity, you can check out our sister podcast -⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ AI Security Podcast⁠Questions asked:(00:00) Introduction(02:30) Who is Ariful Huq?(03:40) Can You Just Use Claude Code to Build an AI SOC?(06:50) Why a "Bolt-On" AI Approach is Tough for SOCs(08:15) The Importance of Data: Beyond Logs to Config, Code & Context(09:10) Building AI Native Capabilities for Every SOC Task (Detection, Triage, Investigation, Response)(12:40) The Impact of Cloud & SaaS Data Volume on Traditional SIEMs(14:15) Building AI Capabilities on AWS Bedrock: Best Practices & Challenges(17:20) Why SIEM Might Not Be Good Enough Anymore(19:10) The Critical Role of Diverse Data (Config, Code, Context) for AI Accuracy(22:15) Data Lake Challenges (e.g., Snowflake) for Real-Time Security Processing(26:50) Detection Coverage Blind Spots, Especially for SaaS (e.g., GitHub)(31:40) Building Trust & Transparency in AI SOCs(35:40) Rethinking the SOC Team Structure: The Rise of the Full-Stack Security Engineer(42:15) Final Questions: Running, Family, and Turkish Food

Ever wondered how source maps actually work? In this episode, Nicolo Ribaudo, Babel maintainer and TC39 delegate, breaks down how source maps connect your JavaScript, TypeScript, and CSS back to the original code — making debugging, stack traces, and observability smoother in Chrome dev tools. We dive into how source maps help in both development and production with minified code, explore tools like Webpack, Rollup, Next.js, and Svelte, and share when you should turn off source maps to avoid confusion. Links Website: https://nicr.dev LinkedIn: https://www.linkedin.com/in/nicol%C3%B2-ribaudo-bb94b4187 BlueSky: https://bsky.app/profile/nicr.dev Github: https://github.com/nicolo-ribaudo Resources Squiggleconf talk: https://squiggleconf.com/2025/sessions#source-maps-how-does-the-magic-work Slide deck: https://docs.google.com/presentation/d/1lyor5xgv821I4kUWJIwrrmXBjzC_qiqIqcZxve1ybw0 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? Fill out our listener survey (https://t.co/oKVAEXipxu)! https://t.co/oKVAEXipxu Let us know by sending an email to our producer, Elizabeth, at elizabet.becz@logrocket.com (mailto:elizabeth.becz@logrocket.com), or tweet at us at PodRocketPod (https://twitter.com/PodRocketpod). Check out our newsletter (https://blog.logrocket.com/the-replay-newsletter/)! https://blog.logrocket.com/the-replay-newsletter/ 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 understanding where your users are struggling by trying it for free at LogRocket.com. Try LogRocket for free today. (https://logrocket.com/signup/?pdr) Chapters 00:00 Intro – Welcome to PodRocket + Introducing Nicolo Ribaudo 00:45 What Are Source Maps and Why They Matter for Debugging 01:20 From Babel to TC39 – Nicolo's Path to Source Maps 02:00 Source Maps Beyond JavaScript: CSS, C, and WebAssembly 03:00 The Core Idea – Mapping Compiled Code Back to Source 04:00 How Source Maps Work Under the Hood (Encoded JSON) 05:10 File Size and Performance – Why It Doesn't Matter in Production 06:00 Why Source Maps Are Useful Even Without Minification 07:00 Sentry and Error Monitoring – How Source Maps Are Used in Production 08:10 Two Worlds: Local Debugging vs. Remote Error Analysis 09:00 You're Probably Using Source Maps Without Realizing It 10:00 Why Standardization Was Needed After 15+ Years of Chaos 11:00 TC39 and the Creation of the Official Source Maps Standard 12:00 Coordinating Browsers, Tools, and Vendors Under One Spec 13:00 How Chrome, Firefox, and WebKit Implement Source Maps Differently 14:00 Why the Source Maps Working Group Moves Faster Than Other Standards 15:00 A Small, Focused Group of DevTools Engineers 16:00 How Build Tools and Bundlers Feed Into the Ecosystem 17:00 Making It Easier for Tool Authors to Generate Source Maps 18:00 How Frameworks Like Next.js and Vite Handle Source Maps for You 19:00 Common Pitfalls When Chaining Build Tools 20:00 Debugging Wrong or Broken Source Maps in Browsers 21:00 Upcoming Feature: Scopes for Variables and Functions 22:00 How Scopes Improve the Live Debugging Experience 23:00 Experimental Implementations and How to Try Them 24:00 Where to Find the TC39 Source Maps Group + Get Involved 25:00 Nicolo's Links – GitHub, BlueSky, and Talks Online 25:30 Closing Thoughts

As the President and Founder of InnerAction Media, an award-winning marketing and branding agency, Jim Matuga has been helping companies simplify, clarify, and amplify their brand messages for over 35 years. Him has a proven track record of delivering cost-effective and strategic solutions to clients across various industries, using his expertise in High Quality video production, inbound marketing, PPC campaigns, social media management, and web site development. On May 1, 2023, Jim's team launched StoryMaker, an easy-to-use SaaS application software platform that uses, at it's core, InnerAction Media's (IAM) proprietary “StoryMaker” process and harnesses the power of generative Artificial Intelligence (AI) to create custom marketing messaging for small businesses and non-profits. Thjeir patent-pending algorithm ensures content is original, tailored just for customers' businesses, and includes the capacity to create content for all products and services. Jim is also the author of Marketing Matters, a book that teaches business leaders how to build a solid marketing strategy that cuts through the noise, connects with their ideal prospects, and moves them to action. His mission is to empower small businesses with the tools and skills they need to grow and thrive in the digital age. Jim is also the host of Positivelywv.com, a podcast that showcases the success stories of West Virginia entrepreneurs. He is passionate about sharing his knowledge and experience with others, and is always looking for new ways to innovate and create value. Connect with Jon Dwoskin: Twitter: @jdwoskin Facebook: https://www.facebook.com/jonathan.dwoskin Instagram: https://www.instagram.com/thejondwoskinexperience/ Website: https://jondwoskin.com/LinkedIn: https://www.linkedin.com/in/jondwoskin/ Email: jon@jondwoskin.com Get Jon's Book: The Think Big Movement: Grow your business big. Very Big!   Connect with Jim Matuga: Website: www.inneractionmedia.com X: https://x.com/jmatuga Instagram: https://www.instagram.com/jmatuga LinkedIn: https://www.linkedin.com/in/jmatuga/ Facebook: https://www.facebook.com/jimmatuga                                                                               *E – explicit language may be used in this podcast.