Podcasts about enterprises

Can organizations trust an AI recommendation when they cannot understand the evidence, relationships, and previous decisions behind it? In this episode of Tech Talks Daily, I welcome back Jim Webber, Chief Scientist at Neo4j, to discuss the company's acquisition of GraphAware and its move from graph database provider to graph intelligence platform. GraphAware has worked with Neo4j for many years and developed Hume, an intelligence analysis platform used to connect and examine complex information. Bringing the two companies together gives Neo4j a direct role in applications serving police forces, governments, intelligence agencies, and other organizations handling connected data. Jim explains why context has become one of the biggest requirements for dependable AI. Enterprises already possess enormous volumes of data, but facts alone provide endpoints rather than the complete path leading to a decision. An agent needs to understand the knowledge available, the conversation taking place, and the record of previous decisions. It also needs to know which actions produced good outcomes and which produced poor ones. Jim compares these information layers to SimCity. Each can be viewed separately, but their greater value appears when they are combined. Knowledge, conversations, and decision traces can then help an agent understand why something happened and learn from the result. This introduces an interesting lesson from scientific research. Positive outcomes are frequently published, while failed experiments receive less attention. An AI agent needs both. Recording the breadcrumbs behind good and bad decisions provides the material required to improve its future behavior. We also discuss why large language models cannot understand every organization by themselves. Jim describes a model as a lossy compression of the internet. It can generate impressive natural language, but it does not automatically understand a company's policies, customers, history, evidence, or operating environment. Retrieval augmented generation can introduce relevant organizational information into the process. Graph RAG adds relationships between facts, helping the system understand how people, events, products, accounts, and other entities connect. According to research Jim references from the National Innovation Centre for Data, Graph RAG can improve accuracy while reducing costs by using fewer, higher-quality tokens. Explainability becomes especially important when AI supports decisions across policing, cyber defense, taxation, intelligence, banking, and government. A fluent answer may sound authoritative while containing a serious technical mistake. Jim shares an example from his own work where an agent confidently warned him about a "committed minority" inside a fault-tolerant computing protocol. The statement sounded plausible, but only a majority could commit within that protocol. Someone without Jim's technical knowledge might have accepted the recommendation and removed working code. This leads us to human oversight. Jim argues that the correct level depends on the consequences of the action. Automating a routine banking process with monitoring and safeguards may improve the customer experience. Ordering someone's arrest based solely on an agent's conclusion demands human involvement. We also consider digital sovereignty and why control over data has become a strategic concern for governments and large enterprises. Geopolitical instability, overseas technology dependencies, privacy requirements, and changing national policies are forcing leaders to ask where their data resides and whether they can retrieve or move it. Jim explains how Neo4j intends to offer organizations flexibility over where their information is stored and how it is deployed. The discussion also examines the opportunity for Neo4j and Hume to provide an alternative within a market where Palantir has held a powerful position. Looking ahead, Jim imagines intelligence analysts directing swarms of digital agents. Those agents could search data, connect evidence, identify relevant patterns, and present findings while humans retain responsibility for consequential decisions. If AI can connect information at machine speed, how do we ensure the person making the final decision can inspect the evidence and challenge the conclusion? Listen to the episode and share your thoughts with me.

As AI inference costs have dropped by over 90%, enterprises are embedding data and intelligence at the core of their operating and business models, enabling always-on, global execution beyond human limits. How are these AI-first enterprises reorganizing around AI in practice, and under what conditions does this actually translate into long-term value for society? This is the full audio from a session at the Annual Meeting of the New Champions 2026 in Dalian, China on 23-25 June, 2026. Watch it here: https://www.weforum.org/meetings/annual-meeting-of-the-new-champions-2026/sessions/whats-the-intelligence-limit-for-ai-first-enterprises/ Speakers: Yuxiang Zhou, Chief Executive Officer, Black Lake Technologies, Michael Römer, Senior Partner and Global Co-Lead, Activate: Digital and Analytics, Kearney Joey Wat, Chief Executive Officer, Yum China Holdings, Inc. Sudip Roy, Co-Founder and Chief Technology Officer, Adaption Yang Yanqing, Director of Center for Education, Innovation and Sustainable Development, ShanghaiTech University Mehdi Ghissassi, Chief Product and Technology Officer, AI 71 Catch up on all the action from the World Economic Forum's Annual Meeting of the New Champions 2026 at wef.ch/amnc26 and across social media using the hashtag #AMNC26. Check out all our podcasts on wef.ch/podcasts:  YouTube: - https://www.youtube.com/@wef/podcasts Radio Davos - subscribe: https://pod.link/1504682164 Meet the Leader - subscribe: https://pod.link/1534915560 Agenda Dialogues - subscribe: https://pod.link/1574956552

Enterprise leaders face a growing gap between AI ambition and the fragmented data, legacy systems, and cultural friction that prevent pilots from becoming scalable value.   In this episode, Julian Tang, Chief Operations Officer for the Innovation Office at BlackRock, examines how unified data foundations, modernized infrastructure, and transparent governance enable organizations to move from reactive experimentation to intentional, enterprise‑wide AI deployment, in conversation with host Matthew DeMello.   He highlights the practical shifts required to reduce friction, build trust in AI systems, and create repeatable playbooks that let teams scale responsibly and with confidence.   Learn how to identify real AI trends by tracking where venture funding is flowing, and by listening to how leading CEOs describe risk and competitive strategy. Download our free PDF report, "3 Ways to Discover AI Trends in Any Sector" at emerj.com/ait1  

By Doug Green “It certainly eliminates the speed bump.” That is how James Walters, VP Strategic Vendors and Alliances at Exclusive Networks, describes the impact of the company's appointment as a Fortinet Global Distributor. In this TR Podcast, Walters explains that the new designation builds on a relationship with Fortinet spanning more than 25 years, while giving Exclusive Networks a framework to better support partners and customers pursuing cross-border and multinational opportunities. At the center of the new model is a global deal desk designed to centralize multinational transactions. Walters says Exclusive Networks can help coordinate requirements that previously had to be handled market by market, including payments, tax alignment, support documentation and support-of-record issues. The result, he says, should be fewer administrative requirements, faster sales cycles and improved revenue recognition for partners and their customers. Under previous arrangements, multinational deals often required partners to work through local teams and local processes, creating inconsistencies in technical support, deal structure and transaction velocity. The new framework is intended to remove those friction points while preserving Fortinet's partner protections. It is aimed at global systems integrators and large international partners, but Walters says regional resellers with customers expanding internationally should also engage Exclusive Networks. The opportunity also extends to enterprise customers and MSPs. Enterprises operating across multiple countries can use the model to accelerate Fortinet deployments and strengthen security posture across locations. MSPs, meanwhile, can use Exclusive Networks' global go-to-market support to expand Fortinet technology across multinational customer environments, with support spanning pre-sales, point of sale, implementation and lifecycle management. Walters describes the designation as a natural next step in an already strong Fortinet relationship. His message to partners is straightforward: whether they are global integrators, MSPs or regional resellers beginning to follow customers into new markets, Exclusive Networks now has a broader global structure to help them take Fortinet solutions across borders with less friction and more consistent support. Visit www.exclusive-networks.com Watch the TR Podcast to learn more.

Bloomberg reported that OpenAI reached a $40 billion annualized revenue run rate and is preparing for an IPO. The company monetizes through ChatGPT consumer subscriptions, ChatGPT Enterprise, API usage, and co-selling via Microsoft's Azure OpenAI Service. Investors will scrutinize margins, revenue mix, and dependence on Microsoft when the S-1 is filed. OpenAI hired Sarah Friar as CFO in 2024 to build public company readiness. Competition from Anthropic, Google, and Meta is pressuring price and performance. Enterprises are negotiating multi-year agreements with data controls and service levels, while startups are building multi-model architectures to manage cost and reliability.Learn more on this news by visiting us at: https://greyjournal.net/news/ Hosted on Acast. See acast.com/privacy for more information.

「上田綺世の獲得にリーズが動く？「自然な移籍先となり得る」「田中碧の存在という…」」　　プレミアリーグのリーズ・ユナイテッドは、今2026年夏の移籍市場で前線の補強を検討している。オランダ1部エールディビジのフェイエノールトに所属する日本代表FW上田綺世の名前も候補として挙がる中、リーズのFWジョー・ゲルハートの退団が補強資金に影響を与える可能性があるようだ。　UKメディア『Leeds United News』は「49ers Enterprisesはジョー・ゲルハートの650万ポンドでの退団を活用し、上田綺世の獲得によってリーズのストライカー問題を解決できる」と題した記事を掲載した。　同メディアは、ゲルハートの移籍金650万ポンド（約14億円）を上田の獲得に充てるべきだと主張している。　同メディアによると、リーズは今夏を通じて上田に関心を寄せているという。フェイエノールトは日本代表FWに対する1,500万ポンド（約32億3,000万円）前後のオファーを検討しており、以前に伝えられた2,500万ポンド（約53億8,000万円）から金額が下がっているという。　ゲルハートの売却資金を再投資すれば、上田獲得に必要な実質的な費用は約850万ポンド（約18億3,000万円）となり、リーズのオーナー企業である『49ers Enterprises』の取締役会は他のポジションの補強資金を大きく取り崩さず、フェイエノールトの要求額を満たせると伝えている。　また、同メディアはリーズに所属する日本代表MF田中碧の存在が上田に与える影響について、以下のように伝えている。　「また、リーズには個人条件の面でも、田中の存在という明確な強みがある。日本代表でともにプレーする両選手の親密な関係は、文化面と戦術面の双方で上田がすぐに適応するための橋渡しとなる」　「そのため、エランド・ロードはフェイエノールトのストライカーにとって自然な移籍先となり得る」　同メディアは、27歳の上田について、ペナルティーエリア内での動き、運動量、空中戦の強さ、両足での決定力を備えていると評価している。

Has enterprise AI finally reached the point where impressive demonstrations are no longer enough? In this episode of Tech Talks Daily, I speak with Bruce McMahon, Chief Product Officer at CallMiner, about what he describes as the industrialization of AI: the move from experimentation and excitement toward repeatable processes, measurable ROI, better customer experiences, and technology that can operate reliably at enterprise scale. Bruce explains why business leaders are increasingly asking a much simpler question about AI: how is this going to create value? Drawing on CallMiner's experience analyzing hundreds of thousands of hours of customer interactions every day, Bruce discusses how AI can surface operational inefficiencies and customer insights that were previously difficult to identify. The opportunity is not simply generating more data. Organizations need processes that get the right insight to the right person so something actually changes as a result. We also discuss how AI is changing workforce expectations. Bruce sees curiosity and adaptability becoming increasingly valuable, particularly among technical teams. As AI takes on more routine work, employees who question outputs, experiment with new approaches, and apply human judgment can become more valuable than those who rely solely on established technical knowledge. The economics of enterprise AI present another challenge. Foundation models, capabilities, and pricing continue to change rapidly, creating questions around vendor dependency and long-term costs. Bruce explains why companies may increasingly use a mixture of commercial, open-source, fine-tuned, self-hosted, and proprietary models rather than relying on one provider for everything. Governance becomes even more important as AI agents begin interacting directly with customers. We discuss red teaming, bias testing, compliance, data protection, monitoring, and why organizations need to decide which actions can be fully automated and which decisions must remain accountable to a human. Bruce also examines how AI is changing customer experience and the BPO industry. Rather than choosing between humans and AI agents, he sees value in designing systems where both can work together, with people handling interactions requiring judgment while AI manages high-volume and repetitive work. For CIOs, CTOs, COOs, customer experience leaders, and anyone responsible for enterprise AI strategy, this conversation provides a practical look at moving beyond AI pilots and turning the technology into a dependable part of business operations.  

In this special episode of Cloud Wars Live, Bob Evans speaks with Manish Sood, founder and CEO of Reltio, about the rapidly changing relationship among enterprise data, AI, and business strategy following SAP's acquisition of Reltio. Sood explains why trusted, interoperable data is becoming increasingly important as enterprises embrace agentic AI and autonomous business processes. He also discusses why AI models themselves may increasingly become commoditized, how organizations can bridge legacy and next-generation technology, and the ideas behind his new book, Agentic Intelligence: Strategy at the Speed of Data. Data Powers Agentic AI Data Becomes the Differentiator: Sood argues that enterprises should stop viewing data simply as another asset and instead recognize it as an interoperable asset that becomes more valuable as it is put to work across the organization. This distinction becomes particularly important as AI capabilities spread. If businesses eventually gain access to broadly comparable AI models, competitive differentiation will increasingly come from proprietary enterprise knowledge: decades of customer information, operational history, relationships, and business context. AI Creates Unavoidable Urgency: Enterprise transformation once proceeded at what Sood describes as a relatively organic pace. AI has fundamentally changed that dynamic by creating an enormous pull on organizations to move more quickly. Executives might still feel uncertainty about AI, but another fear has become even stronger: getting left behind. That competitive pressure is creating urgency around experimentation, investment, and execution. Sood sees this as potentially healthy because it forces organizations to reconsider technology and processes that previously seemed difficult to change. Strategy Still Beats Shiny Objects: AI's extraordinary pace doesn't eliminate the fundamentals of good business strategy. Sood notes that every major technology cycle produces a new "shiny object" that organizations race to adopt, sometimes before determining the architecture, strategy, and business value required to make it useful. AI shouldn't become another example. Enterprises absolutely need to embrace the technology, but Sood argues that they cannot sacrifice disciplined thinking about what they are trying to accomplish. That idea sits at the center of Agentic Intelligence. The Big Quote: "Our thesis has always been that data is not just an asset. Data is the interoperable asset that needs to be used.” More from Manish Sood and Reltio: Follow Manish on LinkedIn and learn more about Reltio and SAP at the following links: Reltio: Agentic AI Readiness Research, SAP Business Data Cloud, and Reltio: Building a Foundation for Agentic AI Visit Cloud Wars for more.

     Lamekia Davis of Chicago, IL, is a nonprofit executive, financial literacy advocate, elected official, speaker, and entrepreneur.  She is also dedicated to empowering communities through education, mentorship, and economic opportunities.  Lamekia serves as the Founder and CEO of the Heyy Girl Foundation and Lamekia Davis Global Enterprise.  She is the visionary behind several initiatives focused on youth development, financial literacy, leadership, and wealth building.        Through the Heyy Girl Foundation and LDG Enterprise, Lamekia provides mentorship, youth empowerment programming, financial literacy education, leadership development, workforce readiness training, and community outreach initiatives. One of her signature initiatives is Wealth Warriors, a financial literacy platform and curriculum designed to teach children and teens about saving, budgeting, entrepreneurship, investing, and building generational wealth in an engaging and culturally relevant way.  Lamekia also leads Lamekia Davis Global, which focuses on leadership development, financial literacy education, speaking, consulting, and wealth strategy initiatives.        In addition to the products and services mentioned, she also offers Financial literacy workshops and assemblies for schools, youth mentorship programs, parent and family engagement programs, leadership and empowerment conferences, coaching and consulting, community partnership initiatives, and speaking engagements and training sessions.  "Our mission is to equip individuals with the tools, confidence, and knowledge necessary to thrive personally, professionally, and financially," she says.        With more than 20 years of experience spanning banking, nonprofit leadership, community engagement, and business development, Lamekia has built a reputation as a transformational leader and "solutionist".  In her capacity, she has successfully developed pipelines to prosperity for underserved communities. She currently serves as a Board Member for Rich Township High School District 227.  Additionally, she has served as Chair of the Park Forest Youth Commission.      Lamekia is a proud mother whose passion for legacy, faith, and service deeply influences her work and mission.  She earned her Bachelor of Arts in Business Administration with a minor in Accounting from Robert Morris College. She is currently pursuing her Master's Degree in Leadership.  Throughout her journey, she has been recognized with numerous honors, including the Presidential Lifetime Achievement Award, the Peggy A. Montes Cook County Unsung Heroine Award, and recognition as a Woman of Excellence honoree.           Lamekia shares that her journey in business began from a personal experience.  "As a teen, I experienced homelessness, instability, and adversity firsthand. Those experiences shaped my heart for service and gave me a deep understanding of what many young people and families silently endure.  I knew early on that if I ever made it through those difficult seasons, I wanted to help others do the same. The vision for the Heyy Girl Foundation was born out of a desire to create safe spaces, mentorship opportunities, and pathways to success for young girls and underserved communities."        She adds that her background in banking and finance further revealed how many families lack access to financial education and wealth-building tools. That realization inspired Lamekia to merge mentorship with financial literacy, which ultimately led to the development of Wealth Warriors and other empowerment initiatives.  "Everything I build is rooted in legacy, impact, and creating opportunities that I wish existed for me growing up," she says.     Lamekia says what she loves most about what she does is watching people transform. "There is nothing more rewarding than seeing a young person discover their confidence, a woman realize her potential, or a family begin to break generational cycles.  I love being able to inspire people while also giving them practical tools to change their lives. Motivation without strategy only goes so far, so I take pride in creating programs that not only encourage people emotionally but also equip them financially, mentally, and professionally.  I also love creating. Whether it is building programs, developing curriculum, mentoring youth, speaking, or launching new initiatives, I enjoy bringing vision to life in ways that create lasting impact."      Accomplishing what Lamekia has in her career hasn't come without some challenges.  Yet, she has pressed her way through and kept her sights on completing her mission.  She says that one of the biggest challenges in nonprofit and community-based work is sustainability.  "Often, the need is far greater than the resources available.  Balancing vision, funding, staffing, programming, and growth can be challenging," she says.  Another challenge has been navigating spaces where innovation and bold ideas are not always immediately embraced.  "Building something meaningful requires resilience, patience, and the ability to continue moving forward even when people do not initially see the vision," Lamekia shared.      She has managed these challenges through faith, strategic partnerships, consistency, and a willingness to continuously learn and evolve.  "I believe strongly in collaboration and community. No major vision is built alone.  Most importantly, I have learned that setbacks are often preparation for greater opportunities," she says.        Life experiences, Lamekia says, have impacted her tremendously. She also says that her son and daughter have been one of her greatest motivations.  "My children remind me daily why legacy matters and why it is important to build something bigger than yourself."  Lamekia has also been impacted by mentors, community leaders, educators, and women who led with strength and grace despite adversity.  "Their examples showed me what leadership, perseverance, and service truly look like," she says.         Lamekia shares that she draws inspiration from people who create impact beyond themselves.  This includes individuals who use their gifts, influence, and platforms to change lives and open doors for others.  "I am inspired by visionary leaders, entrepreneurs, educators, faith leaders, and community builders who continue showing up despite obstacles. I especially admire people who are committed to building generational wealth, strengthening communities, and leaving meaningful legacies," she says.        While she has encountered some hurdles along her journey, Lamekia says there isn't much she would change about the way things have happened, because every challenge taught her something valuable. "Some seasons stretched me, humbled me, and forced me to grow in ways success alone never could.  If anything, I would have learned earlier to trust my vision more, move with greater confidence, and not underestimate the value of my voice, expertise, and ideas.  I would have prioritized rest and balance sooner. As entrepreneurs and leaders, we sometimes spend so much time pouring into others that we forget to care for ourselves."      Looking ahead, Lamekia plans to continue to grow the Heyy Girl Foundation and Wealth Warriors into nationally recognized platforms focused on financial literacy, mentorship, and youth empowerment.  She is also working on larger community development initiatives that will provide educational programming, leadership development, and supportive resources for families and youth.  "Moving forward, I plan to continue expanding my speaking, consulting, and educational platforms while pursuing opportunities in public leadership and policy advocacy.  Ultimately, my goal is to build institutions, programs, and opportunities that create lasting change for generations to come," she says.   To learn more about Lamekia Davis, please visit her website at  www.lamekiadavisglobal.com   To learn more about Huami Magazine, please visit our website at www.huamimagazine.com   To purchase some delicious brittle from Papa's Brittle, please visit their website at www.papasbrittle.com    

Everyone is talking about AI agents. What fewer people are talking about is what happens behind the scenes to make those agents actually work. At Boomi World Tour London, I spoke to Andrea Bureca from AWS to discuss the growing intersection of AI, data management, and enterprise integration.One theme that emerged throughout our conversation was that successful AI initiatives are rarely just about AI. They depend on access to trusted data, reliable integrations, governance, and the ability to connect systems across the organization.We discussed:• The patterns AWS is seeing across enterprise AI deployments• How customers are approaching agentic AI initiatives• Why data management is becoming increasingly important for AI success• Common mistakes organizations make when scaling AI projects• The value of partnerships in helping customers move faster and reduce risk• What customers can expect from the AWS and Boomi relationship moving forwardIf your organization is thinking about AI agents, this conversation offers a practical perspective on what it actually takes to make them successful.The full interview is now live.#data #ai #boomi #BoomiWorldTour #london #api #BoomiWorld ##BoomiAmbassador #theravitshow

Summary Today Marc is chattin' with Richa Kaul, founder and CEO of an AI-based compliance automation platform. The conversation centered on how AI is reshaping enterprise governance, risk, and compliance (GRC), especially by helping organizations handle growing complexity without simply adding more headcount. The discussion quickly focused on how compliance teams can use automation and AI to streamline vendor risk, regulatory requirements, and other time-consuming workflows. Richa explained that his approach starts by separating what truly requires human judgment from what can be automated. A major theme was the mismatch between the speed of modern risk and the pace at which organizations can hire. Richa argued that risk is increasing faster than teams can scale, making it unrealistic to solve GRC challenges by just expanding staff. Instead, she framed the real question as what work should remain with humans and what work can be handled by AI or automation. She emphasized that teams are bogged down by urgent audit prep, repetitive tasks, and reactive “fire drills,” which prevents them from focusing on strategic risk reduction. The chat then moved into visibility and granularity in risk management, particularly around privacy. Richa noted that many CISOs and GRC leaders lack sufficient visibility into their organization's risks, especially because privacy is cross-functional and touches employees, users, operations, and regulatory obligations. She said this lack of clarity makes it difficult for leaders to confidently communicate risk to boards or determine where to invest time and resources. In her view, the biggest issue is not just managing risk, but being able to see it clearly enough to act on it. Another key topic was AI governance. Richa pointed out that many companies are paying attention to AI policy at the top level, but are not doing enough to train employees at the operational level, where mistakes are most likely to happen. She described the “last mile” of AI governance as especially vulnerable, since employees may unknowingly expose proprietary information by entering sensitive data into tools like GPT. According to Richa, human behavior is often the weakest link, and effective governance requires education and training throughout the organization, not just policy statements from leadership. Their chat also touched on industry-specific risk, with healthcare highlighted as a major area of concern. Richa said healthcare compliance appears underinvested compared with financial services, even though both are highly regulated and handle highly sensitive data. She closed by offering a practical starting point for companies facing generative AI challenges: map your most important data, follow it from input to output, identify the systems it touches, and secure each step of the journey. His overall message was optimistic — that even though the risk landscape feels overwhelming, organizations have tools, platforms, and partners that can help them manage it more effectively. Key Points AI can reduce compliance burden by automating repetitive GRC tasks. Organizations can't hire fast enough to keep up with rising risk and regulatory complexity. Many leaders lack clear visibility into privacy and cross-functional risk. AI governance fails most often at the employee level, not just the policy level. Healthcare compliance is highly exposed and may be underinvested relative to its risk. Key Quotes “Risk right now is increasing at a speed and at a rate that teams cannot possibly hire to mitigate.” “It is not the question of, should teams get smaller. I think it’s a question of what work should humans be doing and what work can I do instead.” “A lot of CISOs tell me that they don’t have the visibility, or at least the granularity of visibility into their risks that they would like.” “Humans are the weakest link.” “Don’t you need to boil the ocean, but let’s look at what is your highest risk data.” About Our Guest Richa Kaul is a technology executive and Head of Product Engineering: Strategy, AI Builder, and Cloud & AI Enterprise Transformation, with 20+ years of experience leading cloud, data, and AI initiatives across Fortune 500 organizations. She has managed portfolios as large as $2B in revenue and $300M in operating budgets, while building global teams of 100+ and advising CxOs on enterprise AI and financial strategy. Richa is known for driving GenAI adoption, modernizing data platforms, advancing AI governance, and delivering scalable, cost-effective transformation across banking, capital markets, asset management, and wealth management. Follow Our Guest LinkedIn About Our Host National co-chair of the Cyber Center for Excellence, Marc Schein, CIC,CLCS is also a Risk Management Consultant at Marsh McLennan Agency. He assists clients by customizing comprehensive commercial insurance programs that minimize the burden of financial loss through cost effective transfer of risk. By conducting a Total Cost of Risk (TCoR) assessment, he can determine any gaps in coverage. As part of an effective risk management insurance team, Marc collaborates with senior risk consultants, certified insurance counselors, and expert underwriters to examine the adequacy of existing client programs and develop customized solutions to transfer risk, improve coverage and minimize premiums. Follow Our Host Website | LinkedIn

In this episode of HFS Unfiltered, Saurabh Gupta, President of HFS Research, is joined by Anuj Krishna, Cofounder and President - Technology & Growth of MathCo, to discuss one of the least understood reasons enterprise AI stalls: the absence of context. The pattern is everywhere. Enterprises have sky-high AI ambitions, yet pilots multiply and almost none reach production, what Saurabh calls “death by a thousand POCs.” In research HFS and MathCo ran together, roughly two-thirds of enterprises admitted they don't know where their knowledge lives; it's trapped in people's heads, undocumented processes, and scattered data. Anuj's argument: organizations obsess over models when the real advantage lies in context, who they are, how they work, and the knowledge behind their decisions. The conversation goes deep on what context actually is, why it can't be static, and who should own it, including the shift toward a federated model with “context stewards” by function. Anuj also lays out how MathCo differs from the platform owners and SIs racing to be “context kings”: rent the tech ecosystem, but own the intelligence, because you can't own your intelligence unless you own your knowledge, and an organization's context is its personality. Saurabh closes with a sharp thesis: models and agents will become a utility, and neither will differentiate you, but context is your identity, and owning it is the only sustainable advantage going forward. Read the associated Take 5 Report, titled "Fund the context layer and close the 2.5x AI ambition gap," here: https://www.hfsresearch.com/research/fund-layer-ai-ambition-gap/ #EnterpriseAI #ContextEngineering #AgenticAI #OwnYourIntelligence #MathCo #HFSResearch #AIStrategy #DataGovernance #DigitalTransformation #FutureOfWork

Alex Atallah is the Founder and CEO @ OpenRouter, the unified interface for LLMs. The company has raised over $153M in funding, with the latest valuation pricing the company at $1.3BN. OpenRouter is reportedly in an acquisition process with Stripe for $10BN.  AGENDA: 00:00 Is OpenRouter Selling to Stripe for $10 Billion? 04:05 What Did Alex Learn From Scaling OpenSea? 06:38 What Did OpenRouter's Founding Thesis Get Wrong? 14:47 Is AI Model Routing Already Being Commoditized? 19:12 Do Falling Token Prices Help or Hurt OpenRouter? 27:16 Should America Be Alarmed by Chinese Open Models? 32:43 Will US Open-Source Models Compete With Chinese Models in the Next 12 Months? 39:26 Will the Router Be Swallowed by the Agent Framework? 48:56 Is Distillation Wrong—and How Should We Look at It? 50:01 Is the Reported $10 Billion Stripe Deal Actually Happening?

Intel Chat with Matt Bromiley and Chris Luft — recorded in person at Black Hat USA in Las Vegas, day two.No prep doc, no script: just what Matt and Chris were actually hearing on the floor.• Shai-Hulud is back. The self-replicating npm worm returned on August 4, trojanizing the keyv / cacheable family and spreading to 400+ packages within hours. Chris reads through Datadog Security Labs' analysis of the Shai-Hulud 2.0 wave: 796 packages and 1,092 versions, 20M+ weekly downloads, credential harvesting with TruffleHog, GitHub repositories used for both exfiltration and command and control, and a worm that reads its own code to propagate without a C2 server.• The LLM that downloaded the malicious package by itself. A researcher asked a frontier model about a compromised package, and the model decided the best way to help was to go fetch a copy — tripping the SOC's alert and bypassing the company's centralized package clearing house on the way.• Non-human identity as the new perimeter. Every agent you introduce is another identity: who created it, what can it reach, how long should it live?• "Computer says no." Matt's colleague hit a refusal from Opus 5, and the session automatically downgraded to 4.8 and completed the task. Which raises the real question of the episode: do security teams now need model pinning, the way we once needed certificate pinning? And if defenders pin to older models to keep working while adversaries use the newest ones, have we rebuilt the same gap all over again?• AI governance and change control — which models are approved for which tasks, and what happens when a vendor ships a new version or deprecates an old one.• Token spend as a CISO budget line item. Enterprises buying tokens at a scale their vendors can't match and pulling those vendors onto their plan, token burn as an insider-threat vector, and why $100,000 of tokens is not $100,000 of productivity.• Defender takeaways: pin your npm packages, get security off its island and talk to your developers, build approved paths before detections, least privilege and key rotation, and network-gated pushes as a deliberate chokepoint.Stories covered:• https://www.elastic.co/security-labs/shai-hulud-chaindrop-npm-supply-chain• https://research.jfrog.com/post/shai-hulud-is-back-august/• https://securitylabs.datadoghq.com/articles/shai-hulud-2.0-npm-worm/• https://securitylabs.datadoghq.com/articles/npm-worm-compromises-popular-npm-packages/• https://unit42.paloaltonetworks.com/npm-supply-chain-attack/Chapters:0:00 Live from Black Hat, in person for once0:48 How Black Hat has changed4:31 No prep — let's talk about what's actually happening here4:57 Shai-Hulud is back: supply chain compromise6:23 The LLM that downloaded the malicious package7:19 Inside Shai-Hulud 2.010:34 When attackers and defenders use the same tools11:39 Non-human identity is the new perimeter12:13 Opus 5 said no, so the session downgraded itself15:23 Do security teams need model pinning?18:20 Three companies, very nebulous rules18:35 AI governance: which model for which task21:19 Token spend hits the security budget22:58 Is token spend a productivity metric?25:46 Pin your packages26:25 Get security off the island29:17 Least privilege, key rotation, chokepoints32:55 Why it's called Shai-Hulud33:25 Wrapping up at Black HatThe Cybersecurity Defenders Podcast — a podcast about cybersecurity and the people that keep the internet safe. New episodes drop weekly.Subscribe wherever you listen:• Spotify: https://open.spotify.com/show/6ep00zeY3S8ffZ4o0UeSps• Apple Podcasts: https://podcasts.apple.com/us/podcast/the-cybersecurity-defenders-podcast/id1649981740• YouTube: https://www.youtube.com/@limacharlieioLearn more about LimaCharlie: https://limacharlie.io#cybersecurity #infosec #threatintel #AIsecurity #supplychainsecurity

Imagine redesigning your most important processes from a blank sheet of paper, with no legacy systems to hold you back. Alpa Lally, Chief Product Officer at Grant Thornton, shares how the company is transforming into a frontier firm by reimagining core processes instead of automating them. She unpacks how embedded analytics reshapes client conversations, why AI governance is what helps you move faster, and how to reinvent your career in the age of AI. Key Moments: From Structural Engineering to Product Leadership (01:36): Alpa explains how designing buildings taught her the vision, strategy, and foundation-up thinking she now applies to product. Becoming a Frontier Firm (06:27): Rethinking how work gets done for 13,000-plus professionals means recognizing that automating a broken process just does the wrong thing faster. Embedding ThoughtSpot Analytics (14:57): By putting insights in auditors' hands on day one, Grant Thornton shifts client conversations from data gathering to strategy. The AI Proof Gap: Governance Enables Speed (19:32): Alpa reframes governance as what lets you move faster, sharing that 78% of firms doubt they'd pass an AI governance audit. Is Product Management Dead? (24:33): The role is evolving, not dying, and AI raises the value of deciding which opportunities are actually worth pursuing. Key Quotes: “A frontier firm uses AI not just to improve how work gets done, but fundamentally rethinks how the work gets done. It's moving beyond productivity gains and creating entirely new ways to deliver value.” - Alpa Lally “The challenge is if you simply automate a broken process, you end up doing the wrong thing faster.” - Alpa Lally “What ThoughtSpot has done is [give us] our ability to embed them immediately into the flow [which] has opened up a whole level of different insights that we can offer, not to our practitioners only, but imagine an auditor showing up on day one to your client and having these insights already calculated, already delivered.” - Alpa Lally Mentions Grant Thornton's 2026 AI Impact Survey Report Wall Street is debating the AI buildout. Enterprises just answered: More than 80% say their GPUs run at half capacity or less Hers for the Taking by Tracey Newell Guest Bio Alpa Lally is the Chief Product Officer at Grant Thornton. Alpa is an experienced product management executive with several years in designing, developing, and launching consumer and business products for large to mid-sized to small organizations, fintechs, startups, and Fortune 500. She has led global cross-functional teams to drive high growth targets while staying laser-focused on solving customer and consumer problems. Alpa leverages data and analytics to drive successful business outcomes that deliver results and achieve corporate growth goals. Hear more from Cindi Howson here. Sponsored by ThoughtSpot.

Hazel Nolan, National Secretary for Services and Enterprises with Forsa, discusses the industrial action being taken by union members at Oberstown Detention Campus.

Jason Leeds is Chief Growth Officer at Dartcor Enterprises where he helps organizations use hospitality to create workplaces that strengthen culture, connection, and employee engagement. Jason brings a unique perspective at the intersection of hospitality, commercial real estate, and the future of work, so Mike Petrusky asks him how hospitality helps people connect and thrive at work. They explore intentional, detail-driven experiences that can contribute to a sense of belonging and increase employee engagement as facility management leaders seek to reinvent workspaces and make them more attractive. Technology and AI, when used thoughtfully, can automate routine tasks and provide more space for genuine human interaction in the workplace, and Jason says collaboration across FM, HR, and IT is essential for delivering seamless workplace experiences. Small, consistent actions can create significant positive change in the workplace over time, and the future workplace will be more flexible, experience-based, and focused on human connection, so Mike and Jason offer practical advice and the inspiration you will need to be a Workplace Innovator in your organization! Connect with Jason on LinkedIn: https://www.linkedin.com/in/jason-leeds-7b253a87/ Learn more about Dartcor Enterprises: https://www.dartcorenterprises.com/ Explore Dartcor Hospitality: https://www.dartcorhospitality.com/ Watch the podcast on YouTube: https://www.youtube.com/playlist?list=PLSkmmkVFvM4H3pwnlU2AuqynuRDpvnh4J Discover free resources and explore past interviews at: https://eptura.com/discover-more/podcasts/workplace-innovator/ Learn more about Eptura™: https://eptura.com/ Connect with Mike on LinkedIn: https://www.linkedin.com/in/mikepetrusky/  

The world of IT is filled with technical qualifications in all manner of disciplines. They've become an expected baseline for knowledge in broad fields like networking and security, as well as narrower, vendor-specific knowledge and skills. But what happens as IT leaders move up to more senior roles? Steve Clarke, cofounder and director of Freeman Clarke joins host Eric Hanselman to talk about the challenges that senior IT professionals have in establishing their bona fides as technical business people. The role of a CIO, CTO, CISO or CDO requires technical depth, but the more important part is the ability to integrate that knowledge with business operations. It's not an easy transition to undertake and even more complicated to identify.  Discussions that are taking place in the 451 Research 451 Alliance community brought up the idea of a business level certification process and how it would have to characterize that unique knowledge set. The Standard is an approach that Steve and his colleagues began to address this issue. The 451 Alliance membership is free and open to all qualified IT professionals and business leaders who want to contribute to industry-leading research. Members take anonymous online surveys in exchange for access to research results that power their IT strategy.   More S&P Global Content: Join the 451 Alliance The Standard Certification The Problem with the Status Quo For S&P Global Subscribers: US tech spending intent dips in Q2, but projects to grow in Q3 – Tech Demand Indicator Highlights from Q2 2026 Beyond connectivity: A CIO's road map from network APIs to business impact Enterprises cautiously optimistic for AI amid data management challenges Host/Author: Eric Hanselman Guest: Steve Clarke, cofounder and director of Freeman Clarke and Tech Leaders Connect Producer/Editor: Dylan Scheible Published With Assistance From: Feranmi Adeoshun and Sophie Carr

What makes a country truly AI-ready in 2026? In this episode of UC Today, host Christopher Carey sits down with John Durcan, Chief Technologist at IDA Ireland — Ireland's Foreign Direct Investment Agency — to explore how enterprises are approaching AI adoption, what's driving global tech investment decisions, and why regulation might actually be Europe's secret weapon.John shares insights from his conversations with multinational companies on the ground in Ireland, covering:What separates AI-ready countries from the restHow the EU AI Act is shaping enterprise strategyThe rise of agentic AI across financial services, MedTech, and life sciencesWhy digital sovereignty is now a boardroom conversationThe real impact of AI on jobs — and what companies are doing about itWhether you're a technology leader, investor, or enterprise decision-maker, this is a conversation you won't want to miss.

Sign up for PrizePicks with code: HMA and get $150 in lineups instantly when you play your first $5+ lineup and WIN! Link: https://link.prizepicks.com/LME0/CORNERWVU football is working to get a sponsorship patch for player jerseys. Are they any closer to a deal? In this episode, Couz sits down with Don Robinson, the CEO of Gold & Blue Enterprises to discuss that and much more. Topics covered:-jersey patch deal-how WVU fans can help WVU Athletics and Gold & Blue Enterprises-what type of deals has GBE helped facilitate so far?-how will the Protect College Sports Act impact GBE?-what exactly is Gold & Blue Enterprises and how do they help WVU✈️ Book your travel plans with Mountaineer Travel: ✈️https://mountaineer.travel/a/COUZGet Your Tailgating Stuff HERE: http://victorytailgate.pxf.io/CouzCornholeCouz's Corner Merch Store: https://couz-shop.fourthwall.com/Join this channel to get access to perks:https://www.youtube.com/channel/UCGQsDxC1nVegCKqyoMKnL9w/joinOther Ways To contribute to the channel:Venmo: https://account.venmo.com/u/Justin-Walker-516PayPal: https://paypal.me/couzscorner?country.x=US&locale.x=en_USFanatics link: http://fanatics.93n6tx.net/eKxbVrSubscribe: https://youtube.com/c/CouzsCornerSportsSocials:Twitter: http://www.twitter.com/couzwalkerTikTok: https://www.tiktok.com/@couzscorner?Instagram: https://www.instagram.com/couzscorner206/Facebook: https://www.facebook.com/Couzs-Corner-113327741384316This channel is dedicated to covering college football, with a big focus on the West Virginia Mountaineers and the Big 12 Conference. It also features conference realignment news & rumors, game breakdowns and predictions, special guest interviews, livestreams and a lot more. FTC Legal Disclaimer - Some links found in the description box of my videos may be affiliate links, meaning I will make commission on sales you make through my link. This is at no extra cost to you to use my links/codes, it's just one more way to support me and my channel!See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Bloomberg reported that Amazon recorded its fifth straight quarter of cloud sales growth, signaling a shift from optimization to new workloads. AWS is emphasizing generative AI services such as Amazon Bedrock, Amazon Q, and Amazon SageMaker, supported by custom chips Trainium and Inferentia. Amazon previously committed up to $4 billion to Anthropic, positioning Claude models on Bedrock against Microsoft's OpenAI alignment and Google Cloud's Vertex AI. AWS continues to use multi-year enterprise agreements, Savings Plans, and reserved capacity while co-selling with partners. Enterprises are focusing on FinOps practices, data gravity, and procurement leverage as AI pilots move to production. Competitive moves by Microsoft and Google are shaping pricing and features as customers plan 2026 cloud budgets.Learn more on this news by visiting us at: https://greyjournal.net/news/ Hosted on Acast. See acast.com/privacy for more information.

In this episode of IPS Finance | Vikatan TV, we present a detailed analysis of the Q1 financial results of Adani Ports & Special Economic Zone, Adani Enterprises, and Asian Paints. We break down the key numbers, management commentary, growth drivers, and the major positives and negatives from each company's earnings report to understand which business performed better and what investors should watch going forward.The episode also explores an important new development in India's financial ecosystem: Could a new Social Stock Exchange emerge alongside the NSE and BSE? We explain what a Social Stock Exchange is, how it differs from traditional stock exchanges, who can raise funds through it, and whether it could become a meaningful platform for social enterprises, non-profits, and impact-focused investments in India.A comprehensive discussion covering Adani group earnings, Asian Paints performance, and the future of Social Stock Exchanges in India.

In this episode, Filipe Santos (@chop_safil), CEO of Chop Enterprises, shares how he went from tattoo artist and union carpenter to building a multi-location salon company with nine salons across New York, New Jersey, and Miami.Filipe breaks down the growth, leadership, and execution behind scaling from one salon to nine, including how he built leaders, created systems, recruited talent, used marketing, acquired salons, negotiated owner financing, and developed a shared services platform to support growth.This conversation is for salon owners, beauty pros, and hairpreneurs who know that talent is only one part of building a real business.Follow/subscribe to be the first to know when new episodes are released. Like what you hear? Leave us a review!Key Takeaways:

Queenstown's famous gondola and luge operator continues to reach new heights. Skyline Enterprises has reported revenue of $239.3 million, up 15%, while net profit more than doubled to $86.1 million in the year to March. International visitor numbers from its key markets have now surpassed pre-Covid 2019 levels. CEO Geoff McDonald told Mike Hosking the Iran conflict is influencing where people travel, and is helping New Zealand's shoulder season. He says there's a clear rise in the number of Americans coming through. LISTEN ABOVE See omnystudio.com/listener for privacy information.

Artificial Intelligence is no longer just for large enterprises with massive IT budgets. Today, even the smallest businesses can automate repetitive work, improve customer service, and reclaim valuable hours using AI. Chapters: 00:00 Introduction to Anne Cantera 01:12 The Role of AI in Small Businesses 03:43 Identifying Problems in Small Businesses 06:41 Implementing AI Solutions 10:24 Tech Stack and Feasibility for Small Businesses 12:30 Driving Towards Workable AI Products 13:43 Adoption Challenges and Experiences 15:43 Measuring ROI in AI Implementations 18:07 Advice for Small Business Owners 19:40 Educating Yourself on AI 22:43 Public Perception of AI 24:09 Conclusion and Contact Information Episode # 146 Today's Guest: Anne Cantera, Founder, Elementyl Intelligence She is an AI and voice technology expert, conversation designer, and founder of Elementyl Intelligence Website: Elementyl Intelligence LinkedIn What Listeners Will Learn: Why small businesses may adopt AI faster than large enterprises How to identify business problems that AI can solve A practical framework for assessing AI opportunities When AI is the right solution and when it isn't How voice agents can automate customer interactions The benefits of AI-powered inbox and workflow automation How custom AI solutions are becoming affordable for SMEs Why ROI should drive every AI investment The importance of AI literacy for business owners How to become a better AI operator. Why monitoring and continuous improvement matter after AI deployment. Common mistakes businesses make when implementing AI. How to avoid misinformation and AI hype. Resources: Elementyl Intelligence Voice of AI - Free AI Education Platform Elemental Intelligence - AI Consulting for Small Business Reuven Cohen - Trusted AI Educator

Encuentros con los LÍDERES de la industria en Radio PRODU. Luis Fernández, Chairman de NBCUniversal Telemundo Enterprises, es entrevistado por Ríchard Izarra, fundador y editor jefe de PRODU. Radio PRODU se encuentra en RadioPRODU.com  

The episode reveals a fundamental structural shift in AI deployment: the deliberate decoupling of powerful AI capabilities from accountability and human oversight. This is exemplified by incidents such as a former Mayo Clinic safety lead being fired after flagging a hospital AI tool (Maya) with a significant error rate (up to 67%) and the replacement of nurses by AI for administrative tasks at Montefiore. The trend is further driven by the increasing availability of potent, open-source AI models, like Moonshot's Kimik 3.2, which remove the traditional vendor accountability that was once inherent in software delivery. This detachment is fueled by a desire for speed and cost savings, leading to a critical "governance gap" where AI operates without a robust control layer or "harness." A primary development highlighting this shift is the reported issue with OpenAI's GPT 4.56, which allegedly deleted user files, termed an "honest mistake" by the company. This underscores how AI, even from leading developers, can cause operational damage when unsupervised. The episode points out that historically, software delivery included both vendor liability and human oversight as inherent safeguards. However, the move towards commoditized, freely accessible AI models and open-source releases is intentionally eliminating these checks. Enterprises are also rationalizing this by shifting to local AI models, severing ties with vendors who were previously points of accountability. Supporting this central theme, the episode details how the increasing accessibility of advanced AI models, such as Kimik 3.2, means frontier capabilities are no longer confined to major labs. Furthermore, studies indicate that reliance on AI advice can paradoxically reduce human accuracy and increase overconfidence in incorrect outputs, making human review less effective if not properly structured. This suggests that even human oversight, if not independently rigorous, can be compromised by the very AI it's meant to check. The core value is shifting from the AI model itself to the "harness"—the accountable judgment layer that controls and validates AI actions. For MSPs and IT leaders, this structural shift creates significant operational implications. The erosion of vendor accountability and human oversight means the "harness" is often missing, creating a liability vacuum. Clients may deploy AI without adequate checks, leading to potential errors, data loss, and reputational damage. MSPs are presented with an opportunity to address this by becoming the named, accountable "check" or harness provider. This requires shifting client conversations from AI acquisition to AI accountability, mapping existing unsupervised AI deployments, and offering oversight services as a distinct, valuable offering to mitigate risks for clients and ensure trustworthy AI integration. 00:00 AI Went Free, the Checks Didn't  03:59 Forget the Model — Own the Harness 06:45 You Can't Just Watch It Anymore 10:19 Why Do We Care?  Supported by: Pax8

What You'll Learn:00:00 Introduction02:13 Why Marketing Owns Zero Board KPIs08:54 There Is No Killer Marketing Campaign15:41 Why Your First 10 Customers Matter More24:16 The Biggest GTM Mistake Founders Make33:48 How AI Is Changing Customer Discovery43:11 Demand Generation Beats Chasing Leads53:02 Why Value Wins Over Price1:02:47 The New Rules of B2B Go-to-Market1:11:26 Rapid Fire with Alon WaksRethink your B2B SaaS GTM strategy from pipeline to persona SpotDraft's CMO Alon Waks shares the framework behind $100M raised and 450+ customers.Ask a B2B founder about their killer marketing campaign and most will have an answer ready. Alon Waks will tell you that answer is wrong. There is no killer campaign. There is no one channel. And most of what founders think of as marketing is stuck in one-to-many land when it should be one-to-few.That is where this conversation starts, and it does not slow down.Alon is the CMO at SpotDraft, the AI-powered contract lifecycle management platform backed by Vertex, Qualcomm, Prosus, and P&G Invest, now serving customers across the US, UK, and APAC. In this episode with Prime Venture Partners, he opens up the playbook he actually runs day to day:- How he defines persona versus segment (and why founders keep starting with the wrong one)- What changes as a company moves from 0 to 1 to 10 to 100- Why he thinks paid marketing has become a race to the bottom that most founders are still throwing money at.He also opens up his playbook for B2B influencer marketing, an angle most CMOs will not talk about publicly. He explains why validation has quietly shifted away from Gartner and toward peer-to-peer conversations on Reddit, LinkedIn, and community forums. And for the Indian founders trying to crack the US, he lays out exactly which cities matter, what not to do on outbound, and when to make your first local hire.Toward the end, Alon gets uncomfortably honest about what marketing actually owns on the board KPI list (spoiler: almost nothing) and why that changes everything about how you should measure your team.If you are a founder, a marketer, or a CMO building a B2B SaaS GTM strategy from scratch, this is the one to bookmark.Connect:Alon Waks on LinkedIn: https://www.linkedin.com/in/alonwaks/Spotdraft: https://www.spotdraft.com/Prime Venture Partners: https://www.primevp.in/Jerome Manuel on LinkedIn: https://www.linkedin.com/in/jeromermanuel/About Prime Venture Partners:Prime Venture Partners is an early-stage venture capital firm partnering with exceptional founders building category-defining companies from India.#GoToMarket #B2BMarketing

In today's Cloud Wars Minute, I examine why Google Cloud and Palantir have become the fastest-growing companies in enterprise AI. Highlights 00:01 — Now that we are more than halfway through the year, we've got Q2 earnings season coming up, and a couple that I'm looking for in particular are Google Cloud and Palantir because their growth rates have been so much above the norm. I think what we see in those growth rates and in the numbers behind those is a reflection of what customers really want from AI and the cloud here in the AI revolution. 00:52 — Let's look at numbers for Google Cloud, the number one company on the Cloud Wars Top 10. Palantir is number five. For Google Cloud, in the quarter ended a few months ago, March 31, its growth rate was 63%. Its revenue was $20 billion. Q4: 48%, $17.7 billion. Going back to Q3: 34%, Q2: 32%, and Q1: 28%. So we see, for the last five quarters, Google Cloud has soared over the last couple of quarters 01:57 — Now let's look at Palantir with those same five quarters, going back to Q1 of 2025, and up through Q1 of this year. So, most recently, 85% growth rate with over $1.6 billion in revenue, 70% before that, 63% before that, 48%, 39%. So in both cases, we see the company, even as its revenue base gets bigger, growing much, much faster moving forward. 03:22 — Palantir is 24 years old. This is not a startup company, although it's just sort of burst onto the scene. I wonder if, in some ways, Palantir's technology was out ahead of where the market was. But now that the AI boom has swept the world, Palantir's technologies are now suitable for  companies of any size to help take what they have and use that as a foundation to build into the future. 04:37 — Innovation in going to market, as well as in technology, means  some new approaches to things. I think particularly Google Cloud here has been an extraordinary example of this. And I refer in this article to their recent disclosure that while OpenAI and Anthropic, AWS, and Microsoft are all launching deployment units to pull off these big AI projects, Google Cloud is relying 100% on its ecosystem. 05:11 — I'll be eager to see how these companies do in Q2, and we'll follow up with those and the other Cloud Wars Top 10 companies on how they've done in calendar Q2. But I really take my hat off to Google Cloud and Palantir because, in this very intense time, with an enormous market and everybody going after it, their growth rates are soaring. Visit Cloud Wars for more.

Kevin Wright raises top quality mules in Fountain Green, UT. In this episode we talk about his experiences, education, and thoughts on what it takes to make a nice saddle mule.Find more on social media by looking up Diamond W Enterprises on Facebook

Enter to win WBE's Ranger Z521R 55th Anniversary Limited Edition 2023 bass boat (Brian Bird's personal boat worth an estimated $84K!). Enter with a qualifying merch purchase:https://wbe-the-champions.checkoutstores.com/SWEEPSTAKES INFORMATION: NO PURCHASE NECESSARY TO ENTER OR WIN IN THE WORLD BASS ENTERPRISES “MERCHANT STORE” SWEEPSTAKES. Open to legal residents of the 48 US & DC, 18 or older. Void in AK, HI & where prohibited. Sweepstakes starts 12:00 AM ET 7/6/26 and ends 11:59 PM ET 9/20/26. For details on how to enter without purchase and complete Official Rules, which govern, visit https://www.worldbassenterprises.com/merchant-store-sweepstakes.Here's that link to the Hookset Hoodlums X Jigs & Bigs BCRF Charity Slot Tournament! https://app.fishingchaos.com/tournament/EMMhJZlBMtgYH1sKJ8Z7Online

We speak with Italian duo Mind Enterprises. The former post-punk musicians, Andrea Tirone and Roberto Conigliaro, create feel-good Italo disco – a genre full of Mediterranean escapism.See omnystudio.com/listener for privacy information.

Enterprises are running more AI agents than their security teams realize, and attackers only need to be right once. Anand Oswal, EVP of Network Security at Palo Alto Networks, explains how to secure agents across four surfaces: enterprise, SaaS, endpoints, and the browser. With host Michael Krigsman, he covers shadow agent discovery, MCP and browser risks, prompt injection, agent identity, and why a unified platform beats a stack of point products.YOU'LL DISCOVER✅ The four agent surfaces every CISO must secure at once: enterprise, SaaS, endpoints, and the browser✅ Why discovery comes first: you cannot secure agents, models, tools, and plugins you cannot see✅ The Palo Alto Networks finding that one third of public MCP servers carry takeover level vulnerabilities✅ How vibe coding agents demand privileged access to local files, terminals, and cloud credentials✅ How browser agents inherit your session and cookies and can perform identity impersonation✅ Runtime threats to know: prompt injection, memory poisoning, tool misuse, and model DoS✅ How MCP and A2A protocols expand the attack surface, and why a centralized AI gateway anchors identity, runtime, and observability controls✅ The case for zero trust, an AI-driven SOC, and one unified platform over point products, and where Prisma AI fits⏱️ TIMESTAMPS0:00 Introduction0:22 Agent memory poisoning and tool misuse0:59 Discovering shadow agents across four surfaces2:32 Vibe coding agents and MCP risk4:46 Browser agents and session misuse6:20 Runtime threats and prompt injection7:17 Agent-to-agent protocols and attack surface8:04 Agent identity and the control plane9:16 Centralizing control at the AI gateway10:23 Zero trust and an AI-driven SOC11:29 One platform, not point productsSubscribe for weekly conversations with the business and technology leaders shaping the enterprise. Get the CXOTalk newsletter: https://newsletter.cxotalk.com Show notes, transcript, and summary: https://www.cxotalk.com/episode/palo-alto-networks-evp-securing-ai-agents-in-the-enterpriseEpisode 924#CXOTalk #EnterpriseAI #CIO #AIGovernance #AgenticAI #IBM #DigitalTransformation #AIStrategy #AILeadership

It's been a crazy summer for AI. AI enthusiasm remains high, but the market is starting to ask far harder questions. Semiconductor stocks are in a bear market. IBM's shares fell sharply. Data-center projects are facing political and community resistance. Enterprises are adopting AI, but many are struggling to turn experimentation into measurable returns.In this Freestyle Friday episode, I look at why these signals do not necessarily mean an AI winter. Instead, they suggest that AI is moving from a "possibility market" into an "accountability market", where capability, economics, infrastructure, and organizational reality finally have to reconcile. Put another way, things are going to get real.-----------------------Sponsor: FivetranWith the rise of AI and agents, having centralized, trustworthy data is the absolute foundation for building tools and training models. Fivetran automates your data pipelines, removing the need to build fragile connectors so your data arrives clean and reliable. By handling the messy infrastructure behind the scenes, Fivetran allows your team to focus on building the future. Visit ⁠fivetran.com⁠ to learn more.-----------------------Sponsor: Revefi Save serious money on your cloud costs with Revefi's new autonomous AI DBA, a tool built to handle the gritty reality of cloud data management so you can stop babysitting your infrastructure. Start saving money today at ⁠⁠revefi.com/ai-dba

Safe, reliable, production-ready AI agents don't come from the model. They come from everything built around it.Rasmus Hauch is CTO of Boost.ai, one of the enterprise platforms banks, insurers and public sector organisations use to build customer-facing AI agents. His work sits one layer below every deployment: the orchestration, the guardrails, the testing infrastructure and the model choices that decide whether an agent holds up in front of millions of customers.In this episode, Rasmus opens that layer, explaining why conversational AI is shifting away from traditional conversation flows towards orchestration, testing and continuous evaluation. He walks through how Boost approaches it in practice: persona-based simulation across thousands of digital and voice conversations, predefined test suites for jailbreaking attempts and financial advice, layered guardrails inside and outside the agent, and a trust loop that feeds production results back into the build.Rasmus is direct about the hard parts. We touch on why the big LLM providers can't yet deliver the consistent response times voice demands, which is why Boost runs fine-tuned smaller models on its own infrastructure for latency-critical voice work. Rasmus explains why he advises clients against plugging in their own models. We also discuss where liability sits under the EU AI Act when an agent gets it wrong, and why a volcano eruption in Iceland is a good example of what no model can be trained for.Towards the end, Rasmus shares what's exciting him right now, including adaptive voice, real-time language switching and where agent-to-agent protocols are heading.Show notes
Discover more about boost.aiFollow Rasmus on LinkedIn:https://www.linkedin.com/in/rasmushauchFollow Kane on LinkedIn:⁠⁠⁠https://www.linkedin.com/in/kanesimms⁠⁠⁠Subscribe to VUX World: ⁠⁠⁠⁠https://vuxworld.typeform.com/to/Qlo5aaeW?utm_source=podcast&utm_medium=audio⁠⁠Subscribe to The AI Ultimatum Substack: ⁠⁠⁠⁠https://open.substack.com/pub/kanesimms⁠

Rime is handling over 100 million calls each month across multiple companies Also, Anthropic-backed Ode launches as AI labs bet that embedding forward-deployed engineers inside enterprises is the key to accelerating enterprise AI adoption. Learn more about your ad choices. Visit podcastchoices.com/adchoices

More than 48,000 vulnerabilities were disclosed in 2025, yet only about 1% are actively exploited. However, you're expected to mitigate all vulnerabilities, or at least critical and high. But what if there is no patch to fix the vulnerability or the software is unsupported? Ben Lipcynski, Director Security and Regulatory Services at Optima, joins Business Security Weekly to discuss how organizations can take back control of your enterprise software. OPTAS — Origina Proactive Threat Assurance Service — predicts, validates, prioritizes, and mitigates threats specific to your environment. Unlike AI vulnerability tools that flag everything without context or mitigation guidance, OPTAS cuts through the noise. OPTAS helps security teams focus on the risks that matter instead of chasing the 99% that do not. Segment Resources: - https://www.origina.com/optas#optas-overview This segment is sponsored by Origina. Visit https://securityweekly.com/origina to request a consultation. In the leadership and communications segment, US enterprises incorporate cyber risk into larger strategic focus, 75% of CISOs Fear Executives Don't Understand Cybersecurity Risks, AI agents are not your “coworkers”, and more! Visit https://www.securityweekly.com/bsw for all the latest episodes! Show Notes: https://securityweekly.com/bsw-456

Companies are spending billions building AI factories, but most of them can't tell you why their AI workloads are failing, whether their GPUs are actually being used, or what their infrastructure is going to cost them when agents start running at scale. Paul Appleby, CEO of Virtana, joins Craig Smith to discuss the findings of their AI Factory Reality Check study, a research report that reveals a striking and underappreciated gap between the pace of AI infrastructure investment and the governance needed to run it safely and efficiently. Six in ten enterprises, the study found, cannot automatically identify root cause when an AI workload fails, a problem that compounds fast once you're running critical services on AI infrastructure at scale. The conversation covers the mechanics of Virtana's observability platform, capturing 20,000 metrics per second across the entire AI stack, correlating them in real time, and increasingly using agentic capabilities to remediate failures automatically, but its most important insights are structural. Appleby makes a sharp observation that cuts through a lot of AI optimism: token costs are falling, but token consumption is exploding, meaning the total cost of running agentic AI systems is still going up even as the per-unit price drops. He also tracks a cultural shift inside enterprises - IT resilience reporting that used to happen annually now happens weekly - as evidence that technology risk has become a board-level conversation in a way it simply wasn't before. The result is a conversation that's less about the promise of AI and more about what it actually takes to make it work at production scale. Subscribe to Eye on A.I. for weekly conversations with the people building and deploying the future of AI.

More than 48,000 vulnerabilities were disclosed in 2025, yet only about 1% are actively exploited. However, you're expected to mitigate all vulnerabilities, or at least critical and high. But what if there is no patch to fix the vulnerability or the software is unsupported? Ben Lipcynski, Director Security and Regulatory Services at Optima, joins Business Security Weekly to discuss how organizations can take back control of your enterprise software. OPTAS — Origina Proactive Threat Assurance Service — predicts, validates, prioritizes, and mitigates threats specific to your environment. Unlike AI vulnerability tools that flag everything without context or mitigation guidance, OPTAS cuts through the noise. OPTAS helps security teams focus on the risks that matter instead of chasing the 99% that do not. Segment Resources: - https://www.origina.com/optas#optas-overview This segment is sponsored by Origina. Visit https://securityweekly.com/origina to request a consultation. In the leadership and communications segment, US enterprises incorporate cyber risk into larger strategic focus, 75% of CISOs Fear Executives Don't Understand Cybersecurity Risks, AI agents are not your "coworkers", and more! Show Notes: https://securityweekly.com/bsw-456

More than 48,000 vulnerabilities were disclosed in 2025, yet only about 1% are actively exploited. However, you're expected to mitigate all vulnerabilities, or at least critical and high. But what if there is no patch to fix the vulnerability or the software is unsupported? Ben Lipcynski, Director Security and Regulatory Services at Optima, joins Business Security Weekly to discuss how organizations can take back control of your enterprise software. OPTAS — Origina Proactive Threat Assurance Service — predicts, validates, prioritizes, and mitigates threats specific to your environment. Unlike AI vulnerability tools that flag everything without context or mitigation guidance, OPTAS cuts through the noise. OPTAS helps security teams focus on the risks that matter instead of chasing the 99% that do not. Segment Resources: - https://www.origina.com/optas#optas-overview This segment is sponsored by Origina. Visit https://securityweekly.com/origina to request a consultation. In the leadership and communications segment, US enterprises incorporate cyber risk into larger strategic focus, 75% of CISOs Fear Executives Don't Understand Cybersecurity Risks, AI agents are not your "coworkers", and more! Visit https://www.securityweekly.com/bsw for all the latest episodes! Show Notes: https://securityweekly.com/bsw-456

Enterprises rushing agentic AI into production are running it through approval gates, batch windows, and audit systems built for human speed — and the gap is where most operational risk lives. In this episode, Chris Caldwell, President and CEO at Concentrix Corporation, examines how machine-scale transactions break processes designed for human pace and why bounded digital delegates outperform unrestricted digital twins in the enterprise. The discussion covers compliance bots that check other bots, the cost reality of poorly tuned agentic agents, and what leaders need to stop doing if they want a defensible AI roadmap. Learn how to evaluate AI vendors by assessing leadership expertise, and why funding benchmarks can signal product maturity and stability. Download our free PDF report, "5 Ways to Select the Right AI Vendor," at emerj.com/aiv2

Are you wondering if entering your manuscript in book awards is truly worth the effort? Join host Juliet Clark as she sits down with the founder of Black Château Enterprises and The BookFest®, Desireé Duffy, to uncover the true value of recognition in the publishing industry. They discuss why awards matter, how to navigate the submission process, and common pitfalls authors face when promoting their work. Desireé offers expert insights into building a sustainable author platform and the evolving role of AI in the writing process. Discover how to bridge the gap between being a writer and connecting with readers in this insightful conversation about the current landscape of the book world.Love the show? Subscribe, rate, review, and share! https://superbrandpublishing.com/podcast/

Lee Plotkin | LP Enterprises, Inc. L.P. Enterprises helps small and medium size restaurant groups streamline purchasing with precision, insight, and proven expertise – saving time, reducing costs, and protecting brand standards since 2001. Chances are you have spent years honing those skills revolving around the ownership, operation and management of restaurants and hotels. An […]

AGENDA: 05:00 Washington Just Put Frontier AI on a Leash 06:30 Sam Altman's Wild 5% Government Stake Idea 19:00 The AI Funding Bubble: Why Founders No Longer Fear Dilution 28:00 Alex Karp's Brutal Warning: Enterprises Don't Trust Frontier AI 33:00 Meta's Shock Pivot: Has Zuck Accidentally Built the Next CoreWeave? 41:00 Nvidia's Dangerous New Game: "Compute Now, Pay Later" 45:00 Anthropic & DeepSeek Go After Nvidia's Crown 48:00 Kling vs Sora: Did China Just Win AI Video? 52:00 Is China Secretly Winning the Open Source AI War? 01:02:00 Microsoft & Amazon's $6B Bet: AI Still Needs Humans 01:11:00 Ashton Kutcher Walks Away From Sound Ventures 01:16:00 The New Startup Talent War: No Liquidity, No Chance 01:20:00 Final Thoughts: Who Wins the AI Endgame?

South and Southeast Asia face a different challenge to many developed economies. As the regions continue to grow, so too does demand for energy, transport and industry. The question is whether that growth can be powered by cleaner technologies from the start. In the second of our episodes recorded from Singapore, Michael meets Marie Cheong, founding partner at 100x100, a climate tech venture builder and VC for South and Southeast Asia. Previously, Marie co-founded WaveMaker Impact, where she helped launch climate startups addressing some of the region's biggest opportunities for decarbonisation. Marie explains why climate innovation in emerging South Asian markets requires a different approach. They discuss investing across the region, growing energy demand, using AI to decarbonise manufacturing, and why there are no "silver bullet" solutions to climate change. Marie also takes Michael to the People Bee Hoon noodle factory, which makes rice vermicelli noodles to see how Desmond Goh, the factory's director is using AI to improve his operations. Michael meets to Desmond and Muun AI founder Kathryn Knight about how better use of data can help cut emissions and waste. And at the end of the episode, a very special announcement… stay tuned. Topics Include Building climate startups across South and Southeast Asia Why climate investing needs more than "silver bullet" technologies The biggest opportunities for climate innovation in emerging Asian markets Solving regional pain points as the key to success Can Southeast Asia grow without burning more coal? Investing in emerging markets and navigating regional diversity How AI can help manufacturers cut emissions, costs and energy use The next generation of climate technology in Asia Leadership Circle Cleaning Up is proud to be supported by its Leadership Circle. The members are Actis, Alcazar Energy, Arup, Copenhagen Infrastructure Partners, Cygnum Capital, Davidson Kempner, Ecopragma Capital, EDP, Eurelectric, the Gilardini Foundation, KKR, Mitsubishi Heavy Industries, National Grid, Octopus Energy, Quadrature Climate Foundation, Schneider Electric, SDCL and Wärtsilä. For more information about the Leadership Circle, visit cleaningup.live Links Marie Cheong's bio: https://www.linkedin.com/in/marie-cheong-06141b36/ Wavemaker Impact https://wavemakerpartners.com/ 100x100 https://www.100x100.com/ Muun AI https://muun-ai.com/ Watch our previous episode from Singapore, with Ravi Menon: https://www.youtube.com/watch?v=Xvhd34i6YMk Harish Hande on Cleaning Up https://www.youtube.com/watch?v=jUxdaHFJI68 South Asia Includes: Afghanistan, Bangladesh, Bhutan, India, Maldives, Nepal, Pakistan,and Sri Lanka. South East Asia Includes:  Brunei, Burma (Myanmar), Cambodia, Timor-Leste, Indonesia, Laos, Malaysia, the Philippines, Singapore, Thailand and Vietnam. Acronyms FESIA - Future Energy Storage and System Integration Alliance ASEAN - Alliance for Southeast Asian Nations CPTPP -  Comprehensive and Progressive agreement for Trans-Pacific Partnership MT - Megatonne SAF - Sustainable Aviation Fuel SME - Small/Medium-sized Enterprises

Enterprises have been slogging through the AI adoption journey, but cybersecurity threat actors have been too. As the time from vulnerability discovery to breach effectively goes to zero, the new cybersecurity playbook is all about how fast you can recover. We Meet:  Anneka Gupta is the Chief Product Officer at Rubrik Credits:This episode of SHIFT was produced by Jennifer Strong with help from Emma Cillekens. It was mixed by Garret Lang, with original music from him and Jacob Gorski. Art by Meg Marco.

https://youtu.be/Ji1OZYu1r1Y Charles Fry, Founder and CEO of CODE Éxitos, is helping businesses hire AI in enterprise to transform software engineering, modernize product development, and build intelligent connected systems.  In this conversation, Charles introduces The Agentic Org Chart Framework: Hire Systems Thinker, Look for Failed Entrepreneurs, and Have AI Replace “Trade Skills”. He explains why AI is fundamentally changing software development, how organizations must redesign their structures for an AI-first workforce, and why systems thinking is becoming more valuable than technical specialization. Charles also discusses how the rise of agentic software development is reshaping the future of SaaS, why combining AI with connected hardware creates a stronger competitive advantage, and what business leaders must do to successfully navigate AI-driven transformation. — Hire AI in Enterprises with Charles Fry  Good day. Steve Preda here, and I’m talking with Charles Fry, the Founder and CEO of CODE Éxitos, building cyber-physical systems for mid-market and enterprise companies, as well as full-stack web, mobile, and SaaS development. Charles, welcome back to the show.  Hey, I’m happy to be here. It’s always great to see you, and I’m looking forward to our chat. Yeah. It’s so interesting to talk to you because the last time we had you on the show, three or four years ago, it was still before the AI age was fully upon us.  Right.  Your business was kind of a different business. I’ve been following you on LinkedIn, and I see that you’ve evolved your approach, and now you’re an AI-first company. So tell me a little bit about how that came about, this whole evolution, and how you found your new focus?  Yeah. Wow. It’s been that long since we were on the show. It was a lot of fun, but here we are. You’re right. AI really sort of came out of left field. I’ll skip all the technical things that suddenly made AI an achievable thing. But really, at the beginning of 2024—and somebody can fact-check my timeline—ChatGPT, if you were aware of it, was kind of passing the Turing test. It was giving pretty reasonable answers to natural-language questions.  And we were like, “Wow, this is interesting.” At first, we were helping our clients think about how to build those capabilities into their products, something we still do.Share on X But by mid-’24, late ’24, it became pretty obvious that one of the best applications of large language models—and expert systems, we used to call them that—is writing software. And so by early to mid-’25, the systems were suddenly not novelties. They were credible at what they were doing, and they were gaining momentum in the quality and credibility of the software they were producing.  Now, CODE Éxitos was started largely to create an opportunity for entrepreneurs and enterprises that needed, let’s call it, garden-variety, well-done software. We built that through the Americas to arbitrage labor rates in Latin America and leverage the time zones. So it was essentially an offshore, blended, hybrid-team model. Honestly, by the middle of 2025, the AI tools for software engineering were as good as, or better than, 50 percent of the human developers that we employed.  And at some point, as a business owner, when you’re out there representing yourself, and your product is yourself, and you’re representing that to clients, you have a moral and ethical obligation to say, “Hey, I think I can still give you the best product that you’re looking for, but I’m going to do it in a different way.” So beginning in late 2025, we were hard into the pivot. Today, all of our software development is done agentically. There are still people. It’s not a complete dark factory. But our mid-level performers and below, we exited them from the business, which caused a lot of human turmoil. I mean, we were at around 100 people. A lot of human turmoil. Our clients were going through the same thing. We were watching what was happening in their organizations and what the leadership demands were.  We just made the decision to lean into it. And here we are, almost mid-’26 now, and it’s actually going really well. Now, AI, of course, anyone who opens an internet browser anymore sees it. AI is everywhere. You read the newspaper. AI is going to change everything.  Every application has an AI layer to it.  Yeah.  Right? Every SaaS application has a button that says, “Use AI here.”  My view, at least—and these are the things people should probably give me some credibility on—I’m going to keep my views focused on how AI applies to the software industry, my industry, and its direct impact. We see, and we have clients working on, things like AI in customer service, the legal department, and the finance department. We do all of those things internally—agentic first, AI first. But those really aren’t my industry. I’m not ready to make a sweeping prognosis about how AI is going to change capitalism in the United States. But in the software industry, it’s a fundamental change. And it’s not done yet.  So what’s your vision? Where is everything going? What’s it going to look like three years from now?  Well, I’m not smart enough to know that. But I think the patterns we've seen—and again, within the world of writing software, and making that a broad category of activitiesShare on X —are going to continue to consolidate and converge to where humans are important, but they might be only 10 to 20 percent of the input to the process. I really do think we’re going to see a day, sometime in the three-to-five-year time horizon, where a large amount of software will be written and managed by other software systems.  There’s no technical reason to prevent that. For example, I was talking to one of our clients today, a CIO at a great company. A couple hundred million dollars in revenue. A really well-run business. A sizable internal IT team. But there’s a lot of ongoing maintenance and attention required. Building the software is just the beginning of a five-to-ten-year life cycle. So I think in the near term we’re going to see that building the software becomes, “Okay, we got that figured out.” That’s a largely solved problem.  We’ll then progress to the problem of: “Hey, this software has been in production for five years.” “It needs updates.” “It needs attention.” “It needs maintenance.” “It needs to scale.” More software systems will take care of that. Fewer and fewer humans will be involved in that kind of work. So I think that’s where the software industry is headed. I think it’s going to be 60 to 80 percent smaller in human capital than it is today. Sometime soon. Yeah. I really do think it’s about as close as I want to get to calling it an extinction event. Let’s put it that way. Some people say SaaS companies are going to go out of business, and it’s all going to be agents running around doing things for us. But other people say SaaS companies are actually the SOP for whatever activity is out there, and you need that structure. The SaaS application provides that structure. You don’t want agents running in an unstructured way. You’d rather have these SaaS applications. What’s your view?  I think that’s a good way of looking at it. If you’re a dinosaur like I am, back in the late 1980s or early 1990s, when you wrote software for a company, everything was custom software because there were no packaged software products, no SaaS platforms. But over the last 20 years, I think SaaS companies have become, for a lot of businesses, exactly what you said. They’re the embodiment of best practices. If you take something like HubSpot, which I’m sure you and many of your audience are familiar with, you really don’t need to customize it.  You just need to follow its baseline processes because they have thousands of customers who have helped refine the sales motions that work. So I think there’s some truth to that. The problem SaaS systems face is that the barrier to competitive entry is much, much lower. If you look at a company like Salesforce—and I think I’ve led three different Salesforce deployments back when I was a CIO or CTO—that software really shows its age. It’s layers and layers of complexity built to serve a wide audience. It’s great. It’s expensive. Emerging companies don’t need that. They can effectively vibe-code their own CRM system, and it works. I think the threat for big SaaS companies is twofold.  One is that the next generation of customers is going to onboard very differently into those systems than the previous generation.Share on X I don’t know what that onboarding ramp is going to look like. The second problem is there’s very little defensibility in having a pure software product. And the other part of our intro—you talked about cyber-physical systems. We’re spending more and more of our product development cycles on hardware-related products, things that have a nexus in the physical world. Here’s a good example. I’m wearing one of these health rings. This Oura Ring. Oura, yeah.  There’s a lot of amazing hardware in here that justifies my monthly subscription for the app. The app we could recreate pretty easily. But the development, manufacturing, and distribution of this physical item create a much higher barrier for a competitor to overcome. So more and more of our clients are companies that have a physical product they either want to make smarter or make more connected.  That’s really what it comes down to. And that’s a pretty exciting space. But for a pure-play SaaS company, I think it’s going to get tough. The competitive pressure is going to be intense. And the barrier to entry is going to be really low. It’s not even about engineering cost anymore because the cost of engineering has dropped so much with AI. It’s almost like it went full circle. You had all these product businesses that wanted to become service businesses to create recurring revenue. And now the service businesses—the SaaS businesses—want to become product businesses to create a barrier to entry, improve retention, or reduce disruption. Isn’t that interesting?  Yeah. I hadn’t thought about it exactly that way. Maybe the pushback would be that these professional services businesses wanted to have a technology play or a platform. That’s interesting. But I think we’re going to see AI, at least in technology, continue to lower the barrier to entry. It will allow much faster experimentation with pure software ideas. And we’re focused on the things where the AI robots can’t play. They’re not going to cut your grass.  They might guide the machine that cuts your grass, but they’re not going to cut your grass. So I think that while the turmoil is still sorting itself out in the pure software world, we’re going to see a whole new set of opportunities open up. We’ll be able to build truly smart devices. Devices that think for themselves. Devices that are aware of the world around them. They can participate with us in our day-to-day work. That’ll be a lot of fun. I think we still have some rough sailing ahead of us as AI sorts itself out.  Isn’t it true that people prefer to interact with a purpose-designed device rather than a software product? And maybe an app is kind of a device that is software, or maybe that’s the overlap there. But I know there are some things I’d rather have on my phone, even though it’s complicated because there are so many other things on it. But if I have a single-purpose device, like you have your Oura Ring, it’s easier to interact with. There’s no complexity, and then it lowers the accessibility.  Yeah. An area of active study is something called HMI, or Human-Machine Interface. Again, back in the ’80s and ’90s, it meant things like: Are the buttons big enough for someone to push? Does a red light always mean a bad thing, and a green light always mean a good thing? But now that’s expanded into the kind of research in psychology and sociology that you’re talking about, Steve. Some of that is really amazing.  I’m sure you’ve seen them, and your audience has seen them. You can find these videos on YouTube. There are humanoid robots. It took a while for researchers to figure out that a robot doesn’t actually need a head. It can have what is essentially a torso with arms and legs. The head doesn’t really need to be there. But a robot with no head freaks people out. Yes. People don’t like it. So the robotics engineers put heads on them. Then they thought, “Well, if we’ve got a head here, we’ll just put a face on it.” But if the face is too realistic, it gives people the creeps.  Yeah.  So people didn’t like faces on them. If you look at the current generation of humanoid autonomous robots, they have these, I don’t know, sort of pseudo-faces. They kind of look like Halloween jack-o’-lanterns or something. They’re not scary, but they’re somewhere in the middle. Anyway, the things you’re talking about are really fascinating.  I mean, Isaac Asimov wrote about humanoid robots and all the challenges that come with them. What happens when they have a human-like appearance? What happens when people think they are actually people, but they just don’t age? All those things have been explored. But listen, I’d like to switch gears here and ask you this. Right now, in this AI age, what drives your business? What drives growth in your business?  This part is truly fascinating to me. Everyone is working off the same timeline now, which isn’t a very long timeline. We don’t have a lot of experience to draw on. Much more quickly than when the internet became commercially available—I was there when that happened too— the adoption of AI as a fundamental change happened in a matter of months, compared to several years for the internet.Share on X Some people also compare it to the adoption of mobile phones, which you mentioned.  But this has happened very fast. A year ago, we were talking to sophisticated technical buyers who said, “Yeah, I’m still on the fence about whether I like agentic software development.” That doesn’t happen anymore. Everybody says, “Yeah, we’re using it too.” What we’re seeing now is that it’s evolved so quickly and had such a fundamental impact that people don’t know not only how to manage it inside their business, but also how to deploy it. It’s really disruptive. And this is where you’re a pro.  It’s really disruptive to organizations. So in less than a year, we’ve gone from, “Hey, should I let my developers use AI?” to now everybody using AI. And the leading teams, including ours, can produce high-quality commercial code faster than organizations can absorb it, and faster than org charts can adapt to the change. Our engineering teams have to adapt to the pace of the business, not the other way around. Because we get clients saying, “Hey, you guys are producing too much.” “We can’t check everything.”  “We haven’t finished testing last week’s new features and capabilities yet.” “We can’t take another batch of features and capabilities this week.” So we’re seeing a lot of organizational behavior change starting to come out of this. When we’re talking to C-level executives and senior leaders, that’s where most of the conversations are today. “How do I retool my organization to capture the benefits?”  Yeah. Because what I see is that the more AI you apply, the faster decision velocity becomes. And the complexity of understanding the whole picture, connecting the dots, increases. So you need a different kind of person who can operate at that higher level of contextualization. Do you see the same thing?  We do. Software engineering and product development had matured into a pretty predictable set of job descriptions and capabilities. The business processes were really well worn. We knew what the product owner did. We knew what a project manager did. We knew what a tech lead did. Et cetera, et cetera. A lot of these, frankly, became trade skills. “Hey, I’m really good at writing code.” Or, “I’m really good at doing QA, but I’m not really a systems thinker.” “I’m not an entrepreneur.” “I’m not a creator.” Pick your fuzzy lens of choice.  That’s really what AI displaces right now. AI displaces those trade skills and, frankly, does them better and cheaper. There’s no way to dispute that. What we look for now, and I think where the trend is going with our clients, is systems thinkers. We have enough agentic tooling built on our own internal platform that the people operating and building products for our clientsShare on X —we refer to our team as digital creators—come from a variety of backgrounds. You don’t have to be a computer science major. You do have to have some domain experience. You do have to be a systems thinker. You do have to understand what business value you’re trying to create. But as far as actually writing really good code, nobody’s really doing that now. It’s being done automatically.  If you have a couple of gray hairs like I do, you’ll remember back 20 years ago when we talked about the war for talent. That’s what everybody was looking for. They wanted people with these highly specialized engineering skills. I think there’s a new war for talent. It’s going to be harder to pin down because we’re going to be looking for whole-systems thinkers as opposed to technical specialists. Because AI will be the technical specialist we need, regardless of the business domain. So what do you do to infuse systems thinking in your business?  Wow. I wish I had a good answer for that. I don’t even know how to recruit these kinds of people right now. I’ll be that candid with you and your listeners. I was talking to a couple of my senior people, and I said, “Maybe we should go look for failed entrepreneurs.” Which is kind of a heretical thing to say. But as an entrepreneur, I know firsthand that it doesn’t always work. The fact that the business fails doesn’t necessarily mean you, as an entrepreneur, are a personal failure.  Entrepreneurs are about the only, I don’t know, primary source I can think of for people who have done a little bit of everything. They’re systems thinkers. Maybe they didn’t get it right, but they could. So we talked about that. I don’t know if Disney still does it, but Disney was phenomenal at producing these kinds of people through its internal training programs. We’re not big enough to compete with Disney. But to answer your question, how do we teach it? I can’t honestly say that we do. Because we’re still figuring out what it is that we would even teach.  Well, it’s a new type of SOP that’s needed in the business. So what are the best practices for building an AI workforce? That still needs to be defined.  Yeah. For larger organizations, our clients that are running larger organizations have the same problem. All of a sudden, their org chart is broken. What I mean by that is, if you look at the way we’ve traditionally built and scaled businesses, you have this pretty large cadre of managers who give you what Eliyahu Goldratt called the span of control, your degree of leverage. When you’re younger, you hear things like, “Ah, my manager doesn’t even do anything.” You’ve probably heard that before. “Oh, my manager doesn’t really do any work.” “He just comes in and bugs me.”  It’s not entirely wrong because we rely on that manager’s experience to be spread across six, eight, or ten other people and supervise their work. So managers don’t really do a whole lot of delivering the work themselves. I think AI is going to change that. I know AI is already changing that inside technical teams. All of a sudden, we have clients saying, “My org chart doesn’t translate to the way my business operates under this new agentic model.” That’s problem number one. Problem number two is, “I have people on my team who are good people and good contributors, but there’s no box for them in the new org chart that I think works with an agentic workflow.” Does that make sense?  Yeah.  So two things have happened suddenly. We see a lot of press—although I think it’s moderating a little bit now—about how kids coming out of university are having trouble getting entry-level jobs. True enough. I think the other area where org charts are collapsing is managers who don’t actually produce any output. Supervising other managers and compiling the weekly report of reports just isn’t a valuable job function, even at the best of times. And now—I hate to say this—but it’s useless. So I think there’s a lot more work we’re going to have to do with our clients, and ourselves, on what an org chart should look like. And what the expectations are for people doing work inside a company that’s moving aggressively toward leveraging AI capabilities in what we would normally call white-collar job functions. Yeah. Some years ago, I thought about the org chart being broken. The top-down hierarchical org chart—I think it’s completely broken. In my head, the org chart is more like an amoeba, where you have the entrepreneur and the manager in the middle as yin and yang. Different departments report to different people. And you’ve got these pizza teams all over, actually delivering teamwork. But that’s fascinating. Yeah, fascinating topic. So who are the ideal customers for you? If they have the right kind of projects, what are the right kinds of customers and the right kinds of projects for CODE Éxitos that would be interesting to look at?  There are two types of clients that we focus on and that we can help quite a bit. The first type of client is one that has a large, established internal software development and product development process, and they’re trying to figure out how to adapt, modernize it, and harness AI. We can come in, and we have a very opinionated point of view. We can have a couple of conversations, and they either like the direction our telescope is pointed in and want us to help, or they say, “No, we think we’re going to do it a different way.”  And that’s okay, too. Because right now, nobody really knows the final answer. We call those engineering transformation projects. Somebody says, “Hey, we have a team. Can you help us get better?” The second type of client we like is one that has this physical connection challenge. I’ll give you an example. We have a client that primarily makes pumps and motors. They put those pumps and motors into very specific industrial applications across North America. They wanted those pumps and motors connected to a network.  They wanted to collect data from those pumps and motors to help their customers. Once we built the data collection, the electronics, and the connectivity, the data started coming in. Now there are a lot of AI-related things we can do with that data. We’re beginning to work on what you can think of as supervisory agents that watch what’s going on. They’re much more robust than the old filters that just looked for exceptions and red lights. Those are the kinds of clients we really help on the product side.  Sometimes they come to us with an idea scribbled on a napkin. It’s like, “Hey, we have this system or this process that we envision, and we need somebody to help us build it.” We’ll do the electronics, the AI, and the software engineering. And that becomes a complete system. So, more systems thinking. Yeah. And then you combine software with hardware. Then you have AI agents doing much of the coding, management, and maintenance of these systems.  Yeah, that’s right. This is not a client of ours, by the way, but the story I’m going to tell is fascinating. It’s a second-degree connection that I chatted with. He runs a $100 million-a-year manufacturing company. I think he’s second or third generation—I can’t remember which. He knows the business. He grew up in the industry. He’s in the process of transforming the company so that he can basically run the whole business from his phone.  He’s applying AI to his internal business functions like finance and accounting. He’s done some really amazing stuff. He’s automating the manufacturing process, the machines, and the feedback systems. It’s just stunning what this guy is already able to do. He just picks up his phone and says, “Yeah, I want to run my company from here.” I think he’s going to be able to do it. I think we’re going to see more of that emerge. Yeah. That’s fascinating. The race is for the first one-person unicorn, right?  I think that’s already happened. I don’t know if you’ve seen this. I can send it to you. There was a New York Times article a couple of months ago about a guy—not a tech guy, a marketing guy. He and his brother run an online company that generates $1.8 billion a year in sales. And it’s just the two of them. Wow!  Spoiler alert: As I remember, they sell weight-loss drugs. He’s a marketing guy with a tech background. He figured out all these marketing channels where, if you order Ozempic or whatever online, it basically drop-ships from the pharmaceutical company to you, and he gets a cut. But he said in the article, “At one point, we were doing $300 million a month in sales.” He goes, “Well, technically, I’m not a one-man company because I had to hire my brother to help me out.” So it’s the two of them.  That’s pretty great. Yeah. That’s definitely a unicorn. So if you’re listening to this and you have an enterprise company, and you want to harness AI in your business, create agentic systems, streamline your operations, and make your company more efficient and productive, then reach out to Charles Fry at CODE Éxitos. Any last thoughts for listeners who are thinking about building a business in the AI age? What advice would you give them? I don’t know that it’s changed a whole lot. Building a business is always hard work. For any listener who wants to chat about any of these topics or see if we’re the right fit, they can always reach out and contact me. The conversation is free, and I usually learn something from it. But no, I would say that things are different. It doesn’t mean they’re wrong or better. I think they’re just different. It’ll be interesting to see how all of this unfolds over the next few years.  Yeah.  I’m in it for the journey.  We’re living in interesting times. So, Charles Fry, Founder and CEO of CODE Éxitos, thanks for coming on the show. And if you enjoyed this show, make sure you follow us on YouTube and Apple Podcasts. Give us a review, and stay tuned because every week I bring an amazing entrepreneur onto the show. Thanks for coming. Thanks for listening.  Thanks, Steve. Important Links: Charles's LinkedIn Charles's Website

What does it take to turn a high school side hustle into a thriving retail brand, wholesale business, and nationally recognized name? Ashley Alderson sits down with John Mark Sharpe (John Mark Enterprises) as he shares the incredible journey from selling wreaths out of a guest bedroom to building a multi-location business, launching a successful wholesale ribbon line, and leading a team of nearly 40 employees. Along the way, he learned one of the most important lessons in business: sustainable growth happens when you're willing to start small, stay consistent, and keep reinvesting in what works. You'll learn: How a simple wreath business sparked an entrepreneurial journey Why he believes most business owners overthink growth How a mission trip to India led to a successful ribbon line The mindset change that helped him rethink debt and growth Join The Boutique Hub Get Swym John Mark & John Mark Enterprises: Instagram:@JohnMarkEnterprises Website: JohnMark.com  The Round Top Collection: shop.thertc.com                       ____________________________ Ashley Alderson: Instagram     The Boutique Hub: Website | Facebook | Instagram | Pinterest | TikTok | YouTube