Podcasts about smbs

Send us Fan MailSelecting the right ERP system begins long before software demonstrations or vendor evaluations—it starts with selecting the right advisor. While many consulting firms position themselves as independent, their implementation partnerships, reseller agreements, or vendor incentives often shape recommendations behind the scenes, leading organizations toward shoehorned solutions, vendor lock-in, and architectural decisions driven more by commercial alignment than operational fit. This webinar explains why true independence is critical during ERP readiness and selection initiatives, particularly as enterprise environments become more composable and category-specific. It explores what genuine vendor-agnostic consulting should look like in practice, including defining the target operating model before technology selection, aligning enterprise software categories without forcing everything into a monolithic ERP framework, and evaluating process maturity, data governance, and organizational readiness before narrowing vendor options. In contrast, many advisory firms rely heavily on familiarity bias, implementation convenience, or preconfigured solution stacks that quietly restrict strategic flexibility and increase long-term transformation risk.Video: https://www.elevatiq.com/events-and-webinars/how-to-select-an-independent-erp-consulting-firm-the-process-explained/Questions for Panelists?

Send us Fan MailThis week's enterprise software developments further demonstrate how rapidly vendors are embedding agentic AI, governed automation, and composable data architectures into core enterprise workflows. Rootstock Software strengthened its manufacturing and warehouse execution strategy through the acquisition of Ascent Solutions, while Anaplan expanded its AI planning portfolio with CoModeler, Custom Analyst, and Agent Studio to accelerate enterprise planning automation. In the go-to-market space, Apollo.io acquired Pocus to build a more agentic revenue operations stack, and Zapier partnered with Rillet to connect general ledger workflows with thousands of operational applications. Meanwhile, Databricks introduced Lakewatch as an open, agentic SIEM platform built on the lakehouse architecture, and Oracle launched Fusion Agentic Applications designed to place coordinated AI agents directly inside ERP workflows. Governance and enterprise trust also emerged as central themes, with Relyance AI unveiling Lyo to monitor how AI agents interact with enterprise data, while Salesforce introduced AI Foundry to operationalize research into enterprise-ready AI models. Finally, Spade raised significant funding to transform messy transaction strings into finance-grade AI data, reinforcing how semantic normalization and governed enterprise context are becoming foundational to the next generation of AI-native enterprise systems.In today's episode, we invited a panel of industry analysts for a live discussion on LinkedIn to analyze current enterprise software stories. We covered many grounds including the direction and roadmaps of each enterprise software vendors. Finally, we analyzed future trends and how they might shape the enterprise software industry.Video: https://www.youtube.com/watch?v=hekHpEgI0zMQuestions for Panelists?

What if the biggest bottleneck in hardware design isn't your engineer's skill — it's the sheer volume of manual work standing between a great idea and a working schematic? And once you decide to embrace AI-assisted design, how do you make sure the output is actually trustworthy enough to build from? What you'll learn… (00:12) Why fragmented workflows hit SMB hardware teams hardest (02:39) The real cost of going from requirements to prototype without specialist support (07:33) How functional block-level design changes early decisions — including when a SOM beats building from scratch (12:04) Why system-level abstraction catches wrong-path decisions before they reach the schematic (14:39) The "rubber duck debugging" effect: how AI clarifies requirements before they become costly mistakes (17:54) The biggest AI misconception in hardware design — and why the engineer must own every decision (20:30) How CELUS's NXP collaboration delivers manufacturer-validated, human-in-the-loop solutions (25:05) Why abstraction-first tools help SMBs take on projects that would otherwise be out of reach (28:19) The CELUS Success Program: high-touch onboarding for SMBs on the Siemens instance More about the episode… In this episode of the Printed Circuit Podcast, host Steph Chavez welcomes back Antonio Becerra Esteban, VP of Customer Success at CELUS — a physicist-turned-engineer with experience at Infineon and Altium who now leads the team ensuring customers extract real value from the platform. The conversation tackles the fragmented, manual journey from requirements to schematic that burdens small hardware teams. Antonio explains how CELUS's functional block-level design approach lets engineers define system architectures, navigate component trade-offs with an AI assistant, and output fully-interconnected schematics — illustrating the point with a Linux-based HMI example where the right abstraction layer turns a complex MPU build into a simple SOM selection. On the trust question, Antonio is direct: the engineer must own every decision. CELUS backs this up with manufacturer-validated design blocks, transparent sourcing, and a human-in-the-loop process — putting engineers in the driving seat rather than asking them to ship whatever the model produces. SMBs can join CELUS' Success Program by sending an email to cs@celus.io. Connect with Steph Chavez: LinkedIn Website Connect with Antonio Becerra Esteban: LinkedIn CELUS Website

Send us Fan MailThe automotive ERP market remains one of the most operationally complex and ecosystem-driven segments within enterprise software in 2026, making ERP selection highly dependent on business model alignment, manufacturing architecture, and supplier ecosystem participation. Automotive ERP spans organizations of all sizes, from emerging EV startups to global OEMs and multi-tier suppliers, yet the operational requirements across OEMs, Tier 1, Tier 2, and Tier 3 manufacturers differ dramatically in terms of compliance, traceability, production strategies, quality management, and supply chain coordination. As a result, no single ERP platform universally fits every automotive environment. One of the most important evaluation criteria is understanding whether an organization operates in a manufacturing execution-centric model—where MES integration, plant-floor coordination, machine connectivity, and real-time production visibility dominate—or a more ERP-centric model focused on procurement orchestration, forecasting, compliance management, and financial coordination. In addition, major automotive ecosystems such as Toyota, Honda, Ford, BMW, and Tesla often impose highly specialized supplier collaboration standards, EDI frameworks, and operational protocols that shape ERP vendor alignment strategies. While these ecosystem-specific optimizations can create strong operational fit within certain automotive networks, they may also introduce challenges when organizations expand across different supplier ecosystems, making historical industry alignment and ecosystem depth critical factors during ERP evaluation.In this episode, our host Sam Gupta discusses the top automotive ERP systems in 2026. He also discusses several variables that influence the rankings of these ERP systems. Finally, he shares the pros and cons of each ERP system.Video: https://www.youtube.com/watch?v=9k5ObVkvPMoRead: https://www.elevatiq.com/post/automotive-erp-systems/Questions for Panelists?

Fred Voccola, CEO of Simpro Group, explains how SMBs are using AI to boost efficiency, turning 5–7% margins into over 25% through optimized scheduling and job management. He highlights how AI acts as a digital workforce, helping smaller businesses scale profitably while larger enterprises face disruption from AI-driven efficiencies.======== Schwab Network ========Empowering every investor and trader, every market day.Subscribe to the Market Minute newsletter - https://schwabnetwork.com/subscribeDownload the iOS app - https://apps.apple.com/us/app/schwab-network/id1460719185Download the Amazon Fire Tv App - https://www.amazon.com/TD-Ameritrade-Network/dp/B07KRD76C7Watch on Sling - https://watch.sling.com/1/asset/191928615bd8d47686f94682aefaa007/watchWatch on Vizio - https://www.vizio.com/en/watchfreeplus-exploreWatch on DistroTV - https://www.distro.tv/live/schwab-network/Follow us on X – https://twitter.com/schwabnetworkFollow us on Facebook – https://www.facebook.com/schwabnetworkFollow us on LinkedIn - https://www.linkedin.com/company/schwab-network/About Schwab Network - https://schwabnetwork.com/about

An underground forum post breaks down how hackers scan, exploit, and cash out on vulnerabilities — and it reads like a step-by-step guide. Meanwhile, Microsoft is catching heat for stonewalling a researcher who found real zero-days, and a new phishing campaign is hitting small businesses through the platforms they trust most. The OG crew — Joshua Schmidt, Eric Brown, and Nick Mellem — digs into this week's biggest cybersecurity headlines with sharp takes and real-world context that practitioners can actually use. 

Send us Fan MailModernizing SAP environments requires far more than executing a software upgrade or signing a new licensing agreement. Organizations migrating to SAP S/4HANA or consolidating multiple regional ERP systems into SAP often face significant risks tied to fragmented legacy data models, inconsistent master data, and undocumented transformation logic that can undermine production cutover readiness. In this session, SNP CTO Steele Arbeeny explains how Kyano Crossway supports legacy-to-SAP conversion programs beyond traditional ETL approaches by governing the entire data conversion lifecycle. Rather than treating migration as isolated data loads, Crossway structures and manages mapping logic, transformation rules, validation workflows, and traceability controls to ensure transparency and audit confidence throughout the process. As a result, organizations gain visibility into what changed, why it changed, and whether the transformed data is fully prepared for production deployment within a governed SAP-ready architecture.Video: https://www.elevatiq.com/events-and-webinars/legacy-sap-workloads-readiness-turning-legacy-data-into-sap-ready-data/Questions for Panelists?

Platform vendors are transferring liability and delivery responsibility for AI services onto MSPs by building structured AI practice frameworks, training programs, and service delivery methodologies. This approach is motivated by mounting economic pressures on vendors, as seen with large-scale infrastructure investments and the need for sustainable revenue models. PAX8, Ingram Micro Cloud, ConnectWise, and others are formalizing AI partner programs that enroll MSPs to deliver vendor-defined services, while shifting operational complexity and accountability downstream. The episode highlights PAX8's Managed Intelligence initiative, aimed at helping small and midsize MSPs deliver AI services to SMB clients with minimal prior expertise. PAX8 cites its own research, which notes that 62% of SMBs view AI as essential for competitiveness and 74% plan to increase AI spending in the coming year. The economics of AI scaling are underscored by data on projected data center buildout costs—up to $15 trillion by 2030 and requiring $1.75 trillion annually just to maintain. OpenAI's public offering, with an $850 billion valuation and $180 billion in funding, is attributed to the need for capital that private markets can no longer supply, prompting vendors to leverage channel partners for both revenue generation and market validation. Supporting developments include expanded programs at the distribution and platform levels: a PAX8-Nocdoc partnership providing managed NOC/SOC services for smaller MSPs, Ingram Micro Cloud's collaboration with PartnerStack to formalize AI service delivery infrastructure, and ConnectWise's introduction of an AI-native platform for predictive and autonomous IT operations. Research from Omnia and the IBM Institute for Business Value indicates underutilization of vendor market development funds and widespread deployment of AI frameworks despite only 11% of tech leaders feeling prepared—demonstrating the gap between vendor offerings and operational readiness. The implications for MSPs are significant. By enrolling in these vendor-driven AI programs, providers take on delivery risk, contractual accountability, and potential liability for AI outcomes they did not design. The structural split is clear: MSPs can either create and govern their own AI methodologies—pricing accountability as a service—or become vehicles for vendor frameworks, absorbing complexity without full compensation or control. Practical recommendations include updating service agreements for AI-related risks, building internal governance around AI deployments, and not allowing vendor or community consensus to substitute for explicit accountability for outcomes. 00:00 Channel AI Shift  03:59 Enrollment, Not Enablement 06:55 Methodology vs. Liability 10:01 Why Do We Care?  Supported by:  Zero Networks  CometBackup 

Send us Fan MailThis week's enterprise software announcements further confirm that the market is rapidly converging around agentic AI, semantic intelligence, and autonomous workflow orchestration. Blue Yonder introduced new AI agents and mobile applications aimed at strengthening supply chain execution and frontline operations, while Zendesk expanded its AI customer service strategy through the acquisition of Forethought. Actian launched an AI analyst designed to convert business glossaries into a live semantic layer, highlighting the growing importance of governed enterprise context for AI-native operations. Meanwhile, ActiveCampaign and Contentsquare announced new capabilities focused on customer engagement and digital experience intelligence. On the enterprise planning side, Anaplan expanded its AI planning portfolio with CoModeler, Custom Analyst, and Agent Studio, while Oracle continued embedding coordinated AI agents directly inside Fusion ERP workflows through its new Fusion Agentic Applications initiative. In parallel, Apollo.io acquired Pocus to strengthen its agentic go-to-market stack, Databricks introduced Lakewatch as an open agentic SIEM platform built on the lakehouse architecture, and Rootstock Software acquired Ascent Solutions to deepen its manufacturing and warehouse execution capabilities.In today's episode, we invited a panel of industry analysts for a live discussion on LinkedIn to analyze current enterprise software stories. We covered many grounds including the direction and roadmaps of each enterprise software vendors. Finally, we analyzed future trends and how they might shape the enterprise software industry.Video: https://www.youtube.com/watch?v=ksS15kccXPcQuestions for Panelists?

https://holisticmarketinglab.com/holistic-campaigns/Authority marketing helps SMBs compete with larger players by building trust, not outspending them. Here's how to establish credibility in the AI era. HolisticMarketingLab City: Bad Segeberg Address: Am Weinhof 7 Website: https://holisticmarketinglab.com

There may be 400 million SMBs in the world, but there is no such thing as a typical SMB. That's what makes the segment so difficult and so valuable. From AI adoption and cybersecurity to marketplaces, partner ecosystems, and hyper-local go-to-market strategies, SMBs operate by a different set of rules than enterprises. What works for one business, industry, or geography may not work for another, making SMBs one of the most complex markets to understand and serve. In this episode of Zinnov Podcast, Kristine Henley, WW Head, Public Sector Partner Core at AWS, joins Rajat Kohli, Partner, Zinnov, to explore how SMBs are evolving, why many companies still misunderstand the segment, and what leaders need to do differently to build and scale successfully in the SMB market. Tune in now.

Send us Fan MailThe construction ERP market remains one of the most fragmented and industry-specific segments within enterprise software, making ERP selection particularly challenging in 2026. Before evaluating the top construction ERP systems, organizations must recognize that construction ERP extends far beyond large commercial contractors alone. The category includes a wide range of operational models, including general contractors, specialty trades, engineering and infrastructure firms, developers, public sector construction organizations, property maintenance providers, and real estate-focused businesses. These organizations vary significantly in project complexity, compliance requirements, subcontractor coordination, procurement workflows, field operations, and financial structures. As a result, construction ERP systems differ substantially in their project accounting models, job costing depth, resource scheduling capabilities, document management workflows, and field-service integration, making industry alignment and operational fit far more important than generic ERP functionality comparisons.In this episode, our host Sam Gupta discusses the top construction ERP systems in 2026. He also discusses several variables that influence the rankings of these ERP systems. Finally, he shares the pros and cons of each ERP system.Video: https://www.youtube.com/watch?v=Yu8rU9s8xaYRead: https://www.elevatiq.com/post/top-construction-erp-systems/Questions for Panelists?

What does it take to turn a local idea into a nationwide phenomenon? In this episode, Gordon and Corey kick off a summer series exploring products that started small and went big with the right marketing. Their guest is David Klein, creator of Jelly Belly, who reveals how an $800 investment and some unconventional tactics helped transform a tiny candy into a global brand. Gordon & Corey unpack the marketing lessons every local business can learn about publicity, storytelling, and punching above your weight. Stay in the loop with all things Borrell when you join our Research Alert Lists. As always, thank you for listening. If you like the episode, leave us a review!  Want to join the conversation? Share your comments at borrellassociates.com/podcast.

Join me as I unpack the most impactful Microsoft Build 2026 announcements for SMBs, including Work IQ's general availability, new autopilot and Scout agent features, enhanced agent security with Microsoft Execution Containers, and the latest MAI models for code, image, and voice. Discover how upcoming Work IQ APIs, OpenClaw integration with Windows, and the shift toward hybrid AI solutions are shaping the future of business technology, with practical insights on cost control, disaster recovery, and agentic security. Don't miss this episode for actionable takeaways and expert analysis on the evolving AI landscape. Resources CIAOPS Need to Know podcast - CIAOPS - Need to Know podcasts | CIAOPS X - https://www.twitter.com/directorcia director@ciaops.com CIAOPS Blog Join my Teams Shared Channel – CIAOPS CIAOPS Merch store - CIAOPS Become a CIAOPS Patron CIAOPS AI Dojo  CIAOPS weekly news update - CIA Brief – CIAOPS CIAOPS Labs – The Special Activities Division of the CIAOPS Support CIAOPS Get your M365 questions answered via email Join my email list A special thanks to the CIAOPS Patron community for making this podcast possible. You can find the benefits of a subscription to the community and become a member at https://www.ciaopspatron.com   Microsoft Build 2026 blog – Be yourself at work Developer-Tech – AI agents, Copilot, Windows developer tools VentureBeat – AI agents and enterprise use cases Thurrott – Scout personal work agent and AI models VentureBeat – Data silos and Microsoft IQ Windows Report – Securing code agents and AI models Engadget – Build 2026 live blog Microsoft Learn – Work IQ in Azure Foundry Firstpost – MXC, OpenClaw, and OpenShell

In this episode of The Unconventional Path: Entrepreneurship and Innovation Stories and Ideas, hosts Bela Musits and Mike Wasserman dive deep into a powerful yet often overlooked strategy for small to medium-sized businesses (SMBs): fractional communications. While many entrepreneurs are familiar with the concept of a fractional CFO or HR firm, the idea of a fractional Chief Communications Officer (CCO) is a game-changer for companies looking to scale efficiently and manage their reputation with precision.Our guest, Joshua Altman, shares his journey of starting and running a fractional communications business designed specifically for SMBs. For businesses that may not have the budget or the need for a full-time marketing executive, a fractional CCO provides high-level expertise to shape perception and build long-term trust with stakeholders. Joshua explains that his role goes beyond traditional branding or marketing; he takes an integrated, big-picture view of how a company's messaging impacts its growth and stakeholder confidence.Throughout the interview, we explore:The Fractional Advantage: Joshua discusses how hiring a part-time expert can be significantly more cost-effective than a full-time marketing hire while delivering measurable, high-level results.The Story-Narrative-Brand Framework: Learn Joshua's specific process for helping businesses discover what they truly want to communicate. He breaks down the critical differences between a company's story (the facts), its narrative (how it answers market questions), and its brand (the tangible elements like websites and marketing materials).Innovating with Novel Products: For companies launching entirely new products that the public doesn't yet understand, Joshua stresses the importance of involving a communications team early in the product development roadmap. He discusses how to lay the groundwork months in advance to educate potential customers and shape their purchasing decisions.Offloading Communication Tasks: Many SMB presidents or VPs of operations find themselves handling communication by "happenstance" because there is no dedicated staff. Joshua explains how his firm steps in to take these critical tasks off their hands, allowing leadership to focus on their primary roles of running the business.If you are a business owner looking for innovative ways to manage your messaging and improve your communication process in a measurable way, this conversation is packed with actionable advice on how to use communications as a strategic tool for success.Connect with The Unconventional Path:Our podcast is now available on YouTube. Simply search for "The Unconventional Path" to subscribe and never miss an episode.We're always on the lookout for interesting guests to feature on our show. If you know someone who has an inspiring story, unique perspective, or valuable expertise to share, please let us know. We're eager to connect with potential guests who can bring fresh insights and engaging conversations to our audience.We also love hearing from our listeners! Your questions, comments, and suggestions are incredibly valuable to us. Send us an email at bela.and.mike@gmail.com with your thoughts, and we'll do our best to address them in a future episode. Whether you have a question about a specific topic, feedback on a recent episode, or ideas for future content, we want to hear from you. Your engagement helps us shape the show and deliver content that resonates with our listeners.Thanks for listening,Bela and MikeSEO Search Terms: Fractional Chief Communications Officer, SMB growth strategies, entrepreneurship podcast, fractional CCO vs CMO, small business branding, communications strategy for startups, market penetration for SMBs, cost-effective marketing, building stakeholder trust, business narrative framework, product development roadmap, Bela Musits, Mike Wasserman, Joshua Altman, The Unconventional Path podcast.

Centaris Helps SMBs Bring AI Into the Business Without Letting Risk Come Along for the Ride, Podcast, According to Centaris, 86% of SMB workers are using AI tools, with 80% bringing their own tools into the workplace. At the same time, 80% of leaders cite leakage of sensitive data as their main concern. By Doug Green “We think there's a tremendous opportunity for us to shine where we've thrived for years.” In this Technology Reseller News podcast, Doug Green speaks with Mike Nowak, Chief Revenue Officer at Centaris, about the challenges small and midsize businesses are facing as AI adoption moves faster than many IT and security programs can manage. Centaris provides cybersecurity and managed IT services for small and midsize organizations, with a focus on the Great Lakes region and companies with roughly 50 to 5,000 employees. The company works across key verticals including manufacturing, healthcare and financial services, where security, compliance and operational continuity are central business concerns. The conversation focuses on a problem that is becoming urgent for SMB leaders: AI is already inside the organization, whether or not it has been formally approved. According to Centaris, 86% of SMB workers are using AI tools, with 80% bringing their own tools into the workplace. At the same time, 80% of leaders cite leakage of sensitive data as their main concern. That creates a new challenge for MSPs, IT leaders and business owners. The question is no longer whether employees will use AI. They already are. The question is whether companies can create a secure, consistent and manageable way to use AI without exposing customer data, intellectual property or regulated information. Nowak outlines Centaris' role in helping organizations move from uncontrolled AI experimentation to structured deployment. For many smaller companies, AI adoption is happening at the employee level first. Staff members are using publicly available tools to write, summarize, research and automate work. That can create productivity gains, but it can also create risk when sensitive information is pasted into tools that are not governed by company policy. Centaris is positioning its AI and cybersecurity work around practical deployment. Rather than treating AI as a separate technology trend, the company sees it as part of the broader managed services and cybersecurity conversation. SMBs need policies, training, tool selection, identity controls and security frameworks that match the way employees are already working. The podcast also looks at the broader cybersecurity posture of the small and midmarket. These organizations face many of the same risks as larger enterprises but often lack the same internal resources. That makes consistent managed security, compliance guidance and trusted IT leadership especially important. Centaris is also in growth mode. Nowak says the company is looking to expand across the Great Lakes footprint, particularly in areas where it already has experience and vertical expertise. “The ones that we're looking for and where we're looking to expand is really the Great Lakes footprint,” Nowak says. “We think there's a tremendous opportunity for us to kind of shine where we've thrived for years.” The acquisition strategy is focused on fit and execution. Centaris is interested in organizations that align with its strengths in manufacturing, healthcare, financial services and cybersecurity-driven managed services. The company works with larger clients and clients in other regions, but Nowak emphasizes that Centaris is careful about ensuring it can execute well before expanding. For MSP owners, the message is direct: Centaris is open to conversations with firms that may be considering their next step. For SMB leaders, the message is equally clear: AI is already arriving inside the business, and the time to secure and standardize that adoption is now. Centaris can be reached through LinkedIn, at info@centaris.com, or through the Centaris website. Learn more at centaris.com.

Welcome to the CanadianSME Small Business Podcast, hosted by Maheen Bari. Today, we explore how resilience, leadership, and practical AI adoption are helping entrepreneurs navigate uncertainty, improve profitability, and build businesses that are ready for long-term success. Joining us is Ema Dantas, Summit Strategist, author, and one of fewer than 130 Canadians to complete the Seven Summits. Ema shares how the mindset required to conquer the world's highest peaks can help founders overcome business challenges and embrace transformation with confidence. Key Highlights AI Without the Complexity: Ema explains how SMBs can use AI to increase revenue and efficiency. Protecting Margins in a Changing Market: Ema shares strategies for maintaining profitability in the AI era. Leadership Lessons from Everest: Ema highlights how summit experiences shaped decision-making under pressure. Building an Exit-Ready Business: Ema explains what founders should prioritize to create long-term value. The Human + AI Advantage: Ema shares how small teams can combine technology with human expertise for growth. Special Thanks to Our Partners: UPS: https://solutions.ups.com/ca-beunstoppable.html?WT.mc_id=BUSMEWA ADP Canada: https://www.adp.ca/en.aspx For more expert insights, visit www.canadiansme.ca and subscribe to the CanadianSME Small Business Magazine. Stay innovative, stay informed, and thrive in the digital age! To learn more about how we are supporting the ecosystem, please visit the CanadianSME Small Business Foundation at smbfoundation.ca. Disclaimer: The information shared in this podcast is for general informational purposes only and should not be considered as direct financial or business advice. Always consult with a qualified professional for advice specific to your situation.

Send us Fan MailSelecting a modern FP&A platform is no longer simply a budgeting or reporting decision—it is a strategic architecture choice that shapes how finance organizations operate, collaborate, and scale. Today's FP&A and broader CPM/EPM platforms directly influence forecasting speed, executive visibility, scenario modeling, data governance, and cross-functional decision-making across the enterprise. As a result, finance leaders must evaluate far more than dashboards and planning features alone. They must assess the underlying data architecture, integration depth with ERP and operational systems, scalability across business units, workflow flexibility, and the platform's alignment with the organization's long-term operating model. In many cases, the wrong architectural decision creates fragmented planning processes, inconsistent metrics, and governance challenges that limit finance's ability to function as a strategic business partner.In this episode, Sam Gupta and Shrestha Dash from ElevatIQ, Andy Pratico from Essential Software Solutions, and Phil Coerper from Ringling Business Solutions conduct an in-depth independent review of a leading FP&A platform Aleph.Video: https://www.elevatiq.com/events-and-webinars/aleph-an-independent-in-depth-review/Questions for Panelists?

https://yes.ampifire.com/ampcast/ai-games/launchDiscover how Google AI overviews are reshaping organic traffic and why traditional SEO rankings no longer guarantee visibility. Learn strategies at the AmpCast AI Games, June 5-7, 2026, and how small businesses can use AI to drive traffic on autopilot without massive budgets. MunchEye City: London Address: London Office 15 Harwood Road, , London, England United Kingdom Website: https://muncheye.com/

Send us Fan MailThis week's enterprise software announcements highlight how rapidly the market is evolving toward agentic architectures, semantic intelligence, and AI-driven operational orchestration. Anthropic expanded MCP with a framework designed for full-stack agentic applications, reinforcing the industry's push toward composable AI ecosystems. Meanwhile, Hubbl Technologies raised funding to position itself as an intelligence layer for the Salesforce agentic environment, while Salesforce continued broadening its AI footprint through Agentforce for Communications. Sage enhanced the Sage Intacct Suite with new capabilities focused on finance operations, and Sinch introduced a collection of AI agent features targeting customer engagement workflows. On the operational side, Typeface unveiled a marketing orchestration engine, while Blue Yonder announced new AI agents and mobile applications aimed at supply chain execution and workforce enablement. At the same time, Zendesk moved deeper into AI-powered customer support through its acquisition of Forethought, and Actian launched an AI analyst designed to transform business glossaries into a live semantic layer, signaling the growing importance of governed enterprise context for AI-native operations.In today's episode, we invited a panel of industry analysts for a live discussion on LinkedIn to analyze current enterprise software stories. We covered many grounds, including the direction and roadmaps of each enterprise software vendor. Finally, we analyzed future trends and how they might shape the enterprise software industry.Video: https://www.youtube.com/watch?v=NCxtpqQ_vIwQuestions for Panelists?

Send us Fan MailDistribution-centric ERP systems represent one of the most operationally diverse categories in enterprise software, making ERP evaluation far more complex than many organizations initially expect. Before reviewing the top distribution ERP systems in 2026, it is critical to understand that distribution extends well beyond traditional wholesale operations. Many distribution businesses also manage light manufacturing, assembly, kitting, fabrication, ecommerce fulfillment, or retail processes, yet their primary operational complexity revolves around inventory movement, procurement, warehousing, logistics, fulfillment, and multi-channel coordination. This category spans a broad range of industries and company sizes, including industrial supply, HVAC, automotive, medical devices, food and beverage, construction supply chains, and ecommerce-driven businesses. Consequently, ERP systems designed for distribution vary significantly in their warehouse models, inventory strategies, fulfillment capabilities, pricing structures, and supply chain workflows, making business-model alignment far more important than generic feature comparisons alone.In this episode, our host Sam Gupta discusses the top distribution ERP systems in 2026. He also discusses several variables that influence the rankings of these ERP systems. Finally, he shares the pros and cons of each ERP system.Video: https://www.youtube.com/watch?v=GA4XdEACxZoRead: https://www.elevatiq.com/post/top-distribution-erp-systems/Questions for Panelists?

Discover why single-channel marketing leaves SMBs invisible and how multichannel strategies drive 412% higher purchase rates. We break down the content distribution system that's helping small businesses scale their reach without burning out. For more information, visit https://redwoodbasin.clientcabin.com/ Redwood Basin Digital Media LLC City: San Jose Address: 6933 Rodling Dr Website: https://redwoodbasin.clientcabin.com

Send us Fan MailERP initiatives frequently fail because organizations confuse ERP selection with ERP readiness. Selecting an ERP system is primarily a procurement and evaluation exercise, while ERP readiness is a far more complex organizational transformation involving process alignment, governance, data discipline, and executive consensus. ERP systems do not repair broken workflows, resolve ownership conflicts, or clean inconsistent master data—they simply automate and enforce whatever structure already exists. Unfortunately, many organizations develop a false sense of confidence once software is selected, assuming the implementation partner or vendor will absorb integration complexity and operational gaps. In reality, ERP readiness is what determines long-term success. It defines the target operating model, clarifies process accountability, strengthens data governance, and aligns stakeholders before implementation risk compounds. While ERP selection feels tactical and visible, ERP readiness requires strategic intent, organizational discipline, and executive commitment to prevent adoption failures, financial overruns, and architectural misalignment.Video: https://www.elevatiq.com/events-and-webinars/erp-readiness-vs-erp-selection-selecting-an-erp-will-not-make-you-ready/Questions for Panelists?

Send us Fan MailFor most small businesses, health insurance is their second or third largest expense. And they usually find out what it's going to cost them two to three weeks before renewal.In this clip from our episode “Why Health Insurance Needs Transparency”, host John Driscoll and Ty Wang, Co-Founder and CEO of Angle Health, break down why unpredictable premium increases make it nearly impossible for small businesses to plan, and why the market has accepted this as normal for far too long.Listen to the full episode here

The 2026 Verizon DBIR is here — and one finding changes the conversation around cyber risk.For years, the industry has focused on identity as the primary attack surface. But according to the latest Data Breach Investigations Report, vulnerability exploitation has now overtaken credential abuse as the most common initial access vector in breaches.In this episode of Reimagining Cyber, Tyler Moffitt breaks down what the report really means for defenders, MSPs, and SMBs. He explores why attackers are moving faster than patch cycles, how AI is accelerating both exploitation and phishing, and why “identity vs. patching” is the wrong debate.He also unpacks:Why vulnerability exploitation surged to the top attack vectorHow AI is compressing the timeline from disclosure to attackWhy ransomware still dominates breach outcomesThe growing role of third-party and supply-chain riskWhy SMBs struggle most with patch management and visibilityPractical steps organizations should prioritize right nowWhat MSPs should be telling customers after this year's DBIRKey takeaway:“Identity is the new perimeter, but vulnerability management is still the unlocked window.”If you work in cybersecurity, IT, risk management, or support SMB environments, this episode delivers practical insight into where attackers are succeeding — and what organizations need to do next.#CyberSecurity #DBIR #Ransomware #PatchManagement #IdentitySecurity #AI #MSP #CyberRisk #VerizonDBIR #InfosecAs featured on Million Podcasts' Best 100 Cybersecurity Podcasts  Top 50 Chief Information Security Officer CISO Podcasts Top 70 Security Hacking PodcastsThis list is the most comprehensive ranking of Cyber Security Podcasts online and we are honoured to feature amongst the best!Follow or subscribe to the show on your preferred podcast platform.Share the show with others in the cybersecurity world.Get in touch via reimaginingcyber@gmail.com

Send us Fan MailThis week's enterprise software announcements reveal how aggressively vendors are repositioning around AI agents, composable integration, and industry-specific workflows. NetSuite introduced its new integration platform to simplify connectivity across enterprise ecosystems, while Oracle expanded both its process manufacturing capabilities and AI agent portfolio inside Fusion Cloud Applications. QAD and Tata Consultancy Services strengthened their manufacturing operations strategy through the Redzone partnership, reinforcing the growing importance of connected frontline execution. Meanwhile, Intuit Mailchimp rolled out new e-commerce enhancements, and Seismic and Highspot announced a major merger that could reshape the sales enablement landscape. On the AI infrastructure side, Anthropic expanded MCP with a framework for full-stack agentic applications, while emerging vendors like Hubbl Technologies positioned themselves as orchestration layers for the Salesforce agentic ecosystem. Finally, Sage, Salesforce, and Sinch continued the broader trend of embedding AI agents deeper into finance, communications, and customer engagement workflows, signaling that the enterprise software market is rapidly shifting from passive systems of record toward autonomous systems of execution.In today's episode, we invited a panel of industry analysts for a live discussion on LinkedIn to analyze current enterprise software stories. We covered many grounds, including the direction and roadmaps of each enterprise software vendor. Finally, we analyzed future trends and how they might shape the enterprise software industry.Video: https://www.youtube.com/watch?v=i0Ktqz2rXh8Questions for Panelists?

I recently interviewed Clive Enever, and this conversation goes straight to the heart of why so many coaches struggle to get clients, even when they're good at what they do. Clive has been in business and coaching for over 30 years, and what he shared about sales, identity, and “ideal clients” is not what most coaches are being taught. We talked about why demographics don't define your ideal client, what sales actually is (hint: it's not persuasion), and how misunderstanding your client's real needs is what's quietly killing your conversions. If you've ever felt uncomfortable selling, unsure who your work is really for, or frustrated that your marketing isn't landing, this episode will give you a completely different way to look at your business. Guest Bio Clive Enever isn't just a business strategist, coach, and mentor; he's a seasoned entrepreneur with over 30 years of experience navigating the highs and lows of the business world. He understands the unique challenges faced by small and medium businesses (SMBs) because he's been there himself. Previously holding senior roles in Telecommunications, Retail, and Property, Clive brings a wealth of industry knowledge to the table. Now, he leverages his expertise and proven strategies to help entrepreneurs and business owners like you achieve their goals. Clive doesn't believe in a one-size-fits-all approach. He gets to know your individual needs, whether you're seeking increased profits, a better work-life balance, or less stress. Combining his friendly demeanor with sharp insights, he uses humour and his extensive knowledge to guide you towards success. Links + CTA https://www.enevergroup.com.au/strategy/       https://www.linkedin.com/in/cliveenever https://www.facebook.com/clive.enever   Listen to the Raving Coaches Podcast: Spotify: https://open.spotify.com/show/7pNiUG0d05CTFM0MNJeuFE?si=dd985373802a470b Apple: https://podcasts.apple.com/us/podcast/raving-coaches/id1673460023

Felipe Carvalho is Co-Founder and Chief Revenue Officer of Camu — an AI workflow automation platform. Previously, Felipe spent 10 years building the global go-to-market organization at Pipefy alongside founder Alessio Alionço, scaling a horizontal workflow platform that serves Volvo, Capgemini, IBM, Accenture, Visa, Santander, Itaú, and thousands of other SMBs and enterprises across Brazil, the US, and beyond. Before Pipefy, he built and scaled the fundraising function at Hospital Pequeno Príncipe — Brazil's largest children's hospital — raising over $20M and growing a team of 50.In this TJC Operators episode, Felipe shares the brutal sales lesson from Pipefy — why selling everything to everyone is a GTM trap that hides inefficiency through inbound demand, and why outbound exposed it overnight. He walks through the "who would be crazy not to buy this" framework from Seth Shaw (former CRO of Airtable) that reshaped Pipefy's outbound motion, how Camu got from 1–2% to 17% to 33% conversion by progressively narrowing focus to a single ERP (SAP Business One) and one specific workflow (invoice intake), why charging monthly with no strings attached was the cleanest way to validate true product-market fit, the Sean Ellis "very disappointed" PMF survey methodology and how Camu hit high-50s on a V1 product, why saying no to massive enterprise RFPs is a superpower in the early days, how Felipe now manages 68 active opportunities solo by using Claude and AI to automate 50–70% of sales back-office work (CRM updates, ROI calculations, proposal generation, deal-power scoring), the FCA (Fact, Cause, Action) framework Pipefy used to run monthly results meetings and why analyzing wins matters as much as analyzing losses, why "building a plane is different from flying a plane" — and why founders should nail the sales playbook themselves before hiring senior enterprise sellers, the shift from selling software-as-a-service to delivering recurring impact and how risk has moved from buyer to seller in the AI era, and the lesson he most wants Brazilian founders to learn about building credibility before the market gives it to you.Subscribe to The J Curve Insider newsletter for deeper insights and follow Olga on LinkedIn and Instagram.

Send us Fan MailManufacturing ERP remains one of the broadest and most misunderstood categories in enterprise software. Before evaluating the top manufacturing ERP systems in 2026, organizations must first understand that manufacturing is not a single industry—it is a collection of highly specialized micro-verticals with unique operational, engineering, compliance, and supply chain requirements. Consequently, manufacturing ERP platforms differ significantly in their process models, data architectures, and industry alignment. Some systems are designed to support multiple manufacturing modes through broad and flexible capabilities, while others are purpose-built for highly specific operational environments. This makes context critically important when comparing ERP systems, especially across different company sizes, business models, and levels of manufacturing complexity.In this episode, our host Sam Gupta discusses the top manufacturing ERP systems in 2026. He also discusses several variables that influence the rankings of these ERP systems. Finally, he shares the pros and cons of each ERP system.Video: https://www.youtube.com/watch?v=gLYsM4ExpD8Read: https://www.elevatiq.com/post/top-manufacturing-erp-systems/Questions for Panelists?

Send us Fan MailNearly half of all Americans get their health insurance through a small business. Most of those businesses have no idea why their premiums go up every year and no real power to do anything about it.Ty Wang, Co-Founder and CEO of Angle Health, joins host John Driscoll to discuss why legacy insurers benefit from keeping small businesses in the dark on costs, and how rebuilding the health plan stack from the ground up on modern, AI-native infrastructure is finally making transparency and customization possible for the employers who have always needed it most.

The most consequential development discussed is the rapid proliferation of Shadow IT in client environments, with emphasis on the unchecked adoption of cloud SaaS applications and artificial intelligence (AI) tools by end users. Speakers noted that this has led to a substantial loss of MSP control over client IT environments, eroding trusted advisor status and prompting clients to question the ongoing necessity of working with their MSP. The pervasive use of AI and SaaS products without guidance or oversight introduces governance and security risks, particularly relating to sensitive business data being accessible to third-party vendors and potentially incorporated into external data sets. The episode provided details on how Shadow IT emerges, highlighting the ease with which employees can adopt SaaS and AI tools through free trials, personal accounts, or non-business credit cards, often outside of IT's direct visibility. According to Amy and El, clients are increasingly self-serving their technology needs, shifting traditional MSP-client dynamics. The conversation outlined specific governance issues, such as most AI tools ingesting client data into the cloud, with limited assurance as to how it will be used or protected unless higher tiers of service are paid for—an unlikely scenario for most SMBs using free versions. Secondary discussion focused on broader industry fragmentation and the challenges it poses for knowledge-sharing, consensus-building, and vendor feedback. The speakers recalled a time when MSP best practices spread rapidly through tightly-knit peer groups or single platforms but observed current information channels are numerous and scattered, such as Discord, Reddit, LinkedIn, and Facebook. This dispersion hinders both MSPs and vendors from collaborating effectively and reduces the feedback loop necessary for responsive product development and operational improvement. The key implications for MSPs and IT leaders include the pressing need to shift operational models from rigid, tool-centric offerings to relationship- and advisory-focused services. There is heightened risk if MSPs fail to address governance and security concerns, especially as end users continue adopting technology independently. Speakers recommend implementing proactive client education, detailed risk analysis on SaaS and AI integrations, and establishing clear communication strategies to reclaim the advisory role. MSPs are encouraged to align compensation models to advisory activities, as future client value is projected to depend more on strategic guidance than product-resale or ticket-resolution metrics.Title: How are you managing Shadow IT? Topics: How are you managing Shadow IT? Is the MSP industry too fragmented in how we share knowledge? Why do MSPs exist? (blog posts from “Amy's Sayings”: https://www.thirdtier.net/?s=Amy%27s+sayings) What does it mean to be a M365-based MSP in 2026? Upcoming events: Zero Trust Workshop- 3 sessions starting May 28.  Register here: https://www.thirdtier.net/2026/04/27/arriving-in-may-zero-trust-workshop/ Mastermind Event with James (and Amy is a guest speaker!) in Omaha, NE Register here: https://kernanconsulting-mastermind.mykajabi.com/mastermind-event Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Send us Fan MailProfit erosion in batch and process manufacturing rarely happens suddenly; it accumulates over time through material variability, yield loss, production inefficiencies, excess inventory, and disconnected systems—issues that quietly drain cash, especially in sectors like food and beverage, where small variances can have an outsized financial impact. This webinar outlines four practical levers manufacturers can use to unlock hidden cash without raising prices or reducing headcount, focusing on tighter control of raw material costs, improved real-time production visibility, and the elimination of operational bottlenecks. It also demonstrates how purpose-built ERP solutions such as ECI Deacom enable scalable, end-to-end visibility across production, inventory, and financials, allowing organizations to detect margin leakage earlier and respond proactively. By shifting from reactive to data-driven decision-making, manufacturers can improve cash flow, enhance operational efficiency, and protect profitability across batch and process environments.Video: https://www.elevatiq.com/events-and-webinars/batch-and-process-manufacturing-unlock-hidden-cash-in-your-business/Questions for Panelists?

The Great Talent Redistribution: Where is Talent Actually Going in 2026 and beyond?  Is the start-up compensation model broken? How about big Big Tech? How about non-tech small & medium businesses? What is happening to talent, going forward? This and many other topics in this episode of Tech Deciphered. Navigation: Intro The Broken Contract? The Great Unbundling The Three (?) Destinations Alternative Cap Tables, Alternative Compensation Models Investor Landscape Fragmentation Operator Playbook and Predictions Conclusion Our co-hosts: Bertrand Schmitt, Entrepreneur in Residence at Red River West, co-founder of App Annie / Data.ai, business angel, advisor to startups and VC funds, @bschmitt Nuno Goncalves Pedro, Investor, Managing Partner, Founder at Chamaeleon, @ngpedro Our show: Tech DECIPHERED brings you the Entrepreneur and Investor views on Big Tech, VC and Start-up news, opinion pieces and research. We decipher their meaning, and add inside knowledge and context. Being nerds, we also discuss the latest gadgets and pop culture news Subscribe To Our Podcast Nuno Goncalves Pedro Introduction Welcome to episode 77 of Tech Deciphered. This episode will focus on the great talent redistribution. Where’s talent actually going in 2026 and beyond? The Silicon Valley deal of the last 30 years, very low salary, stock options, you will either sell for a ton of money or IPO, and everyone gets rich, is seemingly broken. Or is it really? The dominant narrative says the tech middle class is dying. We disagree. There is obviously a lot of stuff going on whereby big tech is partially barbelling. There’s a superstar concentration on the top. There’s a bit of a seemingly allowing of the belly. We’ll come back to that. We don’t quite believe that is totally true. There’s a collapse at entry level. The belly is migrating into three, potentially even more, very different destinations: AI native startups, human-verified premium businesses, and the read the industrialized middle of the S&P 500 and SMB world. Each has its own cap table, each will have its own compensation model, and each will have its own investor profile. In some ways, this is the third episode in our Reset trilogy. We started with episode 75 on the SaaS-apocalypse. We talked about the great private capital reset in episode 76, and now we talk about talent redistributions. Bertrand, exciting times, not always positive times.   Bertrand Schmitt Yeah, it’s exciting times because it’s a time of change. Of course, we have the doomsayers. If you listen to Dario Amodei of Anthropic, every white-collar job on Earth is going to disappear. I think I strongly disagree, and I suppose you too as well, we strongly disagree. It’s going to be more of a redistribution. If you look at the history of technology, this is what always happened. We forget how many jobs have disappeared over the past 150 years. We move from a time of 150 years ago. People were mostly in agriculture. Then you had a lot of weird jobs that disappeared from people transporting water to people bringing ice from the pools to people doing the job of computers. People forget that computer was a title given to human beings. We’re doing calculations. Then, of course, secretory jobs in the ’80s, ’90s, where suddenly anyone can type using a word processor, the rise of Excel, that sort of stuff. Many things have changed. Some jobs have indeed disappeared. Some jobs have totally transformed. Where you do these jobs have changed. I think we are at a similar stage where, thanks to AI, and I would say for now, or at least the rise of AI coding, there is a dramatic change happening. I don’t think it means that people will be without a job. It just means, from my perspective, that jobs are changing. You are not just doing a lowly coding level task that actually indeed could be replaced, but you are going to have more of builder type of mindset, a product manager type of mindset going forward. We also expect that the distribution of jobs, depending on the type of business, will be quite different.   Nuno Goncalves Pedro The Broken Contract? Maybe let’s reset a little bit to the broken contract, or if it’s really a broken contract. There’s been this image in technology and tech that basically you get paid very little to work in tech. You get a bunch of stock options. The earlier you are in the company, the higher the level of stock option grants you get. Then you make a ton of money at some point because the company will either sell or IPO, and that’s heard of it. Obviously, there’s a lot of movements happening right now that are changing how these dynamics work. The first part is obviously AI, and in some ways, AI is shrinking companies. It’s not unheard of that companies with as little as four or five people reach 50 million in ARR. There’s companies with one person that have gotten bought for hundreds of millions of dollars or billion of dollars. Obviously, things are moving very, very fast, and therefore, there isn’t a large employee cap table. How would you share the upside? Would you actually give a couple of percentage points to an early employee rather than your 0.2-0.5% kind of thing for early employees? The second part is a little bit the other side of the table, which is the IPO market is seemingly in a drought. There’s not much happening in IPOs. Maybe 2026, at some point, there will be an unlock, but right now, it’s seemingly difficult to get your upside. Even if you’re an employee, you have to wait a long time. The median time of IPO has climbed over 10, 11 years, the longest in over a decade. Basically, not only you have to wait a long time as if there is an IPO drought, like we might be going through right now, when do I actually get my cash back? Unless the company gets bought, maybe there are secondary transactions along the way, maybe there’s something else. But obviously there’s a little bit of a reduction and lowering of the upside seemingly for this contract and for this place. The easy conclusion that I think many are taking is, because of all of this and all the layoffs that are happening, even in big tech, that serve the tech middle class is dying, that basically AI screwing the workers, et cetera, there’s also a lot of discussion that even it might be affecting the entry-level jobs as well. Everyone coming out of undergrad right now can’t get a job, et cetera. There’s this doomsday scenario that you’re alluding to that everything is changing. We have a slightly different perspective. We think there’s a realignment of market. In layoffs, there was a lot of layoffs that were warranted. Big tech, in particular, had actually hoarded a lot of engineering capacity over the last decade or so. There’s a little bit of a realignment that needed to happen in any case. When everyone’s saying, “Well, AI is compressing everything,” well, it’s compressing right now, but we don’t think actually it’s going to compress over time. You’ll still need engineering and science talent to come on board for you to be able to scale up. It’s not like AI is going to take care of everything and teams are going to be five people for companies that are worth a trillion dollars. That’s not happening. Today’s thesis, I think a little bit of this doomsday scenario needs to be seen with a more nuanced lens. I think that’s how we’re framing today’s episode, that there’s a bit of a nuance, there are some extremes happening. We’re going to talk about those extremes, but ultimately, it’s not quite as simple as saying that the tech middle class is disappearing in early jobs are going to be a thing of the past.   Bertrand Schmitt At the same time, what you started with is true. I mean, that 50 million ARR company, just five people. At a bigger scale, that’s exactly the matrix for Anthropic. They have reached a stage where they are at a range of 12 million ARR per staff per employee. It’s metrics that are definitely never seen before. I don’t think any company raised to this level. Best in class, best run companies, one, two million per employees. I mean, that was your target if you can make it. We are definitely in a different game. But I think what matters at the end of the day, and that’s what we’re arguing, is that you have to see the big pictures. Yes, some positions might disappear inside some companies, but some other positions will be created in other companies. Usually, what people do is keep talking about the jobs who disappear and not looking at the bigger picture of jobs that are being created as well. What is true, and I think you alluded to that, is that the big tech the past 10, 15 years had some strategy of hoarding talent in a war where having the best talented people will make the difference in numbers, will make the difference between winning or losing. The Google of the world, the Microsoft of the world, the Amazon of the world, they were hoarding talent. They would try to make sure that they might not have such needs in talented number of people. But if they have the talent, it means their competitors didn’t have the talent. It means that the startup trying to reach scale couldn’t pay the giant salaries that the Google of the world were paying. There was definitely some hoarding. But it went so far in the 2020, 2021, that I think since then there has been a coming back to normal. There is also now in 2026, the recognition that it’s not true anymore. Yes, talent can be very valuable, but there is now a bigger and bigger gap between the extremely talented versus the rest that are merely talented because of AI. AI is able to replace at scale your software engineers, your software managers. I would say it’s quite new. I don’t think it was true a year ago. We’re really talking about a recent dramatic change in what can be achieved thanks to AI. We can see most of the big AI companies are moving to coding. It was started by Anthropic as a trend, OpenAI has followed through. Obviously, the Cursor of the world existed before, but they were not as successful. All the Chinese open-source models are moving very fast to coding optimization the past few weeks. It’s quite an incredible change. I think there is that dramatic change, recognition that coding can be done differently. As a result, we are going to see change in the distribution of jobs. I think it will start from the top because we see the news of the big Google, Microsoft, Amazon, and others who used to hold talented software developers to a change in realization that no, we actually need to invest in AI. We need to invest in compute because compute is going to do the job of most of these people. Therefore, we can’t pay for both at the same time, even us with all our money, we cannot. Wall Street is not going to let us do that. They start by removing a lot of position. I think we see that accelerating, quite frankly. We have only seen the beginning, but in the next 2 years, we see a dramatic shift. But I think my position, I guess yours, and you know as well, is that there will be a lot more opportunities created as well, probably by also entities.   Nuno Goncalves Pedro The Great Unbundling Yeah, there will be more opportunities created. The hoarding is just taken also a little bit of a different view. To your point, there’s hoarding of resources, compute, et cetera. But there’s also hoarding of top talent. We are seeing people getting paid, packages all in that could run up to 100 million, in some cases even over 100 million over several years. This is unheard of. I mean, an officer of Meta would make, I don’t know, maybe 20, 25 million a year. It’s like now there are people that are on the top end of AI researchers that are getting paid around that amount just to join some of these companies. There’s a little bit of a different hoarding. It’s very selective hoarding of certain talent. We’ve seen some acqui-hires. We’ve talked about it in previous episodes that are just literally about getting one or two people specifically to come on board. Alexander Wang, again, going to Meta to lead their intelligence labs there. I feel, I don’t know what you feel, but I feel this is a transition moment where there is overpaying for certain talent on the top of the market. At some point, this will stabilize. You can’t keep paying people 100 million over 4 years or something like that across the board. To your point, a lot of this is actually going to scale up quickly also on the AI side. There’s a little bit of a different hoarding happening on the top end, not just the resources, but also of people, which seems to give further this notion of barbell, that there’s two extremes, the haves and have-nots, the super-duper talented people that get paid a ton of money, tens of millions of dollars a year at the very least. Then the emptying of the middle where there’s a ton of tech layoffs going on in some ways, the belly, as they would call it, is being expelled. The middle market, the managers are being fired because there’s nothing to manage. There’s a lot of positions going away. In some cases, you might keep some of the more junior talent, but with a little bit of experience. But even the talent coming out of colleges is not getting hired either. It’s a little bit of a weird thing where there’s hoarding at the top, there’s an emptying of the belly, the middle, and then the early, early, early is also not getting recruited. It’s like what gives? How is this going to look in the future? I agree fully with you, Bertrand, that there’s a migration of this talent, not only to other companies, but also to other jobs. There will be new jobs that will emerge out of this. The DevOps, dev tools market didn’t exist until maybe 20 years ago at scale, and it got created. In some ways, we’re seeing there will be new markets, there will be new roles and new jobs that will be created around engineering teams going forward. We can’t anticipate all of them. But basically, the emptying of the belly is true as it’s happening right now. The low hiring on the early and the top end, getting tons of money. We think this is a transition to something else. There’s the hoarding of engineering in general is coming to an end at momentum. Now it’s time to rightsize teams, to get the right at the table, et cetera, and start figuring out what works and what doesn’t work. We’ve already had some horror stories coming out even from Amazon where they were breaking systems with their use of AI tools, and I’m sure it’s happening across the board. I’m on a board of a company and been tremendously affected by Meta and its algorithms, where basically because of advertising, there have been people served with ads for this specific company where the ad doesn’t match the company, so basic stuff like that. It’s been actually very, very difficult because in some ways, the company goes back to Meta. It’s like, “Hey, dudes, you guys are serving ads that are not even our ads with our copyright and stuff. How does this work?” They’re like, “Oh, it’s AI.” It’s like, “Well, it’s AI but can you give me my money back?” They’re like, “No, we won’t give you money back.” This creates huge issues for companies, for example, that are very dependent on advertising, which obviously there’s a lot of industries that are. They’re actually in production systems at scale. Meta is, I think now, the largest digital advertising in the world. I think they outgrew Google in one of the last quarters. Basically, this has a tremendous effect that systems that are in production at scale are getting inputs and changes driven by AI tooling, and somehow nobody can say what the hell is happening. Again, there will be a reckoning, there will be a redistribution, there will be a rightsizing of teams and an adequacy of teams going forward. I personally think this is a transition period.   Bertrand Schmitt I think we are moving from hoarding or software engineering to hoarding the top of the top scientists in AI and hoarding of GPUs, GPUs/data center. For me, it was quite interesting to see the deal of Cursor with xAI, where basically they couldn’t get access to computing resources to run their model. But xAI had, I forgot the exact numbers, but close to half a million GPUs that no one, I mean, “no one was using” because their services are not so successful yet in terms of AI chatbot and the like. Basically, suddenly they are like, “You know what? We control access to resource.” But the new resource is, again, a mix of extremely talented AI engineering or AI scientists versus GPUs/data center. There is this race of controlling boss and everything else is going to be collateral damage. Some examples, I think, are quite interesting. You talk about some example of Amazon, even some production issues. I remember reading a quick post-mortem of one of the issues, and the conclusion was it was AI, definitely part of the issue. But the other part of the issue was AI used by junior engineers. For me, it’s interesting. It shows that actually junior plus AI is actually a danger zone. That’s why many companies are going to be way more careful. “Why do we need the junior people if they are just playing with fire?” I think we go back to that situation of barbell, as you call it. The top talents are extremely valuable because they know how a production system works. They are here to develop better AI systems. But the junior guys playing with fires, yeah, maybe it’s cute in startups, but in a big time production environment, a different story.   Nuno Goncalves Pedro There will be a barbell with top-end talent super-mega paid and then mid-level talent that is individual contributors still doing a lot of great work, et cetera. Along the way, a lot of emptying of entry, a lot of emptying of the middle. Where does the talent go? The Three (?) Destinations I think we could say there’s three destinations for this talent. Maybe there’s four, maybe there’s more. Three that we can immediately identify. One is the AI native startup piece, where we have smaller teams that potentially get to a lot of revenue or top line over time, and where the Series Seed is the primary round, where we’re seeing Series Seed being raised of tens of millions of dollars, actually even hundreds of millions of dollars in Series Seed. In some ways, the stars there can get incredible compensations in terms of stock. They will stay for private and selling in secondaries later down the road because there’s so much capital at the table. Actually, in some ways, salaries are very high as well in some of these companies. It’s not like you’re trading off anything. You can get paid a lot of money. If your company at Series Seed for 10 or 15 employees has raised 50-$100 million, you can pay great salaries. In some ways, this is the extreme destination. The AI native startups that can make it is the extreme destination. Now, there aren’t a ton of AI native startups that can raise 50-100 million to 400 million in Series Seed, just to be clear. There’s a handful of hot deals in that space, but that’s one clear destination for top-end talent going through that. In that market, I think that’s one of the destinations. The second one is more what we would call the human-verified premium. It’s more of a play of companies that has still the need of human in the loop, either in terms of development, also in terms of activity, either because go-to markets are very intensive, and so therefore you need to have sales forces, partnership teams, et cetera. Or on the engineering side, it needs to have a lot of customization, integration. Companies are not just going to the, “Oh, you can come in and just apply your AI tooling and somehow magically the systems all work.” there needs to be quite a lot of and work and high touch work in getting stuff done. A significant part of that market, I’m not sure, is super VC investible. Maybe it’s a hybrid of private equity in VC, more PE style in many cases. It’s a PE-hold, sell to someone else market. As we’ve discussed in a previous episode on the SaaS-apocalypse, that hasn’t quite worked out for PEs. Question marks on how that human-verified premium market is going to evolve. But obviously, there’s a lot of work still to be done there, even on the engineering and science side. That’s the second potential destination. Then the third more aggressive destination is the reindustrialized middle companies that have a lot of specificity in going after small and medium businesses, local or regional affectations like ERPs or CRMs for specific markets, et cetera. Those are the three natural destinations. I would add the fourth, which is big tech. I mean, big tech doesn’t magically disappear, and I don’t think it fits neatly into any of these three markets. In some ways, big tech is now looking at the extreme for top talent a little bit like the AI native startup because they can pay. They can pay the 100 million every four years, et cetera. I do think it will typify taxonomically into a fourth type emerging, where, as we discussed, you’ll have top-end individual contributor talent. You’ll have the absolute top-end of the market because they can get paid. Then you’ll start having the emergence of earlier talent that is highly capable, et cetera. That will go back to a bit of a normal distribution in terms of talent on big tech. For me, those are the four destinations that I would put at the table.   Bertrand Schmitt For me, big tech moving to big tech, I’m not sure if it’s really a destination. I mean, yes, in some ways it’s a reshuffle between the big tech companies. They are definitely all fighting in some ways for some of the same people. I can see that dramatic shift where big tech has to remove a lot of positions in order to replace by AI. Again, I think at this stage, it’s mostly driven by AI coding. We are still at the beginning because this is brand-new phenomenon that AI coding is so successful at its task. I don’t think it was true even 6 months ago. Some companies, take Anthropic, take OpenAI, are definitely there or close to be there in terms of no more writing of a single line of code by a human, zero. This is, again, 6, 12 months ago. Not true. But now it’s true in a few top companies. Take OpenClaw as well, most successful GitHub project of all time, not a single line written by its author. It would have been impossible. We’re talking about hundreds of thousands of line of code in a few months. It’s impossible to achieve that manually. If you look at the other big tech companies, the Google of the world, the Meta of the world, the Microsoft of the world, they are absolutely not there yet. They are going to be there because they have no choice. It’s you either go fast there or you die. You are not going to be able to survive competitors that are shipping 10, 50, 100 times faster than you are shipping. It’s a life and death situation. All the big tech companies are going to move, and mark my word, in the next 2 years from 10, 20% of AI-written code to 100%. During that transition, the next 2 years max, if you don’t do it in 2 years, you are going to die. Your stock price is going to crash. Then, of course, you will have to make changes. You will have to invest more in GPUs. You will have to invest less in your standard typical software engineer employees. Like you, I’m very optimistic that there are new buckets. AI-native startups definitely will be there. It will be transformational. Human-verified premium, very interesting category. In a way, it will be businesses that are inevitably less scalable through AI, and there is definitely a spot from there. I think the biggest would be the reindustrialized middle SMBs. Most of S&P 500 type of business are going to dramatically offer new software opportunities, new opportunity story to talented software employees because they will need to implement AI in everything they do. They will do it. They will need people who have software engineering knowledge in order to implement these systems. For them, what’s changing dramatically really is that thanks to much cheaper cost as thanks to AI coding, a lot of software projects that they couldn’t afford to do, that they couldn’t imagine doing by themselves, they are able to do it. They will invest in a lot more software capabilities than ever before. That will be a big game changer. And software, very tuned to their business model. There might be less buying of your traditional off-the-shelf SAF software and a lot more investment in a highly custom software by their own team, assisted with AI. I think that would be the part that is most transformed by all of this in a positive way.   Nuno Goncalves Pedro Alternative Cap Tables, Alternative Compensation Models This will lead to a very fundamental shift, right back to the broken contract. What does the new contract look like? It looks like alternative cap tables depending on which bucket are you transitioning into. If you’re going into your AI-native bucket, and you’re a top-end talent, you’re like, “Dude, I’m worth 100 million over 4 years, so just compensate me accordingly with a mix of options in the company plus my salary.” If you’re top 1%, you can probably get away with salaries that you’d get anyway at mid-level from 300K, 400K and above, and you can get actually a lot of options already in the company. A lot of this is happening right now. There’s a premium for AI, we know that. There’s a premium for AI at the top end of AI researching, in particular on companies that are doing hardcore research on staff AI engineers, so companies that require actual AI engineering. There is a premium that is significant. It could be as high as 18% over non-AI peers, and it widens actually with seniority, shockingly enough. This is more of an average than anything else. Now, for me, and it’s for debate, but the perspective is this extreme comp will need to compress at some point. There will still be the haves and have-nots paid much better than the have-nots, so to speak, but there will be a compression. The variance can’t be the variance we’re seeing today for absolute top-end talent. That said, there will be variants. We know that big tech for over a decade, decade and a half, for example, in the Bay Area, has been paying a lot of money for director and above levels that used to be the VPs, so a million, a million and a half a year, all in compensations. It’s not unheard of that this will actually increase after this stage. That said, I do think that the compensation extreme that we’re in will get diluted down the middle. It will actually come down at some point. It’s part of where we are today. As we know, it is still a bubble.   Bertrand Schmitt Yeah, it’s an interesting point. I think it’s possible. At the same time, that compression coming 2, 3, 5 years. At the same time, we have examples where there is no such compression. Take the top sports players in the world, golfing, basketball, NBA players. There has not really been any compression at all. For me, it’s interesting. If you look at the big tech companies, each being one of this top NBA team, why would such compression happen? As long as they are competing against each other and generating plenty of cash, I think there will be some fair question. We will see. I don’t have a strong opinion, but for me, it’s not a total given.   Nuno Goncalves Pedro For me, the shocking thing is the faster AI becomes better, the more that compression will happen, because at some point, it’s like, why do you need the top talent as well? I don’t know. It feels like you’re trying to evolve a system that’s there to replace you. It’s like, “Okay, I’m getting paid 100 million over the next 4 years”, and then you develop something that’s so good that replaces you. Thank you. That’s cool.   Bertrand Schmitt That’s a total possibility, yes, because we are in that very unusual market where the game is to only replace yourself and people like yourself. At some point, it is a possibility, I guess this one. Right now, we’re talking about replacing your “average software talent”. In 2 years, could we absolutely replace the absolute best top experts in the world? Probably. I think it’s just that at some point we’ll be reaching the stage where we strictly have no control anymore on our AI systems because no human is able to challenge and understand what’s produced. It’s not just a question of scale anymore. We’re talking about a gap in IQ, basically.   Nuno Goncalves Pedro Exactly. It will happen at some point in history. We don’t know exactly when. For the second bucket, the human-verified premium bucket, it’s difficult to see how an HVAC company or an HVAC roll-up of scale or a regional health care platform or high touch go-to-market, B2B, SaaS play, et cetera, for a vertical will compete. At the same end, they have to compete and they will compete. There will be more and more jobs, we believe, for engineering talent in these companies. They’ll have to be more and more AI-enabled themselves. The cash salaries will have to be competitive within the local markets, not necessarily with Silicon Valley. There will be potentially profit sharing and revenue sharing and actual dividends played at the table. The model there on the cap table needs to change a little bit, needs to be probably propped up more on salary and on some way of doing profit sharing or actually having dividends paid to employees and figuring out employee to equity in a more aggressive manner. This is the market that probably was already very attacked, so to speak, or let’s say, occupied by private equity firms. There are still obviously part of that model that would work well. There needs to be a fundamental shift, certainly on the quantum of salary compensation, dividend compensation, profit sharing, and all of that. Then last but not the least, obviously, we had the bucket around basically the reindustrialization of the middle, so everything else, which will take most of the belly that we were talking about. This is probably a poor analogy, the belly fat. It’s not belly fat, it’s people that were doing their jobs that now are getting disrupted. In some ways, that bucket will absorb a lot of that belly, will absorb a lot of talent. The small and medium businesses that Bertrand was saying will need to crucially become more AI, software-enabled by themselves, even with some core stuff and underpinnings that actually might not even require AI in terms of infrastructure platforms. There, you need to get properly paid. Again, how many people do you need in your engineering team if you’re a small business? Probably not a lot. It’s maybe you need one or two people and that’s it. They’ll need to be very nicely paid because they’re running the stuff in the rails. This is probably a market that over time, as AI gets more and more competent, will also be disrupted, but let’s not talk about the disruption to the disruption because otherwise, we’ll stay here the whole day, but certainly a market that has a lot of potential to shift and to absorb a lot of the moments that we’re seeing in terms of layoffs happening in the US in particular.   Bertrand Schmitt This category was a category that historically could not compete with Silicon Valley salaries, could not attract the most talented engineers. It’s not a category that didn’t want to bring these people on board. It’s a category that just couldn’t afford to bring this talent on board, typically. I think it would be a dramatic shift for them when suddenly there are opportunities to hire these people. There is an opportunity to hire them at maybe more reasonable prices from this company’s perspective. You talk about small companies, the great thing is that there are millions of small companies at some point. I think things could be truly transformational. Of course, some of these engineers, software engineers, might decide to become entrepreneurs on their own. Solo entrepreneurs, small businesses, build their own, easier to build their own product to market so to serve other companies. I think there will be quite dramatic changes because not all companies will be disrupted by AI as much, but not every company will benefit from improving processes, improving software through AI. At least early on, you will need this human touch to make it work inside a business. Interestingly enough, I was hearing that some companies like IBM were hiring more younger people to do the work of going to the client, understand their needs, propose implementation plans. That forward deployed engineer, those positions, I think there will be more and more available.   Nuno Goncalves Pedro Investor Landscape Fragmentation What happens to investor into the landscape? We already had an episode, the previous one, Episode 76, where we talked quite a lot about the big capital reset on the private equity and private reset, including venture capital. Just maybe to summarize, how does it align with the buckets that we’ve just been discussing? I think the AI-native bucket clearly is going to be the key bucket. There, we’re going to see two movements. One movement, which is the mega funds, as we discussed in the last episode, are no longer just VC funds. They’re really mostly multi-asset private equity funds, maybe even private equity hedge funds in some cases. Those funds will be all over the high-growth AI-native companies and will be pouring money into companies that are scaling really, really quickly. The early stage, so to speak, VCs, the actual VCs that will stay in the market will be the guys probably identifying the next big wave of AI-native companies. We’ve discussed that as well in the last episode, some research that we did at Chamaeleon that I shared in episode 76. We’ll see that as emerging. What happens to the second bucket, the bucket around human premium, human in the loop? Likely we’ll have more and more private equity capital going into it and the large-scale VC guys, the Thrives of the world, they’ve just announced Thrive Holdings, and others going after those markets as well. It’s trying to converge into the private equity market, which aligns with the point we made in the previous episode that the VC mega funds are no longer VC, that they are private equity, multi-asset class. They’re going after a bunch of things. There’s a conversion happening from VC into private equity. It was going to happen anyway because the private equity guys were coming into VC as well and the hedge funds were coming to VC as well. There’s a convergence in the middle of very, very large funds and large assets under management happening to go after some of these opportunities, certainly in Bucket B. Then this Bucket C, so to speak, the bucket of reindustrialization, as Bertrand was saying, very well, likely will be self-funded for a significant period of time. Will self-fund with their own cash flow. Doesn’t need to have a ton of capital intensity. Maybe you need one or two engineers to do stuff, but that’s it. You don’t need tons of capital. You didn’t need in the past, you won’t need it today. Not sure there’s going to be a fundamental shift to that market.   Bertrand Schmitt Yes, I certainly, overall, agree with you. That last pocket, probably little change to the capital and capital structure. Again, I see that as the biggest opportunity for a lot of people who might be less needed by big tech and also top tech companies. What is sure for the first category, the high native startups? I would say more overall in the VC ecosystem, there is no space left for SaaS anymore. I think SaaS, as we used to know it, is dead in some ways in the sense that new pure SaaS software startup are definitely out. Existing ones that are critical to run your infrastructure, the Salesforce of the world, I think they’re in a decent spot. Actually, interestingly, they changed their pricing model to now sell to AI agents, not just per seat. There is a change in pricing there. But this day and age of funding a pure SaaS software startup through VC money, no way. VC money going to AI-native startups, AI-focused startups, to biotech, to deep tech, to defense tech, yes. SaaS as a fundable category early on, I think it’s over.   Nuno Goncalves Pedro I’m a bit more nuanced as we shared in The SaaS Apocalypse episode. We can call it whatever we call. It’s applied AI is the new SaaS thing. Horizontal applied AI is the new horizontal SaaS or vertical applied AI is the new vertical SaaS. I agree in common with your point that very specific point solutions around SaaS will be disrupted by nature with all the easy stuff you can do today with AI. It will take a while. This is not something that’s going to happen this year. It’s going to happen over the next years. Maybe interesting to also talk about the exit markets. I think the IPO market, as we’ve also discussed in the past, there is, in my view, going to be a reopening of the IPO market, I think this year, probably later in the year, third or fourth quarter. The median time to IPO actually is going to be really weird because there’s going to be potentially some companies in the current landscape, bubble or no bubble, that are going to IPO, the OpenAIs of the world, Anthropics of the world, et cetera. There will be more and more aggression, I think, on M&A. Big tech has already shown it, that they want to buy into markets. Large non-tech companies have also started doing acquisitions in space. To prop up their IT teams, their engineering teams with this world that we’ve also discussed in previous episodes that I’m going to own my own engineering stack for now. As we see, that normally doesn’t withstand the test of time. At some point it will get unbundled and served by someone else. Then finally, the secondary market is very hot right now. Obviously, there’s heavy discounting on some areas, high premiums on others. The exit market, strangely enough, is going to be propped up, in my opinion, over the next year to 2 years, dramatically. Then we’ll see if there’s a big reckoning around the bubble that we are clearly in or not, if it’s a soft landing or hard landing. Definitely, there’s going to be a lot of exit paths over the next year to 2 years.   Bertrand Schmitt Concerning the “bubble”, I have two perspectives on this. One is it’s a bubble in the sense that money is going to a lot of players and some players are going to blow it up. There will be a concentration of players at the end, like it usually happens. If you look at, for instance, long time ago, the railway revolution, there was that intense influx of capital. At the end of the day, there was a dramatic change in transportation in the US and a complete railway system put in place. Yes, some investors lost money, some companies went bankrupt, but the transformation was fully real. There were a lot of top leaders at the end of this revolution. The change after that only happened, we guess, post-World War II, with the construction of the highway system and the rise of airlines and plane transportation overall. Here I feel it’s similar in the sense that, yes, there is a lot of money going in. Some players are going to blow it. They will misuse the money in different ways, but that’s part of dynamic allocation of capital. Of course, you make mistakes. That’s what happens. At the same time, I feel it’s a similar level in the sense of this is a dramatic change in the US infrastructure. This buildup of AI data centers filled with GPUs, integrated at scale with some of the best software in the world and running it, supported by a dramatic shift in energy infrastructure. This is for me similar to the Railroad Revolution. Some players might not own the data center they build because they didn’t manage well their debt, they didn’t manage to run proper software. You know what? They will get acquired by somebody else. I think we are at this level of fundamental transformation. The fact that in a matter of maybe 2 years, the move from 0% of code written by AI to 100 % written by AI is an insane dramatic shift. Just to be clear, when you move from manually coded to AI coded, we’re talking about a 100X difference in terms of speed at similar, if not better level of quality. The shift is dramatic, and on top of it, you don’t pay salaries anymore to achieve that. You pay CapEx, and with GPUs and OpEx with electricity. It’s a very big shift, positive shift in business model. New unions, no management over it, AI working 24/7. Personally, I think for me, bubble has a bad connotation in the sense of it was all for a waste. I don’t think it’s all for a waste. I think we are witnessing a dramatic revolution of our lifetimes, quite frankly, bigger than SaaS, bigger than mobile. From my perspective, it’s exciting times.   Nuno Goncalves Pedro Operator Playbook and Predictions Let’s move to if you are this person, what would you do in the future? Let’s start with two extremes and go from there. One is you’re non-tech, so you’re not an engineer, et cetera. You’re trying to figure out, how do I scale my activity? Maybe physical labor is where I want to go. It’s not, “Go west” anymore. Definitely not necessarily go west. You should go to, I guess, the states that have no sales tax with very cheap energy because that’s where the data centers are being built if you want to be in that market. Obviously, there’s a lot of stuff that needs to be done: HVAC, electricity work, et cetera. Don’t go west. Go low sales taxes, low cost of energy. That’s likely where the data centers are being built. You probably can just follow. There’s, I’m sure, some way for you to follow where the data centers are being built, but that’s next, I think on that extreme of the table. The other extreme of the table, let’s say you are super ambitious, maybe you’re no longer an engineer, but you’re a product manager in your prompt engineering. You could do prompt engineering all day long. You’re 28, 29-year-old superstar. What do you go and do? Likely either you start your own thing, start your own company because you’re so good at prompt engineering, you probably can do a lot of the code yourself, particularly if you have an engineering background, or you go and join very early an AI-native startup that you think has the chance of going through the roof, and you take a pretty good salary early on, a ton of upside on the company because guess what? Companies like that need product managers. They need people to figure out UX, UI. It’s not going to be, at least for now, yet AI figuring that out for you. Those are two extremes, just to give two of the extremes, like engineering, product management persona, and physical labor at the other extreme, non-tech, et cetera.   Bertrand Schmitt In some ways, every software engineering job is going to become the equivalent of a software engineering manager or a product manager, because suddenly you don’t have to do the coding anymore. You’re managing AI that is coding for you. Either you start to have some manager hat, but we saw the humans, so it’s a very different type of manager, obviously, or you are going to be really an empowered product manager. You’re skipping the middleman. You’re skipping the traditional engineering organization because your engineering organization is AI running and doing the work for you. I still believe that it requires some serious skills. I don’t believe in the vibe coder type of value proposition. I don’t believe in the prompt engineer becoming suddenly super incredible, able to manage that. I still think it requires some serious chops to do the best from all of this and to do it in a safe and sane way. It’s very easy to have poor taste, make mistakes. I don’t know you, but keep reading these stories on the heads of companies who lost everything because of the AI agents. That deleted stuff in production, and they had no backups or the backups weren’t deleted as well. Crazy situation. You cannot run companies like this if you let your agents running wild. You could argue it’s the early days. I would argue it that that issues would be there for a while. You need to have some engineering discipline at core in the company running the business to make sure things don’t go sideways because it would be easy for things to go sideways.   Nuno Goncalves Pedro I totally agree. If you’re thinking, Oh, should my kid go into science and engineering and computer science, et cetera? Absolutely, still, because of everything that Bertrand just said. You need to understand actually what code does and what technology does and what all of that does. That’s still a skill of the future. It’s not a skill of the past. In some ways, it’s still a skill of the future very much. Maybe let’s try two more extremes. Around the same level, the person that decided to do an AI native company bootstrapped initially, having difficulty raising a mega round, but could probably get away with raising a 2-3 million seed round, et cetera. Is that still viable? The answer is yes. There’s tremendous capital efficiency right now happening in the market still, 10 plus higher than if you were doing a SaaS company, and you were a founder in 2019 or something like that. That capital efficiency is going to reverberate. You can run a tighter team, smaller team. Actually, you don’t need that many salaries. If you’re a decent engineer as a founder or if you understand enough as a product manager to just generate that code, you can do a lot of stuff yourself, can bring in maybe one or two technical elements to the team early on as you would have done if you were bootstrapped anyway. There’s obviously a path for that. The other extreme is you’re in big tech, you’re level five, individual contributor, making a ton of money, or you were a manager, and you’re now out of a job, where do you go? You can go to a big company that is non-tech, S&P 500 company that’s non-tech, something like that. You join the company, you’ll probably get paid pretty well, maybe not as high as you were paid in big tech. There’s some stock at the table, but guess what? You’ll have probably more work-life balance than you ever did. That’s the trade-off. You’ll have a better job. On the upside, you can transform the company. You can help and be part of transforming a company from non-AI to AI-first or AI-enabled in the future, whatever BS that will look like in terms of the argumentation to the board. You can actually create tremendous productivity enhancements in a big non-tech company if you come with that background. Again, you’ll have certainly a better work-life balance, so not a bad deal, to be honest.   Bertrand Schmitt Also, to be clear, I talk a lot about AI coding because it’s truly transformational. You could argue that it’s going to be self-improving. We are in the situation of a self-improving AI that keeps improving itself thanks to automated coding. It’s a dramatic, virtuous loop. Obviously, AI is also going to improve everything else. It’s going to improve your marketing, it’s going to improve your search process, it’s going to improve your DNA. Improvements will be everywhere. It’s just that right now we are at a point in the quote-unquote revolution where there is one clear piece of the puzzle that is moving faster than the rest.   Nuno Goncalves Pedro Bertrand, the senior executives at non-tech don’t know anything about that. It could be just a great prompt engineer. That’s the only job you do. “I’m the chief marketing officer. I have someone below me that’s doing the whole work.” Nobody knows. Nobody’s the wiser, I guess. I’m being facetious, but not fully.   Bertrand Schmitt Yeah. There would be a transition period where what you described happen. I want to say, going back to AI coding, I think that the part of AI that as of today has reached a stage of limited AGI. We have reached, from my perspective, a limited type of AGI for coding. If you take coding as a discipline today, I think we reach AGI. If you go beyond coding, that’s true. If we are talking about coding, leveraging the latest LLMs: OPUS 4.7, ChatGPT 5.5, combined with Claude Code, Codex, and OpenCode for harness, I think we’ve reached AGI in the context of coding. I’m not sure everyone fully realize that and the consequence of that. I think the rest is going to come as well. We are going to see that category by category, usually categories that are more scientific in nature, where you can replicate, where you can test easily, where you can create clear success. Metrics will be the “easiest” to follow in that direction of self-improvement. I just want to highlight that this part is truly transformational, the root cause of everything we’re talking about today. At the same time, it’s coming beyond coding.   Nuno Goncalves Pedro I think it is true. There are a couple of markets where that might not hold true, which is maybe the final path. If you’re thinking of starting your own business in plumbing and in HVAC maintenance and installation, this is a pretty good time for the reasons we already said before. There’s a lot of buildup of data centers and all that stuff, but also for other reasons, because it’s an activity that won’t be disrupted by AI yet. You need them embodied AI. You need physicality to AI to do stuff like actually fixing pipes.   Bertrand Schmitt Until Optimus replace you.   Nuno Goncalves Pedro Yeah, but if we’re 3, 4 years out in terms of a lot of these optimizations that we’re talking about at the software layer, we’re 10 years plus out on embodied AI, right?   Bertrand Schmitt Oh, yeah, it’s 10 years.   Nuno Goncalves Pedro We’ll probably be optimistic as we speak. That’s a nice business. I’m thinking of starting to go into that market. If you guys are interested in listening to this, just reach out to me. What’s the angle? I think there’s a lot of stuff you can do in the buildup of some of these businesses, plumbing, HVAC, all sorts of maintenance. There are markets that are just totally messed up. Handyman market in the US is totally messed up. There’s a bunch of companies out there that try to go after it with marketplaces and stuff. I honestly just start something from scratch, a small business, and go from there.   Bertrand Schmitt Yes. They’re an interesting middle. Think about accounting firms, consulting firms. I think they are not as easy to replace, but at the same time, there is no way on what they do is not going to be dramatically changed with AI. I don’t know if it’s 50, 80, 90% of the job, but this is changing quite dramatically, would be my expectation in the coming few years. Conclusion Thanks for listening episode 77 of Tech Deciphered about that great talent redistribution. As you heard it from us, we believe there is a dramatic change in play, enabled by AI coding, and that ultimately a lot of the big tech companies are changing their employee distribution, way more focused on the top talents and bringing more GPUs. As a result, we will see a change in their staffing. Some of this change will benefit AI-focused startups, but probably more likely will benefit the bigger SMBs, the S&P 500 companies of the world that will finally be able to bring inside and afford some of the talent that were in some ways trapped by the top 5, 10, 20 software companies of the world. Thank you, Nuno.   Nuno Goncalves Pedro Thank you, Bertrand

Send us Fan MailRecent announcements across the enterprise software landscape highlight an accelerating convergence of AI, integration, and industry-specific innovation as core pillars of modern enterprise architecture. Oracle continues to expand its footprint with new capabilities across financial services, process manufacturing, and AI agents embedded within Oracle Fusion Cloud, reinforcing the shift toward intelligent, industry-aware ERP ecosystems. At the same time, Sage is advancing AI-driven enhancements in Sage X3, while NetSuite is strengthening composability through its new integration platform. Beyond core ERP, ecosystem players such as ActiveCampaign, Bombora, and Omilia are embedding intelligence into customer engagement and data workflows, while emerging innovators like Fibr AI attract funding to push experimentation at the edge. Strategic partnerships, including QAD and Tata Consultancy Services, further signal the importance of services-led transformation. Collectively, these moves reflect a broader structural trend: enterprise platforms are evolving into tightly integrated, AI-augmented ecosystems where domain specialization, real-time intelligence, and composable architectures define competitive advantage.In today's episode, we invited a panel of industry analysts for a live discussion on LinkedIn to analyze current enterprise software stories. We covered many grounds, including the direction and roadmaps of each enterprise software vendor. Finally, we analyzed future trends and how they might shape the enterprise software industry.Video: https://www.youtube.com/watch?v=HtcFOMAANWMQuestions for Panelists?

Most conversations about nearshoring assume you're moving away from Chinese manufacturing. Kerim Kfuri, president and CEO of The Atlas Network, has a harder truth: a lot of "nearshoring" is just Chinese foreign direct investment building factories in Vietnam and Mexico. The geography changes. The supply chain dependencies don't necessarily change with it.In this episode, recorded live on the expo floor at the Logistics World Summit in Mexico City, Kerim breaks down what 20 years of building end-to-end supply chains for small and mid-sized businesses has taught him — and what most operators still get wrong.In this episode:How The Atlas Network manages the full supply chain lifecycle for SMBs, from product idea to inventory management, across a network of 2,000 vetted factoriesWhy "nearshoring" in Vietnam and Mexico often means Chinese-owned factories with Chinese standardization — and why that matters for your tariff and sourcing strategyThe US manufacturing reality: why technology (not policy) is the actual leveler, and why we can't snap our fingers and rebuild a workforce we stopped training decades agoKerim's keynote framework from Logistics World: people, process, and innovation — and why "people" is the most undervalued of the threeWhat Kerim (MIT degree in AI and Strategy) says you actually give up when you hand too much to AI: creativity, human factor, and the interpersonal relationships that drive real businessThe signal-versus-noise framework for entrepreneurs: how to identify the three things that must get done today and stop letting everything else winWhy the most common thing Atlas Network hears from new clients is: "I wish we knew about you sooner"A bonus live interview with the founder of Logistics World Summit, who walked up mid-recording on the expo floorWatch this episode on YoutubeLinks & Resources:The Atlas NetworkKerim's book and speaking websiteBlythe's Logistics World + Mexico City Recap -----------------------------------------THANK YOU TO OUR SPONSORS!SPI Logistics has been a Day 1 supporter of this podcast which is why we're proud to promote them in every episode. During that time, we've gotten to know the team and their agents to confidently say they are the best home for freight agents in North America for 40 years and counting. Listen to past episodes to hear why.CargoRex is the search engine for the logistics industry—connecting LSPs with the right tools, services, events, and creators to explore, discover, and evolve.Digital Dispatch maximizes and manages your #1 sales tool with a website that establishes trust and builds rock-solid relationships with your leads and customers. 

Join Kat and Ian as they stumble through the basics of DRIP (yes, we finally figured it out!), share some questionable life advice for surviving a seven-hour meeting marathon, and geek out over why Multi-Factor Authentication (MFA) is the ultimate digital bodyguard. We're breaking down the "something you know, have, and are" magic that blocks 99% of attacks, and why that extra verification step is actually your best friend, not a nuisance. Plus, Ian drops some secret lore about his past life building cybersecurity programs. Get your MFA ready, and let's get into it! Check out Cisco's cybersecurity solutions (like MFA) for SMBs here: https://www.cisco.com/site/us/en/solutions/small-business/security/index.html

In this episode, Chris Johnson sits down with Eric Shoemaker of Genius GRC to unpack one of the most misunderstood shifts in the MSP space: the move from tool-driven cybersecurity to standards-aligned governance, risk, and compliance programs.Eric explains why Genius GRC isn't a software platform and why that distinction matters. Together, they explore how early automation wins (like continuous access reconciliations) impressed auditors but didn't replace the need for real governance, documented reviews, and independent judgment. As the market matures, the conversation turns to a growing risk: MSPs and SMBs stacking new security tools while core systems remain misconfigured and under-governed.Chris and Eric tackle the myth of “do-it-yourself” GRC, the dangers of vibe-based compliance, and why tools only amplify expertise; they don't replace it. They also dig into the critical separation between IT operations and security leadership, making the case for advisory or independent CISO models that reduce conflicts of interest and improve risk outcomes.The discussion closes with practical, budget-conscious fundamentals, such as DNS filtering, CIS IG1, and free or low-cost controls that actually move the needle, plus hard truths about negligence versus resourcing failures and why resilience must be budgeted from day one.If you're an MSP, consultant, or business leader navigating cybersecurity maturity, this episode is a grounded, no-hype look at what actually reduces risk.

Send us Fan MailLarge enterprises approach ERP through a fundamentally different lens, where the system serves not as a tool for day-to-day execution but as a coordination layer for a complex, global ecosystem spanning multiple countries, regulatory regimes, and business models. Typically starting at $1 billion in revenue and extending well beyond $5 billion, these organizations prioritize financial consolidation, governance, and compliance at scale, often adopting best-of-breed or two-tier ERP strategies to balance centralized financial control with decentralized operational flexibility. Implementation timelines are long and capital-intensive, frequently spanning several years, as enterprises navigate acquisitions, divestitures, and evolving operating models. In this context, ERP systems must support deep multi-entity structures, localization requirements, and intercompany complexity without forcing rigid standardization across all business units. This is why evaluating ERP for large enterprises requires an architectural perspective that aligns system design with organizational scale, and why this 2026 list focuses on solutions built for global resilience—helping leaders reduce long-term implementation risk while enabling continuous transformation across the enterprise.In this episode, our host Sam Gupta discusses the top large company ERP in 2026. He also discusses several variables that influence the rankings of these ERP systems. Finally, he shares the pros and cons of each ERP system.Video: https://www.youtube.com/watch?v=um_l8xeAysIRead: https://www.elevatiq.com/post/large-company-erp/Questions for Panelists?

On this episode of Small Biz Florida, host Tom Kindred sits down with Fred Lenz, Founder and Managing Partner of Margin First Advisors, to discuss how small and medium-sized businesses can uncover enterprise-level cost savings without upfront consulting fees. Fred shares how his company helps SMBs improve margins through healthcare cost mitigation, IT optimization, tax incentives, AP automation, and other specialized solutions typically reserved for large corporations. He explains Margin First Advisors' unique no-risk business model, in which clients pay only after savings are realized, and takes a deep dive into a healthcare program that leverages Affordable Care Act provisions to reduce employer healthcare expenses while generating significant FICA tax savings. The conversation also explores the growing role of virtual healthcare, automation, and proactive cost management strategies for businesses navigating economic uncertainty. Connect with our guest:  https://margin1st.com/

Send us Fan MailEnterprise software is undergoing a structural transformation as AI-native ERP platforms redefine how organizations manage financial control, operational orchestration, and decision-making by embedding intelligence directly into the transactional core rather than relying on rigid workflows and manual inputs. This webinar provides an independent, in-depth review of Everest ERP, examining its AI-first architecture, automation capabilities, and data orchestration framework while comparing it against both legacy ERP systems and emerging AI-native alternatives. The focus goes beyond surface-level features to evaluate structural dimensions such as scalability, governance, financial automation, and operational control—areas that increasingly determine long-term success. By connecting these capabilities to real-world ERP selection decisions, the session equips leaders with a clear understanding of AI-native readiness, where these platforms deliver the most strategic value, and how to avoid common pitfalls driven by outdated evaluation frameworks, ultimately enabling faster, more confident, and future-ready ERP decisions.In this episode, Sam Gupta and Shrestha Dash from ElevatIQ, Andy Pratico from Essential Software Solutions, and Phil Coerper from Ringling Business Solutions conduct an in-depth independent review of a leading AI-native platform Everest ERP.Video: https://www.elevatiq.com/events-and-webinars/everest-erp-an-independent-in-depth-review/Questions for Panelists?

In this episode of Reimagining Cyber, host Rob Aragao sits down with MK Palmore to explore why small and medium-sized businesses are becoming prime targets for cyberattacks — and why traditional enterprise security models often fail them.Drawing on more than three decades of experience across the FBI and Fortune 500 leadership roles, MK shares how SMBs can rethink cybersecurity through a more scalable, cost-effective “fractional CISO” approach. The conversation covers the biggest mistakes growing companies make, why reactive security strategies create long-term risk, and how organizations can build security maturity without enterprise-sized budgets.Rob and MK also discuss:Why SMBs are disproportionately impacted by cyber threatsThe pitfalls of trying to replicate Fortune 100 security teamsHow fractional cybersecurity leadership accelerates growth and resilienceThe importance of embedding security early in product developmentHow AI agents could transform cybersecurity operations and compliance in the years aheadA practical and forward-looking conversation for business leaders, security practitioners, and growing organizations navigating today's evolving cyber landscape.As featured on Million Podcasts' Best 100 Cybersecurity Podcasts  Top 50 Chief Information Security Officer CISO Podcasts Top 70 Security Hacking PodcastsThis list is the most comprehensive ranking of Cyber Security Podcasts online and we are honoured to feature amongst the best!Follow or subscribe to the show on your preferred podcast platform.Share the show with others in the cybersecurity world.Get in touch via reimaginingcyber@gmail.com

Send us Fan MailRecent developments across the enterprise software landscape underscore a dual narrative of rapid AI-driven innovation alongside growing skepticism around how value is measured and delivered. Critiques such as the limited practical relevance of metrics like AWU from Salesforce highlight the disconnect that can emerge between vendor messaging and CIO priorities, even as the broader ecosystem accelerates toward agentic and automated capabilities. Companies like Incubeta and Intentsify are expanding data-driven and agentic offerings, while Klaviyo integrates with ChatGPT to embed conversational intelligence into marketing workflows. Enterprise application vendors are also advancing domain-specific innovation, with Unanet targeting GovCon growth automation, Aptean enhancing routing intelligence, and Oracle and Sage introducing AI-driven enhancements across financial services and ERP platforms such as Sage X3. Meanwhile, partnerships like Cognizant with Uniphore and acquisitions such as ActiveCampaign acquiring Feedback Intelligence reinforce a broader trend: enterprise systems are increasingly converging around AI-infused automation, but buyers must remain vigilant in distinguishing substantive capabilities from surface-level innovation narratives.In today's episode, we invited a panel of industry analysts for a live discussion on LinkedIn to analyze current enterprise software stories. We covered many grounds, including the direction and roadmaps of each enterprise software vendor. Finally, we analyzed future trends and how they might shape the enterprise software industry.Video: https://www.youtube.com/watch?v=usuYQZcFrRQQuestions for Panelists?

On this special episode, Pete welcomes John Kostoulas, VP of Market Positioning & Strategy at Dayforce and former Gartner Vice President and distinguished HCM tech analyst, for a candid conversation on the future of HR technology, AI adoption, and what it really takes to modernize in the era of agentic AI. John shares his journey from an engineering graduate in Greece to an HCM vendor executive and what the "analyst in him" still sees that most miss. He brings research-backed insights on the AI governance gap, and why trust, not features, is the real barrier to adoption at scale. He also delivers a sharp, no-nonsense framework of AI transformation do's and don'ts for executives who are paralyzed or unsure where to start, including why chasing feature lists over outcomes is the fastest road to regret. The conversation explores the growing "vibe coding your HCM" phenomenon, debating whether SMBs and enterprises can realistically AI-generate their way to payroll and HR solutions. Plus, they talk about the critical difference between a truly unified HCM platform and a fragmented "unified" illusion, and why that distinction is make-or-break for enterprise agility. Connect with John: LinkedIn: https://www.linkedin.com/in/johnkostoulas/ John's Post on unified consolidation and AI features: https://www.linkedin.com/feed/update/urn:li:activity:7439258950371344385/ Connect with the show: LinkedIn:  http://linkedin.com/company/hr-payroll-2-0 X: @HRPayroll2_0  X: @PeteTiliakos  X: @JulieFer_HR BlueSky: @hrpayroll2o.bsky.social YouTube: https://www.youtube.com/@HRPAYROLL2_0  WRKDefined Podcast Network: https://wrkdefined.com/podcast/hr-payroll-20  Thank you to our marquee sponsors for powering HR & Payroll 2.0 podcast forward!  G-P ‘Globalization Partners': https://www.globalization-partners.com/  OneSource Virtual: https://hubs.ly/Q03YFNR90 Zoho: https://www.zoho.com/press.html Thank you to our ‘wizard behind the curtain' and show producer Ryan Kielma: https://www.linkedin.com/in/ryan-kielma/

Send us Fan MailMid-sized businesses operate in a distinctly more complex ERP environment than startups or small companies, where growth introduces multi-entity structures, geographic expansion, and increasingly formalized processes that elevate ERP from a visibility tool to a coordination layer across the enterprise. Typically spanning $100 million to $1 billion in revenue, this segment is far from uniform—lower mid-market organizations still prioritize simplicity and cost control, while upper mid-market firms begin to mirror large enterprises with needs such as global consolidation, intercompany accounting, and stricter compliance requirements. Across this spectrum, ERP systems must support shared services models, deeper intercompany relationships, and scalable governance without sacrificing flexibility for continued growth. This is why evaluating ERP for mid-sized businesses requires an architectural lens that balances operational depth with organizational scale, and why this 2026 list focuses on solutions purpose-built for the mid-market—helping executives navigate the transition with a structured framework that minimizes implementation risk while aligning systems with evolving business complexity.In this episode, our host Sam Gupta discusses the top mid-sized business ERP in 2026. He also discusses several variables that influence the rankings of these ERP systems. Finally, he shares the pros and cons of each ERP system.Video: https://www.youtube.com/watch?v=L4qJLO7QtVcRead: https://www.elevatiq.com/post/mid-sized-business-erp/Questions for Panelists?

Scaling with Intention: Building the Modern Operating System with Damon FlowersIn a recent episode of The Thoughtful Entrepreneur Podcast, host Josh Elledge sat down with Damon Flowers, the Founder of modernoperators.com, to discuss the structural evolution required to scale a small-to-medium-sized business (SMB) in the age of artificial intelligence. Damon, a seasoned entrepreneur with two eight-figure exits and four CEO roles to his credit, shares his expert perspective on why the current "patchwork" approach to business software is the primary bottleneck for founders. This conversation serves as a strategic roadmap for leaders who are currently working 70-hour weeks and feel trapped by their own success, offering a path toward true operational freedom through a centralized, AI-enhanced core operating system.The Architecture of Efficiency: Transitioning from Fragmentation to a Core SystemThe modern business landscape is often characterized by "SaaS sprawl," where an SMB might rely on 15 to 25 disconnected tools for CRM, project management, and finance, leading to data silos and extreme founder burnout. Damon Flowers argues that true scalability is impossible without a core operating system—a central hub that orchestrates people, processes, and data into a single source of truth. When a founder remains the primary bridge between these disconnected tools, they become the ultimate bottleneck, preventing the business from functioning independently. By centralizing data and automating routine data flows, a leader can transition from tactical firefighting to strategic oversight, ensuring that the business is built to scale or exit rather than just survive the week.AI represents the next great frontier for operational excellence, but only if it is integrated into a strong existing foundation rather than "bolted on" as a temporary fix. Many founders face anxiety regarding AI, fearing it may disrupt their culture or replace human talent; however, when aligned with a core system, AI acts as a massive force multiplier for fulfillment and customer service. Modern Operators utilizes a hybrid model that combines high-level management consulting with an AI-powered platform to ingest transcripts, web data, and founder input. This allows for the rapid generation of standard operating procedures (SOPs), brand avatars, and vision statements that are uniquely tailored to the organization's DNA, drastically reducing the time required to build a sophisticated infrastructure.Escaping the "founder's trap" requires a disciplined shift toward role clarity and process documentation. Damon suggests that most SMBs mistake payment platforms or task managers for an operating system, but a true system is what defines how information moves and how decisions are made. By implementing role-based access and clear decision rights, staff members are empowered to act without constant oversight, which significantly increases organizational agility. Founders should focus on a 90-day implementation sprint to establish this core, allowing them to step up the value chain where they can focus on culture, high-level partnerships, and long-term vision. In a world of shiny new tools, the winners are those who prioritize the structural integrity of their core operations.About Damon FlowersDamon Flowers is the Founder of Modern Operators and an elite business strategist with a track record of building and exiting high-value companies. Having navigated two eight-figure exits and served as CEO for four different organizations, Damon brings a rare level of "in-the-trenches" experience to his consulting work. He is dedicated to helping SMB founders regain their time and sanity by implementing the same sophisticated operating systems used by global enterprises.About Modern OperatorsModern Operators is an operational consulting firm and technology platform designed to help SMBs build scalable, AI-enhanced foundations. The company provides a unique hybrid of management consulting and custom-built software solutions that integrate seamlessly with tools like Notion. Modern Operators specializes in 90-day implementation cycles, helping founders document their vision, automate their processes, and prepare their businesses for rapid growth or lucrative exits.Links Mentioned in This EpisodeModern Operators Official Website: modernoperators.comDamon Flowers on LinkedIn: linkedin.com/in/damonflowersKey Episode HighlightsThe Fragmented Tech Trap: Identifying why 15-25 disconnected SaaS tools create a bottleneck that forces founders to work 70+ hours a week.The Core System Concept: Defining the difference between a standalone "tool" and a true operating system that orchestrates people and data.AI-Powered SOPs: How to use call transcripts and founder input to automatically generate vision statements and operating procedures.The 90-Day Sprint: Modern Operators' framework for rapidly building a scalable infrastructure and exiting the "tactical" stage of leadership.Exit Readiness: Why having a centralized, documented system is the single most important factor in making a business attractive to eight-figure buyers.ConclusionThe conversation with Damon Flowers highlights that the "founders trap" of overwork is almost always a symptom of a fragmented operating system. By centralizing business data and thoughtfully integrating AI, leaders can build resilient, autonomous organizations that thrive without requiring 70-hour workweeks from the CEO.More from The Thoughtful Entrepreneur

Send us Fan MailManufacturers continue to face persistent challenges in sales and inventory forecasting due to fragmented data spread across ERP, CRM, and operational systems, leading to inconsistent inputs and downstream consequences such as excess inventory, stockouts, cash-flow strain, and missed revenue opportunities. This webinar addresses these issues through a practical, real-world use case, demonstrating how disciplined processes and system alignment can significantly improve forecasting accuracy. It showcases how an Algorithm customer leveraged Acumatica in combination with DataSelf to unify disparate data into a single source of truth, eliminating reliance on spreadsheets and enabling scalable, system-driven forecasting. More importantly, the session illustrates how BI-powered forecasting transforms executive decision-making—from reactive variance analysis to proactive, forward-looking planning—allowing leaders to optimize inventory levels, reduce carrying costs, and improve service outcomes, positioning forecasting not merely as a reporting function but as a strategic capability grounded in clean data and tightly integrated systems.Video: https://www.elevatiq.com/events-and-webinars/accurate-forecasting-in-manufacturing-a-customer-case-study-with-erp-and-bi/Questions for Panelists?

Send us Fan MailRecent announcements across the enterprise software ecosystem highlight a clear pivot toward agentic AI, ecosystem orchestration, and embedded intelligence within core business platforms. Salesforce is advancing this shift with MuleSoft Agent Fabric, enabling automated agent discovery, while ServiceNow is doubling down through expanded partnerships with OpenAI and Anthropic to operationalize AI agents in mission-critical workflows. Strategic collaborations such as Cognizant partnering with Typeface and Uniphore further reinforce the growing importance of composable AI ecosystems. Meanwhile, application-layer innovation is accelerating, with Simpro Group expanding its AI-first platform via acquisition, Klaviyo integrating with ChatGPT, and Unanet and Aptean introducing automation and routing capabilities tailored to vertical use cases. At the same time, data and demand-generation players like Intentsify and Incubeta are embedding agentic capabilities into their offerings, collectively signaling a broader transformation: enterprise platforms are rapidly evolving into interconnected, AI-native environments where intelligent agents, data, and workflows operate as a unified system rather than siloed functions.In today's episode, we invited a panel of industry analysts for a live discussion on LinkedIn to analyze current enterprise software stories. We covered many grounds, including the direction and roadmaps of each enterprise software vendor. Finally, we analyzed future trends and how they might shape the enterprise software industry.Video: https://www.youtube.com/watch?v=W_TyTBrq0ccQuestions for Panelists?

Send us Fan MailSmall businesses represent a critical transition point in the ERP journey, where the focus shifts from fragmented tools and experimentation to operational consistency, financial control, and cross-functional visibility. Typically in the $10 to $100 million revenue range, these organizations bring more process maturity and functional leadership than startups, yet still operate within meaningful constraints—particularly around budgets, customization capacity, and internal technical expertise. As a result, they tend to favor suite-centric ERP systems with tightly integrated capabilities across finance, inventory, and operations, reducing reliance on complex integrations and costly development. At this stage, ERP is about establishing repeatable, scalable processes that eliminate bottlenecks without introducing unnecessary complexity. This is why evaluating ERP for small businesses requires a balanced lens—prioritizing ease of implementation, total cost of ownership, and functional breadth over deep specialization—helping leaders avoid overengineering their stack while selecting a system that delivers immediate value and supports the next phase of growth.In this episode, our host Sam Gupta discusses the top ERP systems for small businesses in 2026. He also discusses several variables that influence the rankings of these ERP systems. Finally, he shares the pros and cons of each ERP system.Video: https://www.youtube.com/watch?v=iswWCJhryy0Read: https://www.elevatiq.com/post/erp-systems-for-small-business/Questions for Panelists?

Send us Fan MailMost ERP initiatives fail well before software selection, often when organizations reduce the decision to feature comparisons, vendor demos, and procurement-style checklists that obscure deeper architectural and operational realities. Influenced by marketing narratives, limited internal strategy experience, and heavy reliance on implementation partners, teams frequently overlook critical factors such as data readiness, integration design, migration feasibility, legal exposure, and behavioral constraints—leading to overcustomization, cost overruns, delayed go-lives, and systems that reinforce silos rather than resolve them. This webinar reframes ERP selection through the lens of ERP Readiness, positioning it as a structured discipline that aligns leadership and cross-functional teams on the true implications of ERP before downstream execution begins. By evaluating process, data, organizational, technological, legal, and behavioral readiness through a staged, decision-gated approach, organizations can follow a practical 3–6 month framework that produces actionable deliverables, reduces implementation risk, and significantly improves selection outcomes for high-stakes ERP decisions.Video: https://www.elevatiq.com/events-and-webinars/erp-readiness-why-checklist-driven-approaches-fail/Questions for Panelists?

Send us Fan MailRecent developments across the enterprise technology landscape signal a decisive shift toward real-time, AI-driven, and sovereignty-aware architectures. From Deepgram securing new funding to accelerate voice AI for real-time applications, to IBM launching cloud platforms aligned with digital sovereignty mandates, vendors are re-architecting core infrastructure to meet emerging regulatory and latency requirements. Strategic moves such as the merger of Tasq AI and BLEND to build enterprise trust layers, alongside Teradata scaling over 150 AI engagements, highlight growing enterprise demand for governed, production-grade AI. Meanwhile, innovation is accelerating across the stack—from Tredence introducing agentic commerce accelerators and Akkodis scaling AI-core platforms, to infrastructure players like ClickHouse and Artie doubling down on real-time data as a foundational layer. At the orchestration level, Salesforce and ServiceNow are embedding agent-based ecosystems through MuleSoft Agent Fabric and deeper partnerships with OpenAI, collectively reinforcing a broader industry trajectory: enterprise systems are evolving from static systems of record into dynamic, intelligent, and autonomous platforms.In today's episode, we invited a panel of industry analysts for a live discussion on LinkedIn to analyze current enterprise software stories. We covered many grounds, including the direction and roadmaps of each enterprise software vendor. Finally, we analyzed future trends and how they might shape the enterprise software industry.Video: https://www.youtube.com/watch?v=_7YXOXZawPoQuestions for Panelists?