Podcasts about slas

By Doug Green “Infrastructure is increasingly becoming a control point for AI enablement and productivity.” In this episode of the Technology Reseller News podcast, Doug Green speaks with Shashi Kiran, Chief Marketing Officer at Nile, about why infrastructure is moving back to the center of enterprise strategy, budgeting and AI readiness. Kiran says Nile is modernizing enterprise networks with what it describes as the world's most secure network delivered as a service. The company provides wired and wireless local area networking for mid-size and large enterprises, with security built in and operations managed across the lifecycle. The conversation focuses on a growing reality for enterprises: AI may appear to live in applications, cloud platforms and user devices, but its success depends on the infrastructure underneath. As organizations rethink AI adoption, infrastructure decisions are becoming long-term strategic decisions again. Unlike software, Kiran notes, infrastructure cannot simply be changed overnight. Network decisions often shape cost, security, agility and business performance for years. A poor infrastructure choice can become a drag on the rest of the organization's technology investment. Kiran says this is driving renewed interest in network as a service. In the modern model, he says, network as a service is not simply a managed provider operating someone else's technology. Instead, Nile builds, owns and operates the technology, giving customers a single accountable partner across the full value chain. For Nile, the focus is the enterprise edge: campuses, branches, users, devices, IoT and, increasingly, AI agents. Kiran says that part of the network has often been overlooked while much of the industry focused on data centers and cloud. Yet it is also where complexity, operational cost and security exposure are often highest. Nile's approach is built around simplifying that environment. Kiran describes a clean-slate architecture with wired and wireless connectivity, zero trust principles, identity-based authentication, security built in, and autonomous operations. Nile also backs its service with performance SLAs and financial penalties. Kiran says the results can include lower complexity, faster change management, reduced breach exposure and significant savings. He says customers typically see cost reductions of 30% to 50% at a minimum, along with faster deployment and change cycles. As enterprises plan for the next several years, Kiran says infrastructure will become even more important as organizations work to become more AI-native. The companies that move away from legacy models and adopt more agile infrastructure approaches will be better positioned to support AI, improve productivity, reduce cost and strengthen security. Learn more at nilesecure.com  

The Wall Street Journal reported that a $13 billion AI startup is betting on cheaper alternatives to OpenAI and Anthropic. Enterprises are shifting from pilots to production and seeking to control inference costs across support, copilots, and content workflows. Open source options such as Meta's Llama and models from Mistral enable targeted deployments with retrieval and fine-tuning to improve cost predictability. Procurement teams weigh SLAs, latency, security certifications, data retention, indemnity, and regional hosting against premium providers. Vendors distribute through AWS, Microsoft Azure, and Google Cloud marketplaces, while access to Nvidia accelerators influences performance and cost. Pricing includes per token and per seat plans, with some platforms routing simple tasks to lower cost models and reserving premium models for complex work. Founders are advised to build evaluation harnesses, track cost per outcome, and negotiate for predictable terms.Learn more on this news by visiting us at: https://greyjournal.net/news/ Hosted on Acast. See acast.com/privacy for more information.

Send us Fan MailSomeone is stealing encrypted data right now and they are not trying to read it today. They are saving it for later, betting that quantum computing will eventually break the encryption that protects it. I dig into the “Harvest Now, Decrypt Later” strategy, why it matters most for long-term confidentiality, and how security leaders can talk about it as a present-day risk instead of science fiction.From there, I get practical with post-quantum planning: what the NIST post-quantum cryptography standards signal, why quantum key distribution is still niche for most organisations, and the big architectural idea to remember for the CISSP and for real enterprise security programs: crypto agility. We walk through concrete steps like building a cryptographic inventory, mapping where RSA and elliptic curve crypto live, identifying data with 10 to 20 year secrecy needs, and pushing vendors for a clear PQC roadmap.Then we pivot into CISSP Domain 1 supply chain risk management (SCRM and CSCRM). I explain why supply chains are a prime target, how modern supply chain attacks can ride in through poisoned open source packages, and what SolarWinds showed the world about scale and impact. We close with the nuts and bolts that actually reduce third-party risk: lifecycle supplier management, meaningful assessments (on-site when it matters), document and policy review, audits, and minimum security requirements baked into contracts and SLAs.If you want more training, check out CISSP Cyber Training, subscribe for weekly updates, share this with a friend who owns risk, and leave a quick review so more CISSP candidates can find the show.Gain exclusive access to 360 FREE CISSP Practice Questions at FreeCISSPQuestions.com and have them delivered directly to your inbox!  Don't miss this valuable opportunity to strengthen your CISSP exam preparation and boost your chances of certification success. Join now and start your journey toward CISSP mastery today!

Dominique Moretti rebuilt the I.AM.GIA website from scratch in 12 weeks. Open rates sit above 50%. The re-engagement flow beats the welcome flow. And 90% of I.AM.GIA's revenue comes from the US. This is how she runs two global fashion brands with one lean team.Dom is Head of Ecommerce and Digital at A&S Labels, the Melbourne company behind Tiger Mist and I.AM.GIA. She started there as a graphic design intern twelve years ago, grew with the business, left for a stint at Calibre, and came back in a bigger role. She's also a Klaviyo Champion 2026. Nathan sat down with her at K:SYD in Sydney before the doors opened, the third of three conversations recorded there.Today, we're discussing:How Dom scrapped an I.AM.GIA website project mid-build, changed agencies and rebuilt in 12 weeks [12:09]Why she moved from headless to Shopify Native and what drove that decision [13:13]The re-engagement flow with no discount that's now outperforming the welcome flow [28:33]How to maintain 50-60% open rates for two fashion brands in 2026 [30:46]The app strategy: push notifications, Tapcart AI flows, and why apps beat SMS long-term [00:00]What TikTok Shop in the US actually requires in terms of product data, SLAs and live consistency [43:09]How Dom is using Claude and Klaviyo MCP for weekly reporting across all channels [37:29]Use the code ADDTOCART20 for 20% off storewide at tigermist.com.au and iamgia.com (excludes EV x TM Collection).Connect with Dominique Moretti | Explore Tiger Mist | Explore I.AM.GIA Subscribe to the Add To Cart newsletter  SMS us to Suggest a Guest Connect with Nathan Bush Join the Add To Cart Community 

Outcome-based managed security and attached vendor warranties are driving a new form of coverage-based vendor lock-in for MSPs and IT service providers. Vendors such as Intezer and SPECTRA are introducing performance guarantees, SLAs, and cyber resilience warranties that require MSPs to fully standardize on their architectures. This evolving model shifts accountability for enforcement and risk management from the individual MSP to the vendor's operating model, thereby altering the independent role of the MSP within client environments. A notable example is Intezer's Amplify Partner program, which asserts that its platform can process 100% of security alerts while escalating fewer than 2% for human review—claims the company frames as outcomes rather than product specifications. SPECTRA's use of certification-linked warranties, distributed via Ingram Micro, establishes channel-distributable assurance products with explicit conditions attached at every level. According to a Check Point report, while 77% of organizations report having adopted AI for cloud security, only 26% feel capable of enforcing those strategies, revealing a gap between security intent and operational ability. This structural shift is further illustrated by Merlin Cyber's FedRAMP managed service offering, Lumen's MDR enhancements targeting mid-market MSPs, and Trustlogix's addition of intent-based authorization controls. The FBI's announcement regarding Microsoft 365 OAuth token hijacking and recent vulnerabilities in widely used platforms like ConnectWise Automate underscore the real-world risks of automation platforms being targeted. These developments collectively point to growing operational complexity, rising compliance burdens, and the need for MSPs to separate their commitments from upstream vendor claims. For operators, the trend demands increased scrutiny of warranty terms, claim denial conditions, and SLA language before making any client-facing assurances. MSPs risk absorbing liability if they repeat vendor marketing claims without contractual clarity or operational control. Effective governance now requires independently produced, audit-ready evidence that documents compliance and enforcement separate from vendor portals. As assurance sales proliferate, the operational gap between acting as an underwriter versus a reseller will drive market differentiation, affecting both pricing structures and eligibility for vendor-backed coverage. 00:00 Channel-Ready Security 03:41 Policy vs. Reality 05:59 MFA Isn't Enough 09:12 Why Do We Care?    Supported by:  ScalePad Moovila   

In this episode, we're joined by Lorna Ewart, PhD, CSO of Emulate, to discuss the company's SLAS 2026 New Product Award-winning product: AVA™ Emulation System. AVA™ is a self-contained, benchtop organ-on-a-chip platform that runs 96 chips simultaneously.Lorna shares how the device was developed and its impact on drug discovery and organ-on-a-chip technology. Key Learning Points:Development of the AVA emulation systemApplications of the AVA platform in drug discoveryImpact of organ-on-a-chip technology on biomedical researchAbout EmulateEmulate, Inc. is the pioneer of Organ-on-a-Chip technology, enabling researchers to accurately replicate human tissue function and disease biology through next generation in vitro models. From target discovery to IND submission, Emulate aims to ignite a new era in human health research—one that reduces animal testing, cuts drug development costs, and accelerates the delivery of life-saving treatments. Emulate's Organ-Chip platforms, consumables, and organ models help the world's leading pharmaceutical, biotech, and academic teams generate human-relevant data that advance safer, more effective therapies.Stay connected with SLAS:www.slas.org | Facebook | X | LinkedIn | Instagram | YouTubeAbout SLASSLAS (Society for Laboratory Automation and Screening) is an international professional society of academic, industry and government life sciences researchers and the developers and providers of laboratory automation technology. The SLAS mission is to bring together researchers in academia, industry and government to advance life sciences discovery and technology via education, knowledge exchange and global community building.Upcoming Events:SLAS Europe 2026 Conference and Exhibition (19-21 May 2026 | Vienna, Austria)SLAS Meet-UpsChicago, Illinois (June 18, 2026)Leiden, Netherlands (10 September 2026)Tübingen, Germany (20 October 2026)SLAS 2026 Sample Management Symposium (October 21-22, 2026 | South San Francisco, California)SLAS2027 International Conference & Exhibition (January 30 - February 3, 2027 | San Diego, California)View the full events calendar

If your SaaS product delivers genuine value fast, growth takes care of itself. That's the core thesis Sanjay Sarathy has spent 8+ years proving at Cloudinary, where he oversees a self-service business representing nearly a third of the company's revenue across 11,000+ paying customers in 150+ countries — without feet on the ground in most of them.In this episode, Sanjay breaks down what product-led growth actually looks like when it's executed well: not just free trials and clever onboarding flows, but building such a frictionless, valuable experience that developers naturally tell other developers. He shares why Cloudinary invested in technical support before marketing, how they redefined "activation" to mean real value (not just uploading a file), why discoverability is a non-negotiable pillar of their growth strategy, and how they're now rethinking the developer experience for a world where AI agents and LLMs are writing the code.This is a masterclass in developer-led PLG from someone who has lived it at scale.Key Takeaways4:07 — The Growth Levers Have Changed SEO, outbound, and paid are still valid, but word of mouth (especially in developer communities), AEO, and agentic discoverability have become powerful new growth engines — when they're earned as a byproduct of value, not engineered as a primary goal.8:28 — Why PLG Before Enterprise Cloudinary was built by developers for developers. They started with self-service because that's what their founding team would have wanted. Only after PLG proved itself did enterprise customers come knocking — and it was far easier to layer on security, SLAs, and support than to bolt on a product that developers already loved.13:46 — Great Product Isn't Enough Without Distribution Cloudinary is in 150 countries with no boots on the ground in most of them. SEO, developer relations, and a docs site that functions as a discovery engine are what made global reach possible. Distribution and product must go hand-in-hand.15:36 — Discoverability Is a Strategy, Not a Tactic "Discoverability" is a recurring internal theme at Cloudinary — constantly asking how to ensure the right people, in the right context, can find and experience the product's value.16:03 — The Cannibalization Trap Cloudinary made the mistake of launching a new product without considering its impact on existing products — and cannibalized their own business. They now use a two-track product strategy: "mature" products with full go-to-market support, and "invest" products being validated for product-market fit before scaling.19:24 — Invest in Support Before Marketing One of Cloudinary's earliest and most impactful decisions: invest heavily in technical support first. Happy, successful developers become word-of-mouth advocates. That bet paid off across an entire community.21:06 — Developer Experience in the Age of AI Tooling Developer experience today means meeting developers where they work — VS Code, Cursor, Claude, Windsurf. Cloudinary built a VS Code extension and is working to minimize hallucinations by giving LLMs accurate, context-rich instructions for using Cloudinary correctly.24:03 — Redefining Activation Uploading a file to Cloudinary is not activation. Doing something with that file — transforming it, tagging it, delivering it — is activation. Reframing their metric around genuine value changed how they prioritized onboarding.33:25 — The Seven-Day Activation Window Data shows clearly: if users don't activate within the first 7 days, a second surge doesn't come. Most activation happens in the first 4–5 days. This insight shapes everything about how Cloudinary approaches onboarding urgency.27:01 — Speak Use Cases, Not Features "We have automated image optimization" means nothing. "Your images are 40% lighter and you'll save X on bandwidth" means everything. The language of outcomes and use cases is what drives adoption and expansion.36:39 — Pricing Must Communicate Value Cloudinary's self-service pricing has remained largely flat for years while the product has added enormous capability — intentionally improving the value/price ratio over time. They also offer pay-as-you-go flexibility for seasonal businesses.44:28 — The 90-Day PLG Focus: Build Trust For founders building a PLG motion right now, Sanjay's single most important recommendation: engender trust. Do what you say. Follow up when you say you will. Make your product deliver on its promise. Trust is the flywheel.Tweetable Quotes"We never set out to get word of mouth. We set out to create value. Word of mouth was the byproduct." — Sanjay Sarathy"If your product genuinely helps people win, growth becomes a natural byproduct." — Sanjay Sarathy"Distribution is equally as important as the product itself. You can have a great product and go nowhere." — Sanjay Sarathy"Discoverability isn't a campaign. It's a strategy." — Sanjay Sarathy"Uploading a file isn't activation. Doing something valuable with it is." — Sanjay Sarathy"If a developer doesn't activate in the first seven days, don't expect another surge. It won't come." — Sanjay Sarathy"Stop talking about your features. Start talking in the language of your customer's use cases." — Sanjay Sarathy"We're okay with free users who are actively using the product. They pay us back in word of mouth." — Sanjay Sarathy"In a PLG motion, trust is the flywheel. Without it, everything else breaks down." — Sanjay Sarathy"We fell in love with our own capabilities and forgot that customers don't care. Use cases are what drive adoption." — Sanjay SarathySaaS Leadership Lessons1. Build Distribution Like You Build Product Cloudinary reaches 150+ countries without sales reps in most of them — through SEO, developer relations, documentation, and community. Great products disappear without intentional distribution. Your discoverability strategy is a growth strategy.2. Earn Word of Mouth — Don't Engineer It The moment you prioritize getting word of mouth over generating it as a byproduct of genuine value, you've lost the plot. Build something that makes people win, then step back and let them talk. The data will tell you if it's working.3. Start Narrow, Validate, Then Scale Cloudinary's "invest vs. scale" product framework exists because they once cannibalized their own product line by expanding without rigor. Validate product-market fit in a controlled way before committing the full go-to-market machine. Repeatability before scale.4. Redefine Your Activation Metrics Around Real Value Ask yourself: is the action we're measuring actually a moment of value, or just a moment of presence? Cloudinary stopped counting uploads and started counting transformations. The metric you optimize shapes the product you build.5. Invest in Customer Success Before You Think You Need To Cloudinary prioritized technical support ahead of marketing in their early days. Counter-intuitive — and it was exactly right. Successful users become advocates. That investment compounded for years through word of mouth and developer trust.6. Speak the Language Your Customer Thinks In "Automated image optimization via F-Auto" is internal language. "Your images are 40% lighter and your site is faster" is customer language. The translation layer between what your product does and what your customer achieves is where adoption lives or dies. Build that bridge deliberately.Guest Resourcessanjay@cloudinary.comwww.cloudinary.comhttps://www.linkedin.com/in/sanjaysarathy/https://x.com/guffnuffEpisode SponsorThe Futureproof Series - https://www.youtube.com/playlist?list=PLfkXKUPZ5xuOqMPR7_gzGybncTtavyR1NThe Captain's KeysSmall Fish, Big Pond – https://smallfishbigpond.com/ Use the promo code ‘SaaSFuel'Champion Leadership Group – https://championleadership.com/SaaS Fuel ResourcesWebsite - https://championleadership.com/Jeff Mains on LinkedIn - https://www.linkedin.com/in/jeffkmains/Twitter - https://twitter.com/jeffkmainsFacebook - https://www.facebook.com/thesaasguy/Instagram - https://instagram.com/jeffkmains

Anthony Tanoury, senior director of distribution at Dell Technologies Distribution doesn’t get a lot of editorial love. It’s easy to treat it as the background infrastructure of the channel – the warehousing, the credit lines, the logistics layer that keeps product moving. But as anyone who’s been paying attention knows, that picture is well out of date. At Dell Technologies World in Las Vegas this week, In the Channel sat down with Anthony Tanoury, Dell’s senior director of distribution, to talk about what distribution actually looks like in 2026 – and the conversation ranged from supply chain strategy to AI-assisted deal registration to the shifting economics of the partner ecosystem. The headline number: Dell moved approximately ten thousand partners to a distribution-led buying model last year. Partners who previously purchased direct from Dell now route exclusively through distribution. The more interesting data point is what happened next – those partners are growing faster than the ones who remained on a direct model. Tanoury attributes it to the enablement depth that distributors can offer at a scale that Dell simply can’t replicate directly. On the Modern Partner Platform rollout – one of the bigger announcements at DTW this week – the conversation came down to speed. Deal registration that today takes two to three days is being redesigned, with AI-assisted automation in the pipeline to bring that down to two to three hours. The plumbing involves integrating Dell’s systems tightly with distributor platforms, streamlining the multi-system, multi-email-thread process that currently slows everything down. And when asked for the single most underutilized resource available to partners through distribution, Tanoury didn’t hesitate: the AI accelerator programs that distributors have built to help partners get started in the AI practice space. With every partner asking “where do I begin,” the answer may already be sitting in the distributor’s enablement catalogue. Read Full Transcript Robert Dutt: Hello and welcome to In The Channel from ChannelBuzz.ca, bringing news and information to the Canadian IT channel community for the last 16 years. I’m Robert Dutt, editor at ChannelBuzz.ca and your host for the show. We’re continuing our coverage from Dell Technologies World in Las Vegas this week, and I wanted to close the series of Dell execs with a conversation that I think will resonate with pretty much anyone who moves Dell product – which, let’s be honest, is a lot of you. Distribution is one of the topics that often gets taken for granted. It’s the plumbing, it’s the logistics, it’s the credit line. Except that’s not really what distribution is anymore, and Anthony Tanoury has about as good a vantage point as anyone to explain why. He spent 30 years in the industry on both the vendor and distributor side of the table, and he’s now Dell’s senior director of distribution, which means he’s the person responsible for making the relationship between Dell and its distributor partners actually work at scale. This week at DTW, Dell announced some significant changes to how it’s thinking about its partner ecosystem, and distribution’s right at the center of that. We talked about the evolution of distribution from warehouse and financing shop to AI enablement engine, what it actually means for partners that Dell moved 10,000 of them to distribution-led buying last year, and what the promise of deal registration in hours rather than days actually requires to make real. Let’s get right into it. My chat with Anthony Tanoury. Anthony, thanks for taking the time. I appreciate it.Anthony Tanoury: Thanks for having me. Robert Dutt: To kick things off – the definition of distribution, and the definition from distributors themselves of what they do, has changed so dramatically over the last few years, as you’ve been party to on both sides of the fence, vendor and distributor, with your background. Sitting where you are now as senior director of distribution, how do you define the core value proposition for your distribution partners today compared to the way it may have looked a few years ago if you were in the seat, or in a previous seat managing distribution? Anthony Tanoury: Yeah, I think 30 years in distribution – dating myself here. The idea of a distributor was warehousing, finance, so on. Really, the way that that’s evolved – and still evolving, because not everyone fully understands distribution and the value of distribution – but it’s really become the engine for all of us OEMs to really dive deep into the mid-market, and as lead generation for all of us. So SMB, mid-market, and then really leveraging their enablement platforms for our partners. So as an example, this week here at Dell Technologies World, we’ve launched our full AI portfolio. And really at the end of the day, it’s a platform to build off of. And our distributors, through our partners, are really enabling those partners – especially in the mid-market. The enterprise partners have hired data scientists and so on. And those mid-market and SMB partners, they need our help. And we really rely on our distributors, who have AI accelerator programs and can really take a partner through the journey of how to look at AI, how to start, and then how to implement and really get started in this space. We’ve met with multiple partners at this show and we’ve had our partner advisory boards. And that’s the number one takeaway when we’re talking to our partners: “How do I get started?” And I think Jeff Clarke and Michael Dell talked about that on stage – it’s really, we’ve got the platform to build off of, and then really rely on our distributors to go enable all of our partners out there to have those conversations, and then to build the proof, the POCs for us with their customers and take it to the next step. Robert Dutt: Let’s talk about this moment in time and managing distribution right now. Whenever I think of running a hardware vendor, running distribution, or being on the purchasing side of the solution provider right now – boy, that’s an interesting challenge – with the supply chain issue, with the pricing issue, with all of that. I guess it boils down to, from your perspective: how are you leaning on distribution differently to help you guys and your partners ultimately, especially the smaller ones, handle this issue of availability, of supply chain, of capacity, as we’ve seen the component price challenges across the industry? Anthony Tanoury: Yeah, so that’s not unique to Dell. We’re all challenged with the supply chain challenges, and it’s really about having a consistent message to our partner community, to our customers, on how – or why – to partner with Dell in these times. And our distributors have really leaned in with us right now and are getting that message out to our partners that “Dell’s got a plan. Here’s the plan.” And this is how we want you to message that and relay that to your partner community. So as an example, I did a keynote speech at one of our large partner events recently, and my talk track was based on how to navigate those supply challenges with us. I spent a lot of time on that, and had multiple partners come up afterwards, catching me outside. And the comment was, “That’s what we need to hear. That’s our challenge today, and you’re tackling that head on.” So to get back to your question from a distribution perspective – they enabled me to take that message to them, and then they’re expanding on that to their 20,000 partners in their ecosystem. Robert Dutt: As you bring up an interesting thread there – I don’t have time obviously to go through the whole keynote, but the elevator pitch, boiled-down version of it – what’s the advice to partners on tackling it from where you sit and from where Dell sits? Anthony Tanoury: Yeah, really leaning in with us and going deeper with your customers. And so that’s where you’re going to work with Dell and get priority allocation – looking long-term versus short-term, “I just need this product in the next week to get through this phase.” Now, let’s look at a long-term solution together and let’s plan two years out. Let’s plan longer in some cases, and then we’ll take it from there. Robert Dutt: And that’s something we heard also from Jeff Clarke in Q&A – that idea of build out those long-term plans, put your hand up as early as you can. Because it sounds like if you’ve got your hand up early, you’ve obviously got the best chance of getting that list fulfilled. Anthony Tanoury: Yeah, whether it’s a customer or a partner – I mean, that’s a true partnership and we’ll lean in when customers want to lean in with Dell. Robert Dutt: I wanted to touch on the changes that are coming to the partner program, specifically as it involves your interactions with distribution. The Dell portal is getting redone and the Dell program is getting redone with the modern partner platform rolling out this year. You guys are baking agentic AI into your partner platform. Meanwhile, your distributors are doing the same thing with their partner platforms. I’m curious – obviously very early in the game – but how are you and your distribution partners thinking long-term about how those various platforms interact with each other, in terms of delineating who covers what base, when it comes to serving the partner and what you may be able to do down the road as a result of having those platforms? Anthony Tanoury: Yeah, so the key is cutting down on SLAs. How do we take getting pricing out to a partner, out to a customer, from two to three days down to a matter of hours, right? And we’ve worked closely with all of our distributors over the last year or two, because our partners rely on our distributors’ platforms. And how does that integrate with ours? But the key is speed. How do we do things faster? And that is, as you stated, embedding AI into that. And so again, can’t get too far ahead, because we’re still going down this path and things sometimes get pushed out. But we’ve been working on this for a long time with them. We’ve had a lot of meetings with them here. We’ve gone deep into their platforms. They’re all rolling out new platforms as well. So making sure we’re doing it all at the same time, and together, has been key. Robert Dutt: One area I did want to double-click on there. One of the big promises of the new platform is deal-reg approval in minutes, AI-generated demand signals, those kinds of things. As Dell is accelerating its own systems, how does distribution plug into that? How does the distributor help manage and act on those AI-driven demand signals and facilitate a faster quote-to-deal-reg? Anthony Tanoury: Without getting too deep into deal-reg, there are a lot of nuances there. But yes, today where you’ve got multiple partners of record and you’ve got multiple partner IDs – simplifying that down to one or two partner IDs versus 20 today that we have – and then with deal registration, having partner of record is key in that mix, and we do have that today. But the distributors are really where it starts. So a partner comes to the distributor, says, “Hey, I need pricing on this and I want deal registration.” Today it might take the full SLA – the two to three days we just talked about – to get deal registration approved, with multiple systems flowing back and forth. In the future – and when I say future, we’re close, we’ll get there – is having that one stream go, starting from the distributor, through AI, plays into that, where it’ll do the work of looking in and making sure: here’s the partner of record. Is there a partner on record? Does the end user qualify? And without multiple people, multiple email streams going back and forth, it locks it in. And so now you’ve got an answer back in two to three hours versus two to three days. Robert Dutt: A lot of MSPs prefer to consume technology as a service, because it’s kind of in what they do – the name’s kind of on the tin – and bundle that with vendors like Microsoft or security or what have you. How are you working with distributors to make APEX and infrastructure solutions seamlessly consumable within distribution, and particularly on their marketplace? Anthony Tanoury: Yeah, so that’s a good question. So there’s APEX, right? We have Dell APEX, and our competitors have their own, but we have Dell APEX. But our distributors also have their own versions of APEX, or as-a-service models. And at the end of the day, we leverage theirs just as well as we do our own. And it depends on the customer, depends on the contract situation, but there are multiple vehicles to get an as-a-service deal done today that didn’t exist a year ago, didn’t exist two years ago, right? And then there’s – moving to another topic, and really the same topic – device as a service, right? And that was something we’ve been talking about for a few years now and hasn’t really taken off, but that’s all part of this now. Because the device at the edge is co-mingled now – especially in the new AI world – with your server infrastructure. So it could all become part of a recurring revenue stream for MSPs. Robert Dutt: And I think it makes potentially hardware more compelling to the MSP. When you’ve gotten that tie-in – I know it’s early days and it’s a way off from being fully operationalized – but what you’re talking about, and what Jeff Clarke was talking about today about basically acting as the arbiter, sort of an open orchestration layer, saying “all right, this particular bit is best handled in the infrastructure and the data center, this particular bit is best handled right here on the machine sitting by the desk side.” Anthony Tanoury: Absolutely. Robert Dutt: We’ve heard a lot this week about the focused accounts incentive, rewarding partners for selling across lines of business. And it’s kind of a cliche almost, in that vendors such as yourselves who have multiple lines of business are always looking for great ways to get partners to sell across those businesses. And certainly incentives are a classic way of doing that. How are you using distribution to train, enable, and facilitate partners making that leap across the portfolio – especially as this seems to be something that Denise Millard and the team are putting a lot of the wood behind? Anthony Tanoury: Yeah, so you mentioned the partner program – and that’s really what we leverage with the push coming from distribution. You typically focus where you can earn the most dollars. And so we’re putting the dollars on driving all lines of business for us. So today you may have a lot of infrastructure-focused partners – like MSPs, they don’t want to sell the client the edge device. But again, with AI driving from both ends now, it’s become an imperative that they don’t ignore the edge devices anymore. So really leveraging distribution both ways. We’ve got CSG partners that don’t sell storage and infrastructure, and then we’ve got partners that are trying to move in that direction. And then we’ve got other partners saying, “Hey, I’ve got to get on board too,” that are in the infrastructure space and have got to move in the other direction. And that’s where we leverage distribution – they have multiple enablement engines, all of our distributors, to enable those partners to do that. So for us – and again, to the partner program – we’ve announced some changes here at this event, with our partner advisory board meeting coming up. Partner programs, you want to keep them simple, predictable for partners, with tweaks along the way. And AI is one of those tweaks where we’ve got to pull the levers in different directions to get partners and distributors moving in that motion. So yeah, it’s an exciting time to be at Dell with this opportunity in front of us. Robert Dutt: That’s a big tweak – or more accurately, a big series, whole family, whole universe of tweaks to be made. But you don’t want to pull a whole program apart. You’ve got partners that have invested and distributors that have invested in that program. So you’ve got to make sure you do those incremental tweaks when you need them, but not blow up the whole program. Anthony Tanoury: Absolutely. Robert Dutt: You mentioned off the top the classic framing of distribution as the warehouse and the bank kind of structure. Let’s touch on the bank side of things a little bit there. In light of everything that’s going on today, in light of the infrastructure refresh opportunity that’s out there, the constraints in the marketplace – financial engineering is probably more critical than ever. Dell Financial Services is doing a lot of heavy lifting, but how do you view the role of the distributor when it comes to PO financing, terms, bridging the financing gap for complex projects, and helping partners manage this whole multiple-balls-in-the-air situation? Anthony Tanoury: You can’t look at a partner just through the lens of what they do with Dell. The business they have with Dell – partners procure from many places. We love them to only sell Dell for us, but they have other options, other solutions, other areas of the business that we’re not focused on. They procure through distribution. Distributors have huge businesses with a lot of these partners. They have financial terms through the distributors that maybe we can’t offer them through Dell – and leveraging our partner programs to deliver extended terms in this environment. With the supply shortages and lead times getting pushed out, really leveraging distribution with terms that we can’t give them today. There are multiple levels, and they have much higher credit lines with the distributors than maybe we have with them. And then going back to the as-a-service model – really leveraging distributors who have all those options in place for them today, that maybe they don’t have with us. Robert Dutt: When you’re looking at distribution, what’s the one metric you look at first to judge whether a distributor is meeting the bar – is delivering net new value to Dell? Anthony Tanoury: New partner recruitment, right? Multiple lines of business – not just focused in one area of our business, but selling across all lines of business. Then we rely on distribution. We just moved 10,000 partners last year over to distribution-led. Where those partners could procure direct from Dell in the past, now they can’t, and they buy strictly through distribution. Those are our authorized partner community – and potentially in the future, expanding that to other levels of our business and offloading them to distribution. Dell is a more channel- and distribution-friendly company than we get credit for. I think that doesn’t always get seen, and we’re moving that way. Robert Dutt: How did that process go, and any learnings from moving those 10,000 partners that may inform what you do in moving the next group, if there is a next group to be moved? Anthony Tanoury: Exactly, a lot. A lot of that is in data transfer and making sure that the distributors have the right data to target those partners and give those partners the service they need. The distributors all had to ramp up their infrastructure to support those partners – credit line facilities with those partners – because they didn’t do business with those partners before. Onboarding some of those partners as net new to distribution, who had never bought from distribution before. And then again, really letting those partners know the value of distribution. Since we’ve moved those partners over, those partners that have embraced distribution are growing faster than the partners that haven’t. It’s sometimes a lot easier to get that additional support, that additional attention from a disti, than it is to try to navigate that directly. In some cases, they can support them better than we can, and it’s proven out in the last year. Robert Dutt: What’s the single most underutilized resource that you guys have through distribution, in terms of what partners are using? Anthony Tanoury: I would say the AI accelerator programs I spoke about earlier. That’s key. Going back to the enablement piece – I just don’t think a lot of partners understand the value. They come to these events, they make the statements, “Hey, we need help here. We need to leverage distribution for that help.” Especially when you come to a Dell Technologies World, or you go to one of our competitors’ or peers’ events. Our distributors have that enablement piece for you to get started, that you need to leverage, because it’s not just a point-solution type of conversation, it’s broad. Really leveraging them to help. Robert Dutt: Along the same lines, but a little bit different – obviously we’ve touched on the idea of cross-selling, and the idea that, surprise surprise, Dell would like partners to sell more of the portfolio, better together, all that kind of stuff. For an MSP or VAR whose primary look at Dell to date has been selling end devices – laptops, desktops, et cetera – sourced through distribution, what do you see as the most likely next logical step to expand that relationship? To get thinking across lines? What are some of the common threads for the best ways to approach that? Anthony Tanoury: Yeah, that’s a tough question. Common ways to approach how to sell across lines of business – take it back to the customer level. Your customer is buying these products, and they may be buying them from somebody else or they may be buying them online, depending on the size of the organization, so on. Again, the service model – going back to it, it’s another service revenue stream that they can leverage. But I think when you look at the distributors, they have a lot of talk tracks with the partners on how to do that, and frankly do it better than we do. So that’s why we really leverage them. When we say, “Hey, we want to sell more of our client and peripheral devices,” we start with distribution. We start with the partner community, and it’s paid off. I think it’s just – really, don’t leave revenue on the table. We’ve been saying it for years and I think it’s starting to resonate, and leveraging distribution to push that message forward. And I think partners are starting to catch on. Robert Dutt: All right, great insights. Anthony, I thank you for taking the time. I’m sure it’s been a busy week for you here. Thanks for joining us. Anthony Tanoury: Thanks for having me. I appreciate it. Robert Dutt: There you have it, Anthony Tanoury from Dell Technologies. I’d like to thank Anthony for carving out some time in what I’m sure was a very busy week on the show floor here at DTW. Few things from the conversation that I thought were worth pulling out. First, the 10,000 partners that Dell moved to distribution-led buying last year – that’s not a small number, and the fact that those partners are outgrowing the ones who haven’t yet made that transition should be a data point for anyone still on the fence about how they structure their Dell relationship. Second, when Anthony named net new partner recruitment as his primary metric for judging distributor performance – not revenue, not attach rate, net new – that tells you something about where Dell thinks its distribution channel still has room to grow. And third, if you haven’t looked at the AI accelerator programs your distributor is running, that came up twice as the single most underutilized resource available to partners right now. Probably worth a phone call. I’d like to thank you as always for listening to the show. Please follow or subscribe wherever you get your podcasts – Apple Podcasts, Spotify, YouTube, most directories. Ratings and reviews are always appreciated as well. Until next time, I’m Robert Dutt for ChannelBuzz.ca, and I’ll see you in the channel.

In this episode, I sit down with Steven Yates, CTO and co-founder of Federant, to dive deep into the urgent need for runtime governance in edge AI. Drawing on decades of experience in embedded systems and PLC design, Steven reveals why the shift to the edge demands more than just powerful inference—it requires robust, local authority to keep operations safe when connectivity falters. We unpack real-world incidents where lack of governance led to costly mishaps, and explore how new open-source solutions are bridging the gap between cloud convenience and industrial reliability. If you think cloud SLAs are enough for industrial AI, this conversation will make you rethink the fundamentals. Join me as we explore the future of safe, autonomous operations—and why the old rules of industrial control are more relevant than ever.

In this episode, hosts Lois Houston and Nikita Abraham break down the differences between Infrastructure-as-a-Service, Platform-as-a-Service, and Software-as-a-Service. The conversation explores how each framework influences control, cost efficiency, expansion, reliability, and contingency planning.   Cloud Tech Jumpstart: https://mylearn.oracle.com/ou/course/cloud-tech-jumpstart/152992 Oracle University Learning Community: https://education.oracle.com/ou-community LinkedIn: https://www.linkedin.com/showcase/oracle-university/ X: https://x.com/Oracle_Edu   Special thanks to Arijit Ghosh, Anna Hulkower, Radhika Banka, and the OU Studio Team for helping us create this episode. --------------------------------------- Episode Transcript: 00:00 Hi there! We're hitting rewind for the next few weeks and bringing back some of our most popular episodes. So, sit back and enjoy these highlights from our archive. 00:12 Welcome to the Oracle University Podcast, the first stop on your cloud journey. During this series of informative podcasts, we'll bring you foundational training on the most popular Oracle technologies. Let's get started! 00:38 Nikita: Welcome to the Oracle University Podcast! I'm Nikita Abraham, Team Lead: Editorial Services with Oracle University, and with me is Lois Houston, Director of Innovation Programs. Lois: Hey there! Last week, we spoke about how hypervisors, virtual machines, and containers have transformed data centers. Today, we're moving on to something just as important—the main cloud models that drive modern cloud computing. Nikita: Orlando Gentil, Principal OCI Instructor at Oracle University, joins us once again for part four of our discussion on cloud data centers.  01:14 Lois: Hi Orlando! Glad to have you with us today. Can you walk us through the different types of cloud models?  Orlando: These are commonly categorized into three main service models: Infrastructure-as-a-Service, Platform-as-a-Service, and Software-as-a-Service. Let's use the idea of getting around town to understand cloud service models. IaaS is like renting a car. You don't own the car, but you control where it goes, how fast, and when to stop. In cloud terms, the provider gives you the infrastructure—virtual machines, storage, and networking—but you manage everything on top—the OS, middleware, runtime, and application. Thus, it's like using a shuttle service. You bring your bags—your code, pick your destination—your app requirements, but someone else drives and maintains the vehicle. You don't worry about the engine, fuel, or routing planning. That's the platform's job. Your focus stays on development and deployment, not on servers or patching. SaaS is like ordering a taxi. You say where you want to go and everything else is handled for you. It's the full-service experience. In the cloud, SaaS is software UXs over the web—Email, CRM, project management. No infrastructure, no updates, just productivity.  02:45 Nikita: Ok. How do the trade-offs between control and convenience differ across SaaS, PaaS, and IaaS? Orlando: With IaaS, much like renting a car, you gain high control. You are managing components like the operating system, runtime, your applications, and your data. In return, the provider expertly handles the underlying virtual machines, storage, and networking. This model gives you immense flexibility. Moving to PaaS, our shuttle service, you shift to a medium level of control but gain significantly higher convenience. Your primary focus remains on your application code and data. The provider now takes on the heavy lifting of managing the runtime environment, the operating system, the servers themselves, and even the scaling. Finally, SaaS, our taxi service, offers the highest convenience with the lowest control level. Here, your responsibility is essentially just using the application and managing your specific configurations or data within it. The cloud provider manages absolutely everything else—the entire infrastructure, the platform, and the application itself. 04:05 Nikita: One of the top concerns for cloud users is cost optimization. How can we manage this? Orlando: Each cloud service model offers distinct strategies to help you manage and reduce your spending effectively, as well as different factors that drives those costs. For Infrastructure-as-a-Service, where you have more control, optimization largely revolves around smart resource management. This means rightsizing your VMs, ensuring they are not overprovisioned, and actively turning off idle resources when not in use. Leveraging preemptible or spot instances for flexible workloads can also significantly cut costs. Your charges here are directly tied to your compute, storage, and network usage, so efficiency is key. Moving to Platform-as-a-Service, where the platform is managed for you, optimization shifts slightly. Strategies include choosing scalable platforms that can efficiently handle fluctuating demand, opting for consumption-based pricing where available, and diligently optimizing your runtime usage to minimize processing time. Costs in PaaS are typically based on your application usage, runtime hours, and storage consumed. Finally, for Software-as-a-Service where you can consume a ready-to-use application, cost optimization centers on licensing and usage. This involves consolidating tools to avoid redundant subscriptions, selecting usage-based plans if they align better with your needs, and crucially, eliminating any unused license. SaaS costs are generally based on subscription or per user fees. Understanding these nuances is essential for effective cloud financial management.  06:05 Lois: Ok. And what about scalability? How does each model handle the ability to grow and shrink with demand, without needing manual hardware changes? Orlando: How you achieve and manage that scalability varies significantly across our three service models. For Infrastructure-as-a-Service, you have the most direct control over scaling. You can implement manual or auto scaling by adding or removing virtual machines as needed, often leveraging load balancers to distribute traffic. In this model, you configure the scaling policies and parameters based on your specific workload. Moving to Platform-as-a-Service, the scaling becomes more automated and elastic. The platform automatically adjusts resources based on your application's demand, allowing it to seamlessly handle traffic spikes or dips. Here, the provider manages the underlying scaling behavior, freeing you from that operational burden. Finally, with Software-as-a-Service, scalability is largely abstracted and invisible to the user. The application scales automatically in the background, with the entire process fully managed by the provider. As a user, you simply benefit from the application's ability to handle millions of users without ever needing to worry about the infrastructure. Understanding these scaling differences is crucial for selecting the right model for your application's need.  07:45 Join the Oracle University Learning Community and tap into a vibrant network of over 1 million members, including Oracle experts and fellow learners. This dynamic community is the perfect place to grow your skills, connect with likeminded learners, and celebrate your successes. As a MyLearn subscriber, you have access to engage with your fellow learners and participate in activities in the community. Visit community.oracle.com/ou to check things out today!  08:18 Nikita: Welcome back! We've talked about cost optimization and scalability in cloud environments. But what about ensuring availability? How does that work?  Orlando: Availability refers to the ability of a system or service to remain accessible in operational, even in the face of failures or extremely high demand. The approach of achieving and managing availability, and crucially, your role versus the provider's, differs greatly across each model. With Infrastructure-as-a-Service, you have the most direct control over your availability strategy. You will be responsible for designing an architecture that includes redundant VMs, deploying load balancers, and potentially even multi-region setups for disaster recovery. Your specific roles involves designing this architecture and managing your failover process and data backups. The provider's role, in turn, is to deliver the underlying infrastructure with defined service level agreements, SLAs, and health monitoring. For Platform-as-a-Service, the platform itself offers a higher degree of built-in, high availability, and automated failover. While the provider maintains the runtime platform's availability, your role shifts. You need to ensure your application's logic is designed to gracefully handle retries and potential transient failures that might occur. Finally, with Software-as-a-Service, availability is almost entirely handled for you. The provider ensures fully abstracted redundancy and failover behind the scenes. Your role becomes largely minimal, often just involving a specific application's configurations. The provider is entirely responsible for the full application uptime and the underlying high availability infrastructure. Understanding these distinct roles in ensuring availability is essential for setting expectations and designing your cloud strategy efficiently. 10:32 Lois: Building on availability, let's talk Disaster Recovery. Orlando: DR is about ensuring your systems and data can be recovered and brought back online in the event of a significant failure, whether it's a hardware crash, a natural disaster, or even human error. Just like the other aspects, the strategy and responsibilities for DR vary significantly across the cloud service models. For Infrastructure-as-a Service, you have the most direct involvement in your DR strategy. You need to design and execute custom DR plans. This involves leveraging capabilities like multi-region backups, taking VM snapshots, and setting up failover clusters. A real-world example might be using Oracle Cloud compute to replicate your VMs to a secondary region with block volume backups to ensure business continuity. Essentially, you manage your entire DR process here. Moving to Platform-as-a-Service, disaster recovery becomes a shared responsibility. The platform itself offers built-in redundancy and provide APIs for backup and restore. Your role will be to configure the application-level recovery and ensure your data is backed up appropriately, while the provider handles the underlying infrastructure's DR capability. An example could be Azure app service, Oracle APEX applications, where your apps are redeployed from source control like Git after an incident. Finally, with Software-as-a-Service, disaster recovery is almost entirely vendor managed. The provider takes full responsibility, offering features like auto replication and continuous backup, often backed by specific Recovery Point Objective (RPO) and Recovery Time Objective (RTO) SLAs. A common example is how Microsoft 365 or Salesforce manage user data backups in restoration. It's all handled seamlessly by the provider without your direct intervention. Understanding these different approaches to DR is crucial for defining your own business continuity plans in the cloud. 12:59 Lois: Thank you, Orlando, for this insightful discussion. To recap, we spoke about the three main cloud models: IaaS, PaaS, and SaaS, and how each one offers a different mix of control and convenience, impacting cost, scalability, availability, and recovery.  Nikita: Yeah, hopefully this helps you pick the right cloud solution for your needs. If you want to learn more about the topics we discussed today, head over to mylearn.oracle.com and search for the Cloud Tech Jumpstart course. In our next episode, we'll take a close look at the essentials of networking. Until then, this is Nikita Abraham… Lois: And Lois Houston, signing off! 13:39 That's all for this episode of the Oracle University Podcast. If you enjoyed listening, please click Subscribe to get all the latest episodes. We'd also love it if you would take a moment to rate and review us on your podcast app. See you again on the next episode of the Oracle University Podcast.

Our guest is the 2026 recipient of the SLAS Innovation Award, Steven Finkbeiner, MD, PhD, of Gladstone Institutes and the University of California, San Francisco. Steven won the prestigious award for his podium presentation, “Development and Application of AI-powered Label-free Imaging for Assays and Screening."Our discussion takes us through his lab's development of an AI-powered, label-free imaging and a closed-loop "thinking microscope" that uses optogenetics and reinforcement learning to perform thousands of single-cell experiments in a single well, dramatically accelerating research into neurodegenerative diseases and beyond.Key Learning Points:AI-powered label-free imaging for assaysDeep learning models in biomedical researchPrognostic markers and disease diagnosis using AIClosed-loop automated microscopy platformsOvercoming challenges and limitations of AI in researchStay connected with SLAS:www.slas.org | Facebook | X | LinkedIn | Instagram | YouTubeAbout SLASSLAS (Society for Laboratory Automation and Screening) is an international professional society of academic, industry and government life sciences researchers and the developers and providers of laboratory automation technology. The SLAS mission is to bring together researchers in academia, industry and government to advance life sciences discovery and technology via education, knowledge exchange and global community building.Upcoming Events:SLAS Europe 2026 Conference and Exhibition (19-21 May 2026 | Vienna, Austria)SLAS Meet-UpsChicago, Illinois (June 18, 2026)Leiden, Netherlands (10 September 2026)Tübingen, Germany (20 October 2026)SLAS 2026 Sample Management Symposium (October 21-22, 2026 | South San Francisco, California)SLAS2027 International Conference & Exhibition (January 30 - February 3, 2027 | San Diego, California)View the full events calendar

Tim Heitmann started Double Good as a 500-square-foot popcorn shop on Navy Pier in 1998 and grew it into a wholesale business that sold to Costco, QVC, and FTD. Then a handwritten letter from a fifth grader who had raised $300 for his band trip made Tim question everything. He walked away from wholesale and poured the company into a fundraising side business that was barely 5% of revenue.In this episode of Predicting The Turn, Tim shares the full arc: how he spent five years quietly building a fundraising tech platform with just three people in a WeWork office, why he focused obsessively on competitive cheerleading as his beachhead market, and how COVID did not create the pivot but revealed a platform that had been five years in the making. When growth exploded in 2021 (400% in Q1 alone), Tim explains the brutal reality of scaling manufacturing, watching SLAs blow from 10 to 47 days, and building a blackout feature to throttle demand before it killed the brand.Tim also explains why Double Good has never taken outside investment, why he thinks in decades instead of quarters, and how he is building an executive team and governance structure so the company can outlast him. If you care about purpose-driven brands, patient entrepreneurship, and what it really takes to disrupt a 100-year-old industry with technology, this one delivers.- From a Navy Pier popcorn shop to a fundraising tech platform- The kid's letter that redirected the entire company- Building the tech platform with 3 people in a WeWork over 5 years- Why competitive cheerleading was the perfect beachhead market- The 4-day fundraiser model vs. the industry standard of 30 days- COVID as accelerant: 400% Q1 growth in 2021- Scaling crisis: SLAs from 10 to 47 days, 3,300 open tickets- Why Double Good has never taken outside investment- Building an evergreen company that thinks in decades

In this episode of the Founder's Sandbox, Brenda McCabe sits down with growth advisor and author Vanessa Golsby to explore what it really takes to scale private equity-backed SaaS companies. Vanessa shares the story behind her new book, The $100M Push: The Four Decisions PE-Backed SaaS CEOs Make to Deliver Growth in 100 Days, and reveals the four critical decisions CEOs must lead to build scalable, resilient growth: defining the ideal customer profile, aligning go-to-market execution, making strategic investment decisions, and creating long-term operational accountability. Drawing from her experience advising more than 100 middle-market software companies and serving as an operating partner in private equity, Vanessa offers an inside look at how investors think, why commercial alignment matters, and how CEOs can create predictable growth through disciplined execution. The conversation also explores the role of generative AI in modern go-to-market strategy, the importance of reputation and purpose-driven leadership, and the entrepreneurial leap Vanessa took to launch her own advisory firm. This episode is packed with practical insights for founders, SaaS executives, and growth leaders looking to scale with clarity, confidence, and purpose. You can find out more about Vanessa at: https://www.linkedin.com/in/vanessa-goolsby/ https://www.linkedin.com/in/vanessa-goolsby https://vanessagoolsby.com/ Or order her book at: https://www.amazon.com/100M-Push-Decisions-PE-Backed-Deliver/dp/1963549309 Transcript: 00:04 Welcome back to the Founder's Sandbox. I am Brenda McCabe, your host. Now in the fourth season, the Founder's Sandbox is a podcast that gathers business owners, founders, professional service providers. 00:31 and corporate directors. And we all are working towards the same mission, which is building scalable, resilient, purpose-driven companies to build a better world. We do this with underpinning, with great corporate governance, and really working with the founders to build that resilience and scalability. My guest, um join me here in what I like to consider a fun sandbox. 00:55 And this month, my guest, I'm actually delighted to invite Vanessa Golsby. Vanessa's joining me from, is it Dallas? Dallas, that's right. Dallas, Texas. So um more here, but thank you Vanessa for joining me on the Founder's Sandbox. And I wanna give a brief introduction to why Vanessa's here today. There's multiple um boxes that she checks, largely Vanessa. 01:22 has her own firm. She is a growth advisor who specializes in scaling private equity back middle market software companies. And it's an interesting time and that space that I'm certain we're going to get to a question here in a minute about the impact of generative AI and all those models out there and the effect on software businesses. You're a seven-year veteran as an operating partner. 01:48 in two private equity firms and portfolio SaaS CEOs. She has helped more than 100 middle market software companies drive growth, execute go-to-market companies, go-to-market, pardon me, turnarounds, and deliver investor returns through sharper commercial execution. That's all in the commercial execution, isn't it, Vanessa? That's right. Yeah. And prior to advising, she was a former operator leading product and commercial. 02:16 teams for 18 years at brands like Travelocity and Financial Times, which I didn't know that when we first were talking. I hadn't realized when we had our first conversations of your corporate experience with Travelocity and Financial Times. So you brought a lot of that corporate kind of know-how into the private equity world and you actually started your own firm. it four months back? 02:44 October, October of 2025. My goodness. So you're not even into your first year. I know. So, and, and, uh, you are an author. So your book, um, so I don't know when you found the time, Vanessa, but your book, the 100 million push the four decisions PE backed as SAS CEOs make to deliver growth. And a hundred days is out. 03:13 Matter of fact, this last week and we're in the third week of April, it uh hit bestseller, right? That's right. Amazon. Yeah. And in that book, we'll get into it. You distill the framework that you've developed. I don't know when, while setting up your own firm, but you developed over decades in the trenches, codifying the sequence behind the big four decisions. 03:40 that enable CEOs to scale with speed, clarity, and confidence. So welcome to the Founder Sandbox. Great. Thanks for having me. Happy to be here. Well, I always like to start with uh my guests to really talk about your origin story. And I think what's very appropriate for today's uh episode is what drove you to actually write a book, right? 04:09 because it distills both your professional as well as um this new tool that you got out there in the market. Yeah, you know, I never thought I would set out to write a book, if I'm being honest. I had, I'd spent, at this point, I'd spent probably about five years as an operating partner, so as a growth advisor for PE firms. And so in that role, I had been 04:38 pretty well practiced at writing best practices. So I understood how to codify a framework and explain it, you know, in long form, basically. But I never had dreams of being like a full author, like writing a book is totally different than writing a best practice. uh But a really strange thing happened about five years into my career as an operating partner. So I'd had about 18 years, as you mentioned, like in the trenches, like a tactical, and then about five years as an advisor. 05:06 And um over the course of those five years, I had developed for myself this framework because when I moved to the firm that I was at at that point, I was having to work on about 10 software companies at a time. And it's really difficult to show results uh efficiently when you're having to focus on so many different companies who have different industries and different sizes and different needs. And so I created this framework just so I could work at scale. 05:35 And uh I had been running it probably about three years at this point when I needed to go back and take a look at some of my case studies. So I wanted to collect case studies. And luckily, because I was still at the firm, I was able to get access to actual data from these companies that had been running the framework. And oftentimes what happens, because I focus on middle market software, there's a sales cycle. So oftentimes what happens 06:04 is we'll run through this framework and we'll see immediate results by way of pipeline and maybe bookings depending on the sales cycle time. But oftentimes we don't see the actual bookings and revenue results until a quarter or two after, depending on what it is that we're selling. So this was really the first time that I had really paused and like done, if anybody here has had to do a case study or fact finding exercise for a PE firm, know like what a... 06:32 slog it is to have to like go look through all this data. I like found the time, I prioritized it. And what I found was, I mean, there was no surprises in terms of like when we wrapped up our, usually my engagements, I try not to be there longer than 90 days. So it's either a 30 day, 60 day or 90 day plan that we run through. It's pretty tight ah in terms of how we manage through it. So by the end of our... 06:57 I have a sense of some results, like whether it's pipeline or early bookings. have some walking away knowing that we've seen some lift, but this was the first time I'd been able to go back like a couple of years to see like, what about those first companies that ran through it? And I'll tell you, Brenda, I fell out of my chair. I was like, I cannot believe the consistency. You can see in the data, like the trajectory, the upward trajectory from when we started working on the framework and then where they were today. And 07:27 At that, that was like the first seed. Like that was like a Thursday. And I was like, I don't know what to do with this information, but I have this information. Oh my gosh, this works. can't believe it. Right. And I really had to sit with that. And over the course of like two or three weeks, a few other things kind of happened that led me to the path of writing a book. Um, and one of those is I was listening to a podcast. I'm an avid podcast listener. 07:54 And I was catching up on April Dunford. She wrote a book on positioning. Obviously awesome. It's a great book for positioning. And I was going to have to run a positioning workshop. And so I was like, oh, let me like get into my head back into the game on messaging. So I just like queued up like the latest podcast I could find from her and then went on a run. And then I was like a captive audience. I went on this run. It turns out the podcast I had queued up was not about positioning. It was about her journey as an author and writing her book. 08:23 So I spent an hour listening and getting really inspired. And when I came back from that run, I thought, you know what? I have to tell the people, there is a way to consistently build and scale companies when they're going from, my framework is very from 10 to that first 100 million. And so that was really the inspiration for me. then it's just been a journey from there. 08:52 We'll get to it, but you uh codified um when you had those aha moments, right? You went back and looked at the cohorts of the companies that you had been working with, right? 30, 60, 90 day framework, for lack of another word. Can you share what are those four things that enterprise SaaS CEOs do? 09:18 Sure, so my framework is an order of operations. So everything that happens at the beginning has like downstream implications on the other activities. And originally when I created this order of operations, I hadn't high leveled it in terms of four decisions. I did that for the book because I wanted to write the book for CEOs. CEOs are such a, especially going to the first hundred million. CEOs. 09:45 have to have their hand on the strategic wheel of commercial growth. not yet mature, they haven't yet matured out of that. There is a place over a hundred where you can start to delegate more of the idea of commercial strategy to like a, you know, top tier executive CRO, for example. But when you're working on the path, especially if you're PE-backed to a hundred, you really need to stay involved. And that had, I had noticed that that core ingredient oftentimes was 10:15 one of the gaps I was inadvertently closing when I was working with these companies. And so because of that, I wrote the book for CEOs. And since I was writing it for CEOs, I was like, oh, I need to go one level higher than my traditional order of operations, which is very like activity sequenced and like talk about more of like, what is like, what is strategy? Strategy is making a decision and committing to it. So what are the four decisions that a CEO needs to direct and commit to have their team commit to in order to see this growth? 10:44 And those four decisions kind of tell the story of growth from up to the first hundred million. Frankly, it's kind of the same above a hundred, except the last decision actually becomes the first decision over a hundred. But anyway, that's right. So four decisions that CEOs that you were saying that are 10 and get to and to get in order to get to a hundred million, they have to be really continuously involved. 11:13 in the growth of the company. They cannot delegate until they reach that um upper level. They don't necessarily need to direct or be boots on the ground in these areas. But when they make these decisions and they guide their teams and champion these decisions, what happens as a byproduct of this is they inadvertently align their business in a way that is 11:43 successful for commercial strategy. So for example, I'll just walk through the decisions quickly to give you an example of how this works. um So the first decision, I high level it as the ideal customer profile or the ICP, which is just another way of saying who are we going to target? And my bit, my specialization is being PE backed. So part of what CEOs and companies hire me for is certainly the pattern recognition of working on over a hundred software engagements. 12:13 but also that sort of behind the scenes view of what the investor is expecting. you know, bringing that idea. When your PE backed, once that investment round closes, are inadvertent, not inadvertently, you are inherently um signing up to expand and grow either within your market, into an adjacent market, or in some other capacity. And just by that definition, you need to, 12:41 understand who your target is going to be, who your best buyer is going to look like for this next round of growth. So it's generally, this is such a major trigger event, this idea of becoming um PE backed, that it's generally a signal for CEOs to say, okay, now let's take a look and see if our existing customer today is going to get us to where we need to be in five years. Because that's five year journey is what you've signed up to take on essentially. So the first 13:10 The first decision is that ICP decision. Once we have an understanding of who we're going to target, then we focus, especially with the commercial side, we focus on how are we going to turn those targets into opportunities, right? So in software, it very much goes from like lead to opportunity to closed one deal, right? So that's what I mean when I say opportunities and or pipeline opening. And this idea of how do we turn targets into opportunities? I high level this decision as the SLA. 13:40 which is a pretty common service level agreement. in this framework, it covers about five or six very specific decisions that your sales, marketing, channel partner and CS teams need to align around to ensure that the build of their lead management system and how they're qualifying those leads to become opportunities is sufficient enough to have some predictability. like you have some confidence that when you put a dollar out, 14:10 into a marketing campaign, it's going to convert into pipeline, really, right? And then ideally into bookings from there. And so that's the second decision. the first one, who do we target? ICP decision. The second, how do we turn those targets into opportunities? The SLA decision. Once you reach... 14:29 Once you have the confidence and some predictability flowing through, now you're ready to make a more strategic decision. And these last two decisions are really where the CEO not just champions, but takes an active role in the decision making. The next one is the contribution decision. So this is now that we know who we're going to target and we understand and have confidence that when we target those buyers, they are going to turn into customers. The next question is where do we invest? 14:57 to go get more of those targets. So who's going to contribute to our revenue number? How much are we going to put into channel partners? How much are we going to invest into marketing? How much are we investing into outbound? How much are we investing into PLG or a self-serve motion, right? How much is new? How much is expansion? And in this decision, we start to bring the CFO in to take more of a governance posture around commercial. So we give the CEO more context around 15:26 Some of the horse trading that typically happens in a silo between the teams. We now have those kinds of conversations around investment decisions and headcount and budgets all together in a room. I run this like a workshop, but all together in a room. And the book teaches the CFO and the CEO how to run this on their own. Excellent. for kind of the terminology that I would use and correct me if I'm wrong, it's kind of capital allocation. So a bit more rigor. 15:56 is brought in with this discipline of budgeting, right? You're talking about contribution decisions, So it's budgeting, capital allocation, and um bringing another uh kind of the controller of the purse strings, the CFO. That's right. Right? And jointly with the CEO are posturing and actually sprinkling it down to their direct reports, I suspect. 16:25 Right. Well, we so the way that I teach contribution modeling is everyone needs to be in the room. No one function, not the CFO, not the CEO, not the CRO can make these decisions for the entire commercial team who is actually going to need to. Yes, it is a budget allocation exercise, but actually that's the second step. The first step, it's a goal setting exercise. oh We break down. 16:53 Each of those pipeline sources has different stages, which we just got very deep on in our SLA decision. So we understand what those stages are called. We understand how long we expect somebody to stick in those stages. We understand what those conversion rates are through those stages. And now that we have some sense of those inputs, we basically enabled ourselves to sign up for a number. So now we can look at marketing and we can say, oh 17:22 If you're gonna sign up for a million dollars in pipeline this year, that means at this selling price, you're gonna drive this many deals, right? At this conversion rate, at this close rate, this means you need to have this many opportunities and that this conversion rate from lead to opportunity, you need to drive this many leads. Can you drive this many leads? And the marketing person's like, that's a lot of leads. I don't know if I can drive that many leads, right? 17:48 And if they hesitate and they say like, can't realistically get that many, we look around the room and we say, okay, who else can drive more leads? Let's look at channel partners. Now we do the same thing from referral to meetings booked to, know, et cetera, et cetera down the So it's very like, it's very precise in terms of setting goals at the funnel stages, but not to become that, like we're not expecting frankly, to get a bullseye out of this workshop. What we're doing is we're kind of snapping the chalk line to say, 18:17 Okay, this is what we think we can go do. And now we're gonna meet with the CFO leading, we're gonna meet every two weeks or every month, and we're gonna see how we're doing. Are we driving this many leads for marketing? Are we getting this many referrals from channel partners? Are we booking this many meetings through the BDRs? And if the answer is no, then we look around the room. Where else can we do it this month? So we have something we can react to in real time, and rather than showing up to the board meeting and saying like, yeah, it was kind of a miss, but I think we have some ideas for next quarter. 18:46 Like this puts everyone in a position now to become far more reactive to what's happening in real time uh as a group, as like a singular one team. And what about the fourth? Yeah, so the fourth decision. And again, this decision is fourth when you're going to 100 million. But if you were above 200 million or as you like progress to like four up to a billion, this actually can become sometimes the first decision. 19:14 when you kind of need to work your way to this point um for when you're going to 100 million, especially after the contribution decision, that contribution. Yeah. Cause that's going to surface a lot of ahas for teams. Like oftentimes you're like, Oh, actually we need to break into a new market. We're saturated or, my gosh, you know, like we need a, you know, too many, we need a ton more reps or actually we don't need more new sale reps. What we need is expansion reps and really need more there. So 19:43 Like in that contribution conversation, you really surface so many of your growth levers that you're prepared for the fourth decision. So the fourth decision is now that we know who we're going to target and we know with confidence how we're going to turn those targets into opportunities. And we understand where we're going to investigate more of those targets. Now we talk about how are we going to do this over the long term? So how are we going to do this not just this year, but for the hold period? So for five years. 20:10 And so this decision I high level as the OKRs, which is an industry term. I didn't come up with that, but it stands for objectives and key results. And it's essentially gives the CEO like almost like a project management framework for long-term planning. um And you really can't necessarily jump to number four if you're going up to that hundred day plan without having these first three decisions at least somewhat cemented or somewhat committed to. 20:39 um Otherwise, what ends up happening is your OKRs are, you know, have like 25 things you're going to try and go tackle. So you kind of like, kind of, you know, by just by um the effort of making these first three decisions, you've already like started to prioritize for your team where the important levers are that you're going to focus on. 21:01 Thank you. I wanted to ask you by publishing this book, are you putting yourself out of business? That's a good question. A grow-to-market advisor, The enterprise SaaS sector that's under a lot of pressure right now with the dinner to bay eye. So let's take the two questions. Let's take them apart. And I'm being a bit. It's a great question. I asked myself that question. Yeah. 21:29 Yeah, my publisher asked this too. Why put it out there? You're putting yourself out of business or no? Yeah. Well, you know, the way I, there's a couple of answers to this, a couple of dimensions to this. The first is, you know, a lot of the motivation to write this book was to get the word out. Like when I saw the consistency and how well the results sustain when companies run through this framework, I was like, Oh my. 21:56 Why aren't we telling all of the CEOs that there's a way to go do this? Like we know these activities, it's things like territory planning and quota setting and SLAs. like, know, people know that activities that need to happen, but the unlock here is the sequence, like it's important to do them in order and that they're done altogether, which is the role of the CEO, right? Is to ensure that the right people are in the room when you're making these decisions and everything's like. 22:24 That's the those are the connectors right is are the those are the interlocks are the decisions the activations happen You know within the function so I? Was passionate like we talk about purpose the reason I was excited to be on this podcast is because this is very purposeful for me It felt like holy cow Look what I discovered under the pyramid I got to tell the people like there's an easier way to do this We don't have to bang our head against the wall to try and figure this out the hard way so 22:53 In that way, it didn't really feel like an option to necessarily hide it. ah And then the other side of me thought about it in terms of like changing the oil in my car. Like, I know that I can change the oil in my car. It's not a difficult, complex process. Like, it's very straightforward. But do I want to do, do I want to like get in coveralls and crawl underneath my car, like find the little lackey thing? No, I don't want to do any of that. I would far rather just bring someone in. 23:22 take the guesswork out, have it done, have it done correctly the first time, and leverage someone else's expertise in case they find something that I wasn't expecting. ah So I feel like I'm still bring, like when people leverage me to run through this, I'm still bringing a lot of value that you're not gonna necessarily get out of the book. mean, people, CEOs and firms hire me because of the pattern recognition and because I've seen these things play out enough times across different industries. 23:51 uh But I don't want to be a holdup. Like, please, if you are able to do it, then I welcome, I encourage you please to go run these plays yourself. And I try to give a lot of, it's very structured. This book is, the structure of this book was really difficult to come up with. It probably took me the longest amount of time, honestly. But I wrote it in a way that a CEO could read it quickly, because I know they don't want to read too many things. They are very busy. um 24:18 And so like they could digest it quickly and they could hand it off because that's kind of their role is to say like, I'm going to now equip my leaders to go do this and do it successfully. And they still have a role to play. But again, they don't have to be like in the trenches. Right. And without um seeing the book right now, I sound and Kendall on audibles or Kendall, um are there like exercises? Are there, is it like a handbook or is it um I'm a CEO? I 24:48 read your book um and I want to contact you. Do I to come in and maybe do some seminars? How does that work? Because this is a marketing tool as well. Yeah, yes. mean, of course I this book can be just a step by step guide for CEOs and their teams if they want to take it that way. So I tried to write it dimensionally. So the first dimension is 25:13 It equips the CEOs to understand, like the first two chapters are really around what is the investor expecting of you? Basically it's like, here's a little bit of the behind the scenes. Yeah, that was intriguing for me when we first spoke of it. Yeah, you've been in that room. Yeah, like I've been in it. Yeah, exactly. like, you know, one of the things that, again, like a lot of things happened in this like two or three week time period when I was kind of coming to the conclusion that I was going to write this book. And one of them was I was in a board. 25:44 meeting and there was a CEO advisor also in this board meeting and I could see the CEO advisor was um giving great advice based on their singular experience but the truth is is their experience was so unique to them that it would be really difficult it'd be like saying like 26:07 Yeah, just, once you press post, it's gonna go viral. It's like, let's not over promise here, you know, what's realistic. And that really hit me to say like, oh, this is a unique perspective. Like I'm not necessarily an investor and I'm not a CEO. it's been years since I've like managed a commercial team or been a GM, but I have... 26:34 I've flown all of those altitudes and I've been an observer in all of those rooms so many times that like the patterns, you just can't deny the patterns. um So yeah, I'll stop there. I'll pause there. So you do the reveal, right? So for any CEOs of enterprise, um SAS companies, this is a must read, right? Because you're doing the real deal. What is actually happening in the boardrooms of those private equity? uh 27:05 partners right that are yes looking at their portfolio companies yes yes thank you yes so i start with like you need to equip yourself with understanding what is expected of you when you took this investment which isn't frankly always talked about like it's not always revealed to the CEO ah so that's the first step and then it is a step-by-step guide so like there are the four decisions and then within each decision 27:33 I show them the book is structured to show them, tell them what the decision is, give them some case studies of other companies who have solved it, give them some red flags that say like, look, this is a really helpful book if you just closed your investment and you need to run like a, they call it a hundred day plan of like, you're going to deploy a lot of that, those investment dollars very quickly in order to like try to get traction on growth. So this is, I wrote it in that framework just because it is naturally 28:00 predisposed to running in like a 90 day plan framework anyway. um But it's also one that oftentimes in a hold period, you're going to hit some kind of plateau, right? It's very rare to like knock a home run out of the park right out of the gate. And so I also, so like in that, in that first part, so like each part, each decision has a part. So there's like a part for, there's like a four chapters on ICP, four chapters on SLA, four chapters on contribution. 28:26 The first chapter tells you, like gives you the red flags to look for if this is an issue, tells you what the investor is expecting, tells you your role and how you can direct the team, tells you when you need to maybe outsource, like what's the things you should absolutely do and the things that are kind of like nice to haves. Then the next chapter goes into how do you make this decision? And each of these decisions, the way that my approach is, 28:53 Um, is I like to do like 50 % gut and like 50 % data. So I always start my engagements with like surfacing from your internal experts already. Like a lot of times your C-suite lieutenants. Yeah. They like, I get called in for audits. Like that's like oftentimes I'm brought in initially for an audit of some kind. And in that audit, it's like a 360 commercial audit. And in that audit, I have like a week that I just cap off and I talk to anyone that you'll let me talk to. 29:23 And they're telling me the problems. like, this is really like, we've known this is very rare for people to like, I have no idea. They know what they did to get here. And so we start with the gut. And so in this framework for the book, the gut is surfaced through workshops. I'm a huge advocate of workshops. think, you know, honestly, my time with Vista really beat this into me, like the importance and the value of workshops, because not only is it a great place to surface everyone altogether, but it's 29:52 early adoption. Like when your voice is heard and you could challenge something in the room, when the decision is being made, you're far more likely to adopt it when we get to the final output. So I'm a huge fan of workshops. So each of these has a workshop. And this is a lot by and large when I'm training, when I'm teaching the CEOs, it's like, this is what you need to get out of the workshop. This is agendas. You can, have all of my agendas are up for download. Like you can download the agenda. You can run through it yourself. And this is who needs to be. 30:21 Yeah, like I want this to be helpful. That's the whole point is like it's supposed to be taking the guesswork out for the CEOs. uh And then you need to there's a data validation. Like, yeah, everyone's got gut. But then we do need like we are going to make some commitments here. So exactly. Yeah. So we need to like in each of these have different places that you go and source that data to validate. uh 30:43 So that's how we make the decision. Then I go through how you execute the decision. And for CEOs, this is almost like the TLDR. It's like, give you like, look, these are the steps that they're go through. Then in each of these chapters, I go far more into detail. This is what you're gonna go tell, like this is what your management team is gonna go do. And this is what good is gonna look like. So you're not done with this step until you've seen these five things come out of this exercise, essentially. 31:07 And then finally, each of these parts, so we've got like, what is the decision? How do we execute the decision? I'm sorry, how do we make the decision? How do we execute the decision? And then how do we measure the decision? And this goes back to how your growth story. So a CEO's role is not just to understand, right, our long-term objectives that may be surfaced in our investment thesis, right? Those are the first two chapters. It's not just coordinating the execution and setting the priorities and resourcing your team, right? Those are the four decisions. 31:37 But you also need to tell that story and you need to tell it in a way that makes you show well, that makes your company show well, and that makes you more attractive, frankly, at your next round of investment. so, yeah, externally telling exactly. So as well as internally. that's right. So that was really long winded, but that's basically the structure. It goes pretty far into detail, but I do. 32:02 high level for CEOs, like you can skip this part, just give it to your zero. So, so the book is out and um you started as you went rogue yourself and said, I'm working for myself and yeah, that's right. And um what happened is you've got some of your clients that had seen your, your work in prior years and, have taken you on as their advisor. 32:31 Why are they taking you on? it around your, are you scalable or your purpose? I mean, you're wanting to give back. So yeah, tell me. And you shared a little bit when we were talking before the podcast about you got a call from a client that you had from many, many years ago. Yeah. Yeah. I, you know, when I was deciding to go out on my own, it was really scary, right? Because I had, I never really even, I, I had been motivated to write the book. 33:00 And that was almost as far as my thinking had gone. And then at that point, the book was supposed to come out. Originally, the book was supposed to come out in January and we could have a whole other podcast about writing a book. so originally it was kind of, I knew like internally, I was like, gosh, by October, I was like, I need to make a decision. Like, what am I going to do? Am I staying? Am I going? Am I doing something else? And so I reached out to every person that, that I, you know, had some sort of like respected conversation, like a respected relationship with. 33:29 over the course of my career. And I basically asked him like, what do I do? What would you do? And I'm really lucky because at this point, I had been an advisor for about seven years, you know, with really established firms and the folks that I had worked with, that knew me, knew what I could do, had since gone on to a million other firms. So like my network on the firm side was pretty large. 33:59 And in those conversations, there was just inevitably a conversation that ended with like, look, if you go, I'll give you your first client right now. And so I was like, well, there you go. Close the door, a window, let's go. That was how it went. Yeah, so you reached out to your network, which is super powerful. Yeah, it really was. And it was honestly, I had surfaced my network throughout kind of writing the book because 34:27 You know, one of the things I think that is unique about my situation versus some of the other authors who have written fantastic, and I'm an avid business book reader, Fantastic Frameworks, is that my perspective is from the operating partner's point of view. And I am, yeah, it's very like, and so I'm really lucky because I, as I mentioned, like a lot of the folks that I have worked with over the years are now at so many different firms. 34:57 And so as I was writing this book, I would send out surveys to people and just say, Hey, just like gut check, do you see this too? Are you seeing this? Like when I wrote a whole chapter on like the value creation plan and you know, the value creation plan is one of those things that people talk about. Like it's this like standardized formal process, but it's wildly different, like firm to firm, like it's so totally different. And I just wanted to uh get a better sense of how these different firms of these different sizes were actually running their value creation plans. 35:26 And that's just impossible for me to do by myself. Like I need my network for that. So this whole process has been really great. And just like also bringing together some of my work friends that I hadn't been able to really, or I hadn't like, you know, kept up with as well as I should have. And so now I feel like my network is just like really thriving and humming. And I feel so much closer to like these people now than I have in a long time. So it's been really beautiful in that way. 35:54 Thanks for sharing. know, I want to ask you how has, well, your frameworks be at all affected in your opinion by the generative AI and how it's taken quite a bit of value out of the stock market. So now it's back up, right? So let's, so was, are you isolated from that effect? Your, your, your, your, just your, your frameworks. 36:22 Yeah, you know it's funny I wrote this book so I've done a lot around writing best practices for AI for go-to-market teams so I was pretty what by the time I wrote this book I had a lot of already like pretty packed research and thinking around AI and what it could do and what it couldn't do. I of course how could I you know I wrote this book almost two years ago now like 36:46 has really changed the game and just some of the new models that have come out. We knew that they were gonna be pretty revolutionary, but it was hard to be very specific. But I did, in the book, I have a very specific point of view on how AI can ah make what you do more effective, more scalable, where can use what you are bringing to the table and... uh 37:12 The word is escaping me, which is ironic scale, basically what you could do. And so that's my approach to AI and it's still my approach to AI. So I don't see AI as a competitor. I see it as an accelerator, really. And so I'll take account scoring as a great example. So in this idea of 37:38 these four decisions, one of the activities that you inevitably will need to do, it's under the ICP decision. So once you have an understanding of who you're going to target, you want to then score the accounts that are in your database to say like, is this a tier one, is this a tier two, is this a tier three, is this a tier four, and we're not gonna like, they're actually gonna churn too fast for them to even be worth that selling to. And so you're building out this account scoring model. Now, there are platforms that can just do this for you. 38:06 and they're just like, look at your data and they're like, great, we're gonna do this for you. But those platforms don't know your growth plan. They don't understand like what your investment thesis is. They don't understand that you have a very concentrated point in time where you're going to make, you know, a 30 % CAGR, you know, you've got like big, big goals. You're not just trying to do status quo every year. And so it's in that same kind of vein, like the human still needs to drive and be the director of... 38:33 where the AI is going to execute. um But AI is a fantastic accelerator. I'm excited. I love partnering with AI. It's not perfect. I think of it as almost like an MBA intern, like whip smart, smarter than I will ever be. But you can't totally take your hands off the wheel. You're like, there's context. That's great analogy. Oh my goodness, that's hilarious. It is true. um 39:03 AI. particularly like the perplexity model because it's on top of all of them for uh writing and preparing some of the work I do with my clients. So it becomes my companion is what I call it. Right? Yeah. Oh yeah. Definitely. Excellent. Well, I'd like to give you an opportunity to share how my listeners can reach out to you. Oh, sure. They'll be in your notes. Vanessa. Carry on. Okay. Great. 39:32 So I have a website Vanessa ghouls be calm I'm also on LinkedIn both ways You know are pretty easy ways to just you can look at my calendar and schedule time if you're interested Often time like my most most of the ways that I get brought into engagements is There is some kind of trigger event where the CEO or the PE firm Says like we need we need some 39:59 things, some kind of audit, some kind of assessment, some kind of strategy, some kind of like, what are our growth levers, right, to get us to whatever the next thing is. It's generally a two to four week audit. em And as I mentioned earlier, it combines interviews with your team with I have like a list of artifacts that we start off with. It's, I don't want to say it's like diligence, because it's not like diligence. But it is a pretty thorough 40:25 uh So you get sales, marketing, customer success, channel partners, digital, all of that. uh And oftentimes CEOs will have like a specific need on top of that. you know, I've got one where I just did one where it was like, we want to see, you know, we know we just got our investment came through and we kind of need to set our hundred day plan. So where should we go? You know, what are the foundations we need to build and fortify for this next round? uh We have one. 40:53 One other trigger that's pretty common is on the back of maybe M &A, where you have like two go-to-market teams that need to integrate together. Yeah, they like will bring me into sales. How are we gonna do that? Yeah. Or they have done that and maybe they're still not quite hitting that like expansion number that was originally conceptualized. um And then, yeah. And then the third, which is, I mean, it's like the... 41:21 the least positive, but honestly, the most exciting for me is, you you're like an a mid hold plateau. You're like, gosh, you know, I had one just last month where it was like, they hit this $30 million ceiling and they for like three years have thrown every spaghetti they could at the wall and just could not get past this ceiling. And, um, and so like the audit can, it's very focused and like trying to get to whatever the objective is, but it's, it's holistic because my whole, my whole shtick, right. Is that like, 41:51 It's no one team. It's like all of the teams kind of have to interlock in a line together. Yeah. Yeah. Quite revealing. Excellent. Those are excellent use cases. Um, and we'll put this in the show notes as well as your website and Vanessa. Um, let's come back to the sandbox. I do like to do a round of just questions about three words and what is the meaning for you. Um, and each of my guests comes up with their own um interpretation, their own meaning. it's 42:19 So what does resilience mean to you, Vanessa? Yeah, think resilience means being internally motivated. There's a drive that is not necessarily anchored or reactive to anything that's happening externally. uh For some reason, you just can't let it go. 42:47 How about scalable? What's scalable? Oh, wow. I mean, spent so many years uh writing about being scalable. Yeah, you know, it's funny when I think about being scalable, you know, it actually initially comes to mind as like growing pains, like this idea of growing pains. uh And I'm just now kicking myself for not reading the prep questions closer. We're going to rip a little bit, but. 43:15 But yes, being scalable is having that resilience through the growing pains, knowing, right, having like some kind of faith that at the end it's gonna be bigger, better, probably bigger than you even really could even have imagined or maybe even in a direction that might not have been initially planned. Excellent, excellent. Yes, and I also wanna just, I think. 43:43 you know, we're back to the title of the episode, is, um, and which is building purpose, building reputation with purpose. And you were adamant about that. So what does purpose mean? And maybe you'll bring into, know, what, what is building reputation with purpose for you? know, I, um, 44:11 It's funny, I feel like it really goes back to this resilience question, but it's so much of it just comes down to acting with kind of like, like I work with companies that have like cultural values, right? And they're like, oh, or Patrick Lindsay only has a great one, like the heat, likes to say, you know, hire people that are hungry, humble and smart, right? So like, you have your like keywords, your brand words, your value words. And I think for me, 44:40 um over the years, my purpose has been to act with integrity and grace and curiosity. And, um and that's something that I don't think about logically, right in life. But I try to bring that kind of inspiration to the teams that I'm working with. And it's a lot of the reason why I wrote the book was to say like, 45:10 Look, there is a way. You don't have to follow every single thing that's in this book. But if you get stuck, isn't it helpful to have a guide, like a troubleshooting guide to say like, oh, let me just go to the index here. I'm a little stuck on territories. I'm going to get over it. And that's the spirit that I try to bring to everything that I do, which is, yeah, we can solve any problem. Like any problem is solvable. And guess what? Execution problems are the easiest thing to solve. So like, 45:40 Let's have some fun and we can, we can, there's a way to do it basically. Right. Excellent. Thank you. And last question, did you have fun in the sandbox today? I had so much fun. This was great. You know, honestly, I didn't really know how this, like I do enough of these podcasts now and it's so usually anchored on the framework and like, you know, the execution and like, you know, very tactical. 46:07 And so this was just a really, this was like a breath of fresh air because we got to talk a little bit about the human side of it, which I find really motivating. It is. And I do recall you were really set on building you and you it's your reputation. Do you have Vanessa Goldsby that has gotten to you, gotten you where you are today and by giving back and providing that, you know, writing that book and then, you know, serendipity, you decide, Oh my gosh, I'm going to go out on my own. So it's, your reputation. 46:35 that has been built with purpose. I want to thank you for joining me here in the Founders Sandbox. To my listeners, if you like this episode with Vanessa Goldsby, sign up for the month release of the Founders Sandbox where I have guests that are Founders, business owners, service providers like Vanessa, um and board directors who build with strong governance, resilient, scalable, and purpose-driven companies. 47:03 So signing off for this month. Thank you very much. Thank you, Brenda.

In our first episode of Thrive in Science: Women's Leadership Edition, hosts Ginger Cooper, CEO of Summit Success Group, and SLAS Scientific Director Madeline Farley, PhD, introduce themselves, share their career journeys, and share the inspiration behind launching this new podcast spotlighting women in science. They talk about what it means to thrive in the field, the many paths to leadership, and what's ahead in upcoming conversations. They also share where you can meet the hosts in person at SLAS Europe 2026 in Vienna, 19–21 May. Want to learn more? Check out our press release. We're always looking to highlight inspiring women in science. If there's someone you think should be featured on Thrive in Science, we'd love to hear from you. Please fill out this form. Stay connected with SLAS:www.slas.org | Facebook | X | LinkedIn | Instagram | YouTubeAbout SLASSLAS (Society for Laboratory Automation and Screening) is an international professional society of academic, industry and government life sciences researchers and the developers and providers of laboratory automation technology. The SLAS mission is to bring together researchers in academia, industry and government to advance life sciences discovery and technology via education, knowledge exchange and global community building.Upcoming Events:SLAS Europe 2026 Conference and Exhibition (19-21 May 2026 | Vienna, Austria)SLAS Meet-UpsChicago, Illinois (June 18, 2026)Leiden, Netherlands (10 September 2026)Tübingen, Germany (20 October 2026)SLAS 2026 Sample Management Symposium (October 21-22, 2026 | South San Francisco, California)SLAS2027 International Conference & Exhibition (January 30 - February 3, 2027 | San Diego, California)View the full events calendar

A maioria dos programas de AppSec está afogada em findings, dashboards, scanners, CVEs, SLAs e relatórios que ninguém aguenta mais ler. O problema não é falta de ferramenta. O problema é falta de contexto, correlação e inteligência para entender o que realmente importa. Neste episódio, eu apresento o M.A.R.I.A., o Management Application Risk Integrated Analysis, uma plataforma criada para atuar como uma camada de inteligência de risco em Segurança de Aplicações. O M.A.R.I.A. não nasceu para ser mais um scanner. Ele nasceu para responder perguntas que ferramentas tradicionais normalmente ignoram: qual aplicação está realmente em risco? Qual vulnerabilidade merece atenção agora? Qual time precisa de ajuda? Qual mudança aumentou o risco do ambiente? A proposta é simples e ambiciosa: conectar dados de SAST, DAST, SCA, IaC, Secret Scan, pipelines, repositórios, contexto de negócio e exposição real para transformar ruído em decisão. Porque no fim do dia, AppSec não deveria ser uma fábrica de tickets. Deveria ser um sistema de priorização inteligente para proteger o que importa. Neste episódio, falo sobre:Por que scanners sozinhos não resolvem AppSecO problema real por trás do excesso de vulnerabilidadesA diferença entre dashboard, ASPM e inteligência de riscoComo o M.A.R.I.A. pretende correlacionar contexto técnico e contexto de negócioOnde entram risco, exposição, criticidade, SLA, dívida de segurança e Security ChampionsPor que AppSec precisa sair do modo “lista de problemas” e entrar no modo “tomada de decisão”Um episódio para quem está cansado de medir segurança por quantidade de findings e quer começar a discutir risco de verdade.Become a supporter of this podcast: https://www.spreaker.com/podcast/devsecops-podcast--4179006/support.Apoio: Nova8, Snyk, Conviso, Gold Security, Digitalwolk e PurpleBird Security.

In this episode, we're joined by Anneke Mühlebach, Director Marketing Lab Productivity Innovation of Agilent Technologies, to preview the company's upcoming NexusXp Flash Talk at SLAS Europe 2026.The discussion explores the NexusXp theme of "the connected lab," which blends hardware, software, and human ingenuity across three levels of lab automation: guided workflows in the human-operated lab, fully automated work cells, and vendor-neutral data access. Anneke highlights Agilent's integration of hardware, software, and human factors in lab automation, real-world applications, progress through smart partnering and customer collaborations, and future industry trends. Key Learning Points:Lab productivity and automationRole of data standards and vendor-neutral formatsCollaboration with partnersCustomer-centric innovation and co-creationRegister for SLAS Europe 2026 (19-21 May | Vienna, Austria)Lean More — featuring 135+ exhibitors, keynote and podium speakers, behind-the-scenes access to a leading biotech campus, a rich ­networking program and more!Thank you to our Sponsor: Agilent TechnologiesAgilent supports scientists in 110 countries in cutting-edge life science research; patient diagnostics; and testing required to ensure the safety of water, food and pharmaceuticals. Our advanced instruments, software, consumables, and services enable our customers to produce the most accurate and reliable results as well as optimal scientific, economic, and operational outcomes. DE-014621 Stay connected with SLAS:www.slas.org | Facebook | X | LinkedIn | Instagram | YouTubeAbout SLASSLAS (Society for Laboratory Automation and Screening) is an international professional society of academic, industry and government life sciences researchers and the developers and providers of laboratory automation technology. The SLAS mission is to bring together researchers in academia, industry and government to advance life sciences discovery and technology via education, knowledge exchange and global community building.Upcoming Events:SLAS Europe 2026 Conference and Exhibition (19-21 May 2026 | Vienna, Austria)SLAS Meet-UpsChicago, Illinois (June 18, 2026)Leiden, Netherlands (10 September 2026)Tübingen, Germany (20 October 2026)SLAS 2026 Sample Management Symposium (October 21-22, 2026 | South San Francisco, California)SLAS2027 International Conference & Exhibition (January 30 - February 3, 2027 | San Diego, California)View the full events calendar

The episode identifies a structural shift in how AI adoption is being managed within IT environments: control and accountability are now central concerns, overtaking simple discussions of AI usage or feature deployment. Shadow AI—unmanaged or improperly governed AI agents—has emerged as a tangible risk vector. Government entities, such as the White House, and technology vendors including Microsoft, Cisco, and OpenAI are framing AI not only as a productivity tool but increasingly as a source of operational and security liabilities that demand more robust oversight. A key example comes from an incident reported by TechRepublic in which an AI agent within a coding workflow deleted both a production database and its backups, resulting in a prolonged, business-impacting recovery from a three-month-old backup. In parallel, the Hacker News highlighted findings from scans of one million exposed AI services, characterizing the market's current AI security posture as lacking, with many endpoints widely reachable unintentionally. Microsoft's public transition of Agent365 from preview to release was directly tied to fears over the risks associated with shadow AI, indicating industry recognition of autonomous agents as a new attack surface requiring governance. Supporting developments further validate this trend. Cisco's open sourcing of AI Bill of Materials (BOMs) tools, Wiz's tracking of non-human identities tied to AI workloads, and OpenAI's rollout of advanced account security all signal a growing industry emphasis on making AI deployments auditable and restrictable. Practices such as phishing-resistant authentication—driven by token theft campaigns analyzed by Microsoft—and continuous permission monitoring, as advocated by Material Security, are now increasingly viewed as necessary safeguards rather than optional enhancements. Providers like Enforcer and products such as Copilot Manager are explicitly focused on surfacing shadow AI usage and enforcing credential discipline, underlining the growing demand for proof-of-controls. MSPs and IT service providers now face greater operational complexity and contract risk tied to AI automation. Client expectations are shifting from baseline AI access to demonstrable governance—requiring non-human identity inventories, documented permission boundaries, and validated recovery frameworks for AI-powered workflows. Token harvesting and persistent OAuth grants increase the likelihood that MSPs will be held responsible not just for prevention, but for rapid containment, rollback, and producing evidence during security incidents. Failure to meet tightened SLAs around backup immutability, authentication protections, and agent visibility could soon become a material contract exposure. 00:00 Agents Gone Rogue 03:50 Govern the Agent 06:24 MSP at Risk 09:54 Why Do We Care?  Supported by:  CometBackup ScalePad  Upcoming event:  The Pivotal Point of IT: Building Services for the AI-First Era Date: May 13 at 1p.m. EDT Register: https://go.acronis.com/davesobelaiera

Have an idea for an episode? Contact us!Thank you to SLAS Europe 2026 Sustainability Sponsor, PulpFixin, for sponsoring this episode.PulpFixin CEO Chad Jenkins returns to discuss the urgent need for sustainable sample management. He presents proven solutions, such as pre-barcoded tubes, standardized racks and new plastic-free alternatives like PulpFixin's Auto-Rack and Auto-Sleeve, that can save on freezer space and costs, improve data integrity, and divert waste from landfills.Key Learning PointsLatest trends in sustainable sample managementReducing the impact of necessary plasticsHow to transition from legacy systems to new technologiesAbout PulpFixin:PulpFixin is a leading manufacturer of sustainable products and packaging. We are dedicated to eliminating single-use and other unnecessary plastics. Our expertise lies in designing and producing products and packaging from compostable or biodegradable sustainable materials to fully replace traditional plastics, and we welcome you to collaborate with us.Interested in lab sustainability? Join our Sustainability in Sciences Topical Interest Group!Register for SLAS Europe 2026 (19-21 May | Vienna, Austria)Lean More — featuring 135+ exhibitors, keynote and podium speakers, behind-the-scenes access to a leading biotech campus, a rich ­networking program and more!Stay connected with SLAS:www.slas.org | Facebook | X | LinkedIn | Instagram | YouTubeAbout SLASSLAS (Society for Laboratory Automation and Screening) is an international professional society of academic, industry and government life sciences researchers and the developers and providers of laboratory automation technology. The SLAS mission is to bring together researchers in academia, industry and government to advance life sciences discovery and technology via education, knowledge exchange and global community building. Upcoming Events:SLAS Europe 2026 Conference and Exhibition (19-21 May 2026 | Vienna, Austria)SLAS Meet-UpsChicago, Illinois (June 18, 2026)Leiden, Netherlands (10 September 2026)Tübingen, Germany (20 October 2026)SLAS 2026 Sample Management Symposium (October 21-22, 2026 | South San Francisco, California)SLAS2027 International Conference & Exhibition (January 30 - February 3, 2027 | San Diego, California)View the full events calendar

Dave discusses how Flotek scaled its finance and billing operations from a simple setup (a bookkeeper and a director overseeing finances) to a more structured team while growing rapidly through acquisitions. He explains their philosophy that client-facing billing is part of service delivery, with SLAs and a "wow" mindset to protect relationships and reduce friction from invoice errors. The conversation covers challenges of cost-of-sale reconciliation amid inconsistent vendor billing, the need to accept imperfect acquisition data, and using standard cost models and monthly margin monitoring (with more precision where margins are tighter, like Microsoft). They emphasise simplifying vendors/products, building processes and controls across sales, projects, and finance, capturing historical billing data, and balancing automation with necessary manual review. Dave notes they reached £18M revenue in 3.5 years and wishes he had hired earlier, stressing upfront investment in scalable systems, culture, and pricing for long-term growth.   00:00 MSP Finance at Scale 00:50 Early Acquisition Setup 01:47 Billing as Customer Service 05:24 Wow Factor and Trust 08:17 Cost Reconciliation Reality 10:14 Standard Costs and Margins 14:45 Automation and AI Tools 17:39 Limiting Complexity 19:53 Team Size and Reporting Depth 23:24 Sales Ops to Finance Handoff 27:46 Lessons from Rapid Growth 29:32 Closing and Contact Connect with Dave Middleton on LinkedIn by clicking here – https://www.linkedin.com/in/david-j-middleton/ Connect with Daniel Welling on LinkedIn by clicking here – https://www.linkedin.com/in/danielwelling/ Connect with Adam Morris on LinkedIn by clicking here – https://www.linkedin.com/in/adamcmorris/ Visit The MSP Finance Team website, simply click here –https://www.mspfinanceteam.com/   MSP Glossary: MSP Finance Glossary Explained | MSP Finance Team We look forward to catching up with you on the next one. Stay tuned!

In this episode, Philip Kiely, head of AI education at Baseten, joins us to unpack the fast-evolving discipline of inference engineering. We explore why inference has become the stickiest and most critical workload in AI, how it blends GPU programming, applied research, and large-scale distributed systems, and where the line sits between inference and model serving. Philip shares how research-to-production can move in hours, not months, and why understanding “the knobs” of inference—batching, quantization, speculation, and KV cache reuse—lets teams design better products and SLAs. We trace the inference maturity journey from closed APIs to dedicated deployments and in-house platforms, discuss GPU lifecycles, and survey today's runtime landscape, including vLLM, SGLang, and TensorRT LLM. Finally, we look ahead to agents and multimodality, making the case for specialized, workload-specific runtimes when performance and efficiency matter most. The complete show notes for this episode can be found at https://twimlai.com/go/766.

The dominant structural shift outlined in the episode is the destabilization of the classic per-seat MSP bundle caused by the rise of agentic AI and token-based, metered automation platforms. Vendors such as Kaseya, Google, and OpenAI are embedding persistent AI agents within core business applications, moving beyond traditional licensing models to charges based on actions, tokens, and workflow usage. This introduces margin instability, as MSPs cannot reliably predict costs or maintain flat-rate contracts in an environment where AI consumption is dynamic and externalized. The most consequential evidence presented is the quantification of AI-driven inefficiencies and costs in operational terms. According to a Gallup poll, cited by ZDNet, half of US employees are now using AI at work, but those users waste up to eight hours weekly managing AI-related tasks—amounting to approximately $1.25 million drag per year for a 100-person firm. This data underlines how the proliferation of automation does not equate directly to labor savings and can introduce significant, unanticipated costs that are difficult to contain under legacy MSP pricing models. Supporting developments further highlight the governance gap and operational risk. Reports from PRWeb and Ruist find that 97% of MSPs intend to automate more in 2024, but only 4% are “highly mature.” Vendor announcements—as with Kaseya's agentic IT management platform, Auvik's Aurora AI agents, and Liongard's data control enhancements—are paired with warnings from Information Week and The Register about the risk of overspending, audit failures, and accountability gaps tied to AI-driven automation. Most IT managers lack full control over AI agents, and as agents proliferate, the difficulty of tracking, governing, and assigning accountability rises. For MSPs and IT service providers, these changes demand immediate attention to contract structure, governance, and pricing. Flat-rate, all-you-can-eat support models expose providers to untracked vendor consumption and hidden overages, making traditional agreements economically unstable. Practical safeguards require shifting toward consumption-based or outcome-based billing, enforcing explicit usage caps, audit controls, and vendor SLAs that clearly define liability and accountability. Failing to adapt risks absorbing uncontrolled automation costs and shouldering client disputes over AI-driven actions and expenses. 00:00 AI Overhead Crisis  04:48 Agent Control Gap 07:17 MSP Margin Squeeze 12:00 Why Do We Care?  Supported by:  Acronis Zero Networks Nerdio  Upcoming event:  The Pivotal Point of IT: Building Services for the AI-First EraDate: May 13 at 1p.m. EDTRegister: https://go.acronis.com/davesobelaiera

Send us Fan MailA single compromised identity can turn your whole environment into a hallway of unlocked doors and cross-domain attacks are built to exploit exactly that. We start with a timely real-world breach theme and use it to explain how adversaries move between endpoints, cloud platforms, and third-party connections by abusing identity and privileged access, not just by running noisy malware. If your organization relies on a patchwork of identity tools, limited visibility, and “normal looking” logins, you may not see the threat until it has already jumped domains.From there, we pivot into CISSP Domain 8.4 thinking: how to evaluate acquired software without guessing. We break down what to look for in open source software (community activity, maintenance signals, orphaned project risk), what makes COTS software uniquely hard to assess (no source code visibility for deep vulnerability assessment), and what matters most for SaaS and managed services (encryption for data at rest and in transit, plus clear SLAs that define performance metrics and incident response expectations). We also cover why the shared responsibility model is non-negotiable for cloud security clarity, especially around account management and access control.We round it out with hands-on evaluation methods that map to both the exam and real security programs: threat modeling to uncover dependency risk, dependency scanning to catch vulnerable libraries, sandbox testing in a controlled environment, and periodic reassessments as threats evolve. If you're studying for the CISSP or building a safer vendor and software intake process, this one gives you a practical checklist mindset. Subscribe for more CISSP training, share this with a study partner, and leave a review with the software risk topic you want us to cover next.Gain exclusive access to 360 FREE CISSP Practice Questions at FreeCISSPQuestions.com and have them delivered directly to your inbox!  Don't miss this valuable opportunity to strengthen your CISSP exam preparation and boost your chances of certification success. Join now and start your journey toward CISSP mastery today!

Have an idea for an episode? Contact us!In this episode, we're joined by members of Beckman Coulter Life Sciences and HSE•AG, Ian Shoemaker (Beckman Coulter) and Konstantin Lutze (HSE•AG), to discuss their SLAS 2026 New Product Award-winning collaboration, the eviDense UV Photometer: an on-deck module that seamlessly integrates into liquid handlers to measure optical density and absorbance - ideal for quantification and purity assessment of DNA and RNA samples.They explore the collaboration behind its development, technical features, applications in genomics and diagnostics, and its impact on automation and workflow efficiency.Key Learning Points:What led to this collaboration between Beckman Coulter Life Sciences and HSE•AGTechnical innovation in UV photometryApplications in genomics and diagnosticsAbout Beckman Coulter Life SciencesWe develop innovations for scientists by scientists, with many of our 3,300+ global colleagues coming from the laboratory with a deep understanding of today's challenges and complexities. We're passionate about translating science in partnership with our customers, and our customizable, accessible and sustainable solutions empower them with intuitive workflow efficiencies.About HSE•AGAt HSE•AG, we empower breakthrough discoveries in life science and diagnostics by delivering tailored, high-performance engineering solutions. From concept to market, we partner with leading companies to transform complex biological workflows into scalable, automated systems.Stay connected with SLAS:www.slas.org | Facebook | X | LinkedIn | Instagram | YouTubeAbout SLASSLAS (Society for Laboratory Automation and Screening) is an international professional society of academic, industry and government life sciences researchers and the developers and providers of laboratory automation technology. The SLAS mission is to bring together researchers in academia, industry and government to advance life sciences discovery and technology via education, knowledge exchange and global community building.Upcoming Events:SLAS Europe 2026 Conference and Exhibition (19-21 May 2026 | Vienna, Austria)SLAS Meet-UpsChicago, Illinois (June 18, 2026)Leiden, Netherlands (10 September 2026)Tübingen, Germany (20 October 2026)SLAS 2026 Sample Management Symposium (October 21-22, 2026 | South San Francisco, California)SLAS2027 International Conference & Exhibition (January 30 - February 3, 2027 | San Diego, California)View the full events calendar

Have an idea for an episode? Contact us!XDemics is the 2026 SLAS Ignite Award winner, and we're joined by members of the team: Colin Cook, PhD (CTO & Co-Founder), Daniel Downie (Manager, Sales and Commercial Development), and Nicholas Scianmarello, PhD (VP Manufacturing), to discuss their respiring membrane technology.They discuss applications in viral vector manufacturing, cell banking, T-cell and stem cell culture, and exosome production, emphasizing compatibility with automation and the ability to scale from 96-well plates to GMP bioreactors.Key Learning Points:XDemics' respiring membrane technologyApplications in viral vector manufacturing and exosome productionImpact on cell culture efficiency and automationRecognition and future plans after winning the SLAS Ignite AwardAbout XDemicsXDemics, a Caltech spinout, is fundamentally improving the way cells are grown. We've addressed a primary bottleneck—the basic inability to efficiently transfer oxygen in media during cell growth.Stay connected with SLAS:www.slas.org | Facebook | X | LinkedIn | Instagram | YouTubeAbout SLASSLAS (Society for Laboratory Automation and Screening) is an international professional society of academic, industry and government life sciences researchers and the developers and providers of laboratory automation technology. The SLAS mission is to bring together researchers in academia, industry and government to advance life sciences discovery and technology via education, knowledge exchange and global community building. Upcoming Events:SLAS Europe 2026 Conference and Exhibition (19-21 May 2026 | Vienna, Austria)SLAS Meet-UpsChicago, Illinois (June 18, 2026)Leiden, Netherlands (10 September 2026)Tübingen, Germany (20 October 2026)SLAS 2026 Sample Management Symposium (October 21-22, 2026 | South San Francisco, California)SLAS2027 International Conference & Exhibition (January 30 - February 3, 2027 | San Diego, California)View the full events calendar

The episode identifies a structural shift in the integration of generative AI within organizational workflows: variable cost models, unpredictable output quality, and heightened accountability requirements are converging to reshape managed services operations. This shift is exemplified by Anthropic's move toward usage-based pricing for Claude Enterprise, combining compute consumption with per-user fees, and by reports of major enterprises and intelligence agencies piloting dedicated cybersecurity-focused generative AI models. These trends expose IT service providers, especially MSPs, to cost volatility, operational risk, and new governance challenges as generative AI transitions from experimental implementation to core workflow tooling. Primary evidence includes Anthropic's revised pricing strategy, which replaces predictable licensing with usage-based billing, introducing financial unpredictability for heavy users. The episode cites reporting from The Verge and The Guardian, noting that AI-generated outputs can create hidden labor through the need for manual review and corrections, while undetected errors escalate into operational disputes and rework. The implementation of generative AI in security-sensitive environments underscores the need to scrutinize how AI-driven processes are metered and governed. Supporting developments reinforce this shift: MSP platform providers such as Enable are embedding generative AI directly into operational workflows, connecting third-party tools to live data. This creates the need for controls over what AI systems can access, approve, and log, particularly in multi-tenant environments. Meanwhile, outcome-based service agreements—such as fixed response-time SLAs—set new client expectations for measurable performance and accountability in AI operations. The market is also rewarding those who wrap unmanaged technology surfaces, like BYOD or AI tooling, with enforceable policies and auditable evidence trails. Operational implications for MSPs include increased pressure on margins due to AI's variable usage costs colliding with fixed-fee contracts, the challenge of capturing and reporting hidden labor from AI output review, and the necessity for evidence-based governance. Service providers unable to implement and sell AI operations management (“AIOps”) as a billable, controlled service risk becoming de facto shock absorbers for unpriced spend, rework, and disputes. Those who standardize on enforceable budgets, approval gates, audit trails, and compliance-ready reporting stand to protect service margins and reduce liability exposure. 00:00 AI Cost Reckoning 02:39 AI Governance Gap 04:44 Govern or Lose 07:12 Why Do We Care?  Supported by:  TimeZest Zero Networks 

In this episode we welcome Naveen Neelakantam, Chief Architect of Everpure's Digital Experience Business Unit. Naveen dives into the origin and evolution of Everpure's Digital Experience (DX), detailing how DX revolutionized storage management by moving beyond reactive support. The foundation of this lies in the phone home telemetry data collected from storage arrays, which first enabled the Cloud Assist capability. This data powers the ability to proactively identify and prevent issues, non-disruptively upgrade systems, and ensure a first-class support experience for every customer. Naveen explains how the intelligence gathered through telemetry propelled innovations like Pure1 and Evergreen//One. Pure1, the cloud-based platform, uses machine learning to offer predictive recommendations—such as projecting capacity needs to avoid unexpected overages. This predictive power is central to Evergreen//One, the consumption-based storage-as-a-service offering. By managing the physical appliance using telemetry, Everpure allows customers to consume logical storage connected to SLAs, simplifying the procurement process and eliminating the complexity of managing hardware specifics. This subscription model provides predictability and isolates customers from pricing pressures on components. Our discussion shifts to the future of storage and the transformative power of Artificial Intelligence. Naveen details AI Co-pilot, an agentic AI interface that helps users triangulate performance issues and orchestrate complex operations, such as migrating VMs, through conversational language using the Model Context Protocol (MCP). This move to active management is further realized through Pure1 Edge, allowing fleet-level data management and cloud-based upgrades. We then touche on Everpure Protect, a crucial cloud-based Disaster Recovery as a Service (DRaaS) solution. Ultimately, Naveen advises IT leaders to embrace AI as a powerful tool—like the domestication of the horse—that will make people more effective and accelerate innovation. To learn more, visit: https://www.purestorage.com/products/monitoring-fleet-management.html Check out the new Everpure digital customer community to join the conversation with peers and Pure experts: https://purecommunity.purestorage.com/ 00:00 Intro and Welcome 01:45 Naveen's Career Journey 09:29 Origin of Digital Experience 12:45 Proactive Recommendations 16:05 Cloud Management and Subscriptions 18:12 Stat of the Episode on Storage Capacity Growth 21:30 AI Co-Pilot and Automation 32:14 Telemetry 37:01 Pure1 and Subscription Management 39:51 Everpure Protect DRaaS 45:44 Hot Takes Segment

In Episode 177 of the Cyber Threat Perspective podcast, host Brad Causey and virtual CISO Daniel Perkins take a clear-eyed look at Claude Mythos — Anthropic's AI model that's generating serious buzz in the cybersecurity world for its ability to analyze source code, identify vulnerabilities at scale, build working exploits, and surface flaws that have sat undetected for decades.The cybersecurity community is reacting. Brad and Daniel think a more measured response is warranted.This episode breaks down what Mythos actually is, what it actually did, and what it actually means for your security program — without the hype or the hand-waving.Topics covered include:What Mythos really is — a purpose-built code analysis model, not a hacker-in-a-box or AI overlord, and why that distinction mattersThe BSD vulnerability reality check — it cost $20,000 to find a 20-year-old DOS flaw in software almost nobody uses, and what that tells us about the real-world economics of AI-driven vulnerability discoverySpeed, not net-new — why Mythos hasn't introduced anything fundamentally new to the threat landscape, just compressed the timeline dramaticallyVulnerability chaining — how Mythos could change triage by identifying how low and medium severity CVEs combine into critical attack pathsThe vibe coding problem — why organizations that have never written code before are now writing a lot of it, and why that's where Mythos becomes genuinely importantWhat this means for pen testing — why AI finding code flaws doesn't replace the human-driven validation of security programs, business logic testing, and misconfiguration discoveryThe shift to continuous vulnerability management — why monthly or quarterly scanning cycles won't be sufficient once Mythos capabilities proliferate, and how to make the move to continuous without going big bangThe Mythos-Ready framework — a look at the CSA guidance document, what's useful, what needs to be scaled to your organization, and why inventory and attack surface should come before governance for most teamsSupply chain and third-party risk — how Mythos changes the questions you should be asking your software vendorsThe bottom line from Brad and Daniel: be responsive, not reactive. Tighten your patching SLAs, understand your attack surface, document your decisions, and execute the fundamentals well. The organizations that do that won't be caught flat-footed when this becomes mainstream.Blog: https://offsec.blog/Youtube: https://www.youtube.com/@cyberthreatpovTwitter: https://x.com/cyberthreatpovFollow Spencer on social ⬇Spencer's Links: https://spenceralessi.comWork with Us: https://securit360.com | Find vulnerabilities that matter, learn about how we do internal pentesting here.

In this episode of The Fleet Success Show, RTA VP of Product, Marc Canton. sits down with Jake Johnson, former fleet maintenance supervisor and current RTA Fleet Success Manager, to break down one of the most critical and misunderstood topics in fleet: outsourcing. Whether you're a government fleet manager with limited resources, a trucking fleet with scale, or just trying to figure out how to do more with fewer techs, you're probably outsourcing more than you think—and leaving data and dollars on the table if you're not managing it properly. Jake brings his 20+ years of hands-on and leadership experience in trucking fleets to share how to decide what to send out, how to build strong vendor relationships, and how to track outsourced work like you would your own shop.   Key Takeaways Don't outsource blindly: Use VMRS codes to evaluate where you're spending the most time and money to decide what to outsource... and what to train for instead. Tooling and training determine viability: If your team lacks the tools or training, and it's not cost-effective to invest—send it out. Vendor performance must be tracked: Track vendor jobs like in-house work, with proper work orders, status updates, and SLAs for turnaround and comeback rates. Use outsourcing to protect your tech bandwidth: Don't send out the big, expensive job if small ones can be sublet faster and cheaper, freeing your shop for higher-value work. Relationships matter: Vendor partnerships should be built on honesty, clarity, and expectations. Think long-term and treat vendors like part of your team. Speaker Bios Jake Johnson Fleet Success Manager at RTA, Jake spent two decades working his way up from diesel tech to service manager to fleet leader in trucking operations. He now helps fleets across the country optimize everything from shop staffing to outsourced vendor networks. Marc Canton VP of Product & Consulting at RTA, Marc is a fleet operations veteran and co-host of The Fleet Success Show. He blends hands-on consulting experience with strategic leadership across public and private sector fleets.   Looking to take the next step to fleet success? Start by requesting your free copy of The Fleet Success Playbook. Written by fleet professionals for fleet professionals, the Playbook breaks down the four key pillars of fleet success, and gives you the tools you need to build a truly great fleet. Request your free (yes, really, free!) copy here: https://rtafleet.com/resources/fleet-success-playbook?utm_source=simplecast&utm_medium=footer_notes&utm_campaign=episode_213 Control fleet chaos with RTA Fleet360, proven software designed by fleet managers for fleet managers: https://rtafleet.com/book-a-demo?utm_source=simplecast&utm_medium=footer_notes&utm_campaign=episode_213

Automation and AI are shifting the pricing and accountability models for managed service providers, with risk increasingly centered on governance, workflow coherence, and outcome measurement rather than tool deployment. Evidence from studies like Fixify, reports from ChannelLive, and real-world cases such as the City of Seattle's pause on Microsoft Copilot rollout highlight that technology adoption is now gated less by access to solutions and more by readiness to govern, coordinate, and prove outcomes across fragmented processes. Automation exposes underlying coordination debt, moving the client focus from paying for labor time to demanding measurable outcomes and managed exceptions. Fixify's analysis of more than 50,000 support tickets from 30+ organizations showed tickets with at least 75% automation saw average resolution in 4.4 hours versus roughly three days for non-automated tickets. Data cited from OpenAI found that 93% of London SMBs use AI tools, but readiness and uptake are highly uneven within the UK. In Seattle, more than 450 labor hours per week were reported saved during the Copilot pilot, yet adoption was paused due to concerns over data governance and accountability for errors, not tool capability. According to coverage in GeekWire and IT Pro, these dynamics are shifting buyer expectations and vendor liabilities. Supporting developments include security concerns outlined by Kaseya's INKY report, which highlights the normalization of AI-generated phishing and changes in attack formats, forcing defenders to rethink detection and response. The operational surface of automation—where AI reshapes data, not just moves it—means standard controls and classic alerts are increasingly bypassed. Reports from Information Week and experts such as Dan Lorman emphasize that accountability for exceptions, shadow AI usage, and data exposure is shifting by default onto providers, whether or not contracts address these risks. These trends mean MSPs face direct operational and contract exposure: clients and auditors are demanding proof of how AI touches data, how exceptions are handled, and where logs and controls exist. Pricing based on seats or tickets is becoming harder to defend as automation compresses labor and raises expectations for accountability. Providers must reconsider SLAs, explicitly define automation boundaries, charge for governance activities, and move toward outcome-based pricing models if they want to avoid absorbing unpriced liability and operational complexity. 00:00 Automation Divide 04:27 Coordination Debt 06:01 Automation Liability 09:18 Why Do We Care?  Supported by:  JumpCloud HaloPSA   

Send us Fan MailThank you to SLAS2026 Sustainability Sponsor, My Green Lab, for sponsoring this episode!In this episode, host Emily Yamasaki, PhD, is joined by James Connelly, CEO of My Green Lab, for a conversation about sustainability trends in life science research. Connelly provides insight into the growing adoption of third-party certifications, such as the ACT® Ecolabel and My Green Lab Certification, driven by both voluntary commitments from major pharmaceutical and biotech companies. He also highlights innovations in lab automation and waste management, and how regulations are shaping industry practices. Key Learning Points:The benefits of sustainable certifications like ACT® Ecolabel.The Impact of regulations on industry standards that labs should be mindful of. Waste auditing is a practical first step for any lab looking to understand and reduce its environmental footprint.About My Green Lab:My Green Lab is a non-profit organization with a mission to build a global culture of sustainability in science. We are dedicated to promoting safe, sustainable practices in research laboratories, while still preserving the integrity of the science.Stay connected with SLAS:www.slas.org | Facebook | X | LinkedIn | Instagram | YouTubeAbout SLASSLAS (Society for Laboratory Automation and Screening) is an international professional society of academic, industry and government life sciences researchers and the developers and providers of laboratory automation technology. The SLAS mission is to bring together researchers in academia, industry and government to advance life sciences discovery and technology via education, knowledge exchange and global community building. Upcoming Events:SLAS Europe 2026 Conference and Exhibition (19-21 May 2026 | Vienna, Austria)SLAS Meet-UpsBasel, Switzerland (30 April 2026)Chicago, Illinois (June 18, 2026)Leiden, Netherlands (10 September 2026)Tübingen, Germany (20 October 2026)SLAS 2026 Sample Management Symposium (October 21-22, 2026 | South San Francisco, California)SLAS2027 International Conference & Exhibition (January 30 - February 3, 2027 | San Diego, California)View the full events calendar

Everyone's saying AI will kill SaaS — but is the SaaSpocalypse actually real, or just the latest wave of disruption that enterprise software has survived before? If you're a SaaS founder or operator watching vibe-coded apps spin up overnight, the fear is real. But the narrative is missing something critical: enterprise software isn't just code, and the moats that protect your ARR aren't going away anytime soon. Understanding what actually protects your revenue — and what doesn't — is the difference between panic and a clear-headed strategy. Here's what will you'll learn in episode #361 with Ben Murray. Why enterprise software is far more than code — compliance infrastructure, security, governance, SLAs, and integrations take years to harden, and a weekend project won't replace that How your proprietary data moat is actually becoming more powerful in the AI era, not less — and why AI agents without that data context are starting from zero Why switching costs remain one of the strongest SaaS defensibility factors — and why even AI-native alternatives face massive operational barriers to displacement The real operational commitment behind SaaS that vibe-coded tools can't replicate: customer support, product development, distribution, and long-term value delivery Why internal vibe-coded tools face their own adoption ceiling — from data security concerns to IT compliance — so enterprise spend isn't fleeing as fast as the hype suggests Tune in for the full bull case on SaaS survival — and get the frameworks from Ben's SaaSpocalypse blog post linked in the show notes. Resources Mentioned Ben's SaaSpocalypse Blog Post + Defensibility Frameworks: https://www.thesaascfo.com/the-saaspocalypse-ai-agents-vibe-coding-and-the-changing-economics-of-saas/

The dominant structural mechanism highlighted is the industry-wide shift toward liability transfer and governance gaps in AI procurement, deployment, and incident response. According to Dave Sobel, both vendors and organizations are accelerating AI adoption without corresponding investments in oversight, training, or clear accountability structures. This is reflected across multiple sectors, from software vendors such as Grammarly, Eightfold.ai, Cohesity, and Rubrik, to business leaders and policymakers, where risk is systematically deferred downstream rather than managed at the point of adoption. The most consequential evidence is the quantitative disconnect between stated AI priorities and functional oversight. Research cited by Dave Sobel from Economist Impact and HR Dive found that while 38% of organizations budget for AI and 86% of executives rate AI as essential, only 16% offer internal training and over half of department-level AI initiatives lack formal oversight (Ernst & Young). Additionally, 88% of AI vendors limit their liability, and only 17% align with regulatory compliance, per cited surveys, leaving substantial legal and operational risk for end users and service providers. Supporting this trend, Dave Sobel points to Grammarly's opt-out identity usage in new features and a class action lawsuit against Eightfold.ai regarding AI-driven employment decisions. Vendors such as Cohesity, Rubrik, ServiceNow, and Datadog are responding by building tools focused on remediation and recovery from AI-driven incidents, underscoring a shift from preventive governance to reactive containment. Policy moves—such as expanded operational cyber roles for the private sector—further offload accountability without addressing contractual and insurance exposure. For MSPs and technology leaders, these developments create practical risks: unclear service scope around AI tool usage in contracts, increased exposure to billable incidents and legal action, and rising labor costs for incident recovery. Service providers must audit agreements for AI-specific language, distinguish AI-related incidents from standard SLAs, and treat AI governance as a managed risk service. The pressure will increasingly fall on MSPs to account for training gaps, audit trails, compliance attestations, and recovery procedures—not simply the technology itself. Three things to know today 00:00 ROI Reality Check 02:12 Governance Gap Widens 03:14 Cleanup Economy Rises 05:45 Why Do We Care?  Supported by:  CometBackup 

Send a textStop guessing which software to trust. We break down a clear, repeatable path to evaluate commercial off-the-shelf tools, open source projects, custom third‑party builds, and cloud services so you can pass CISSP Domain 8.4 with confidence and protect your environment in the real world. We start with exam-winning tactics—how to slow down, read for intent, and think like a manager—then move into concrete practices that tame software risk without stalling delivery.You'll hear how to interrogate vendor claims, separate real certifications from marketing fluff, and judge patch cadences and incident response maturity. We dig into open source realities: vetting contributors, scanning dependencies against the NVD, building and maintaining an SBOM, and avoiding abandoned projects that explode under pressure. For third-party development, we outline what strong contracts look like—SLAs with teeth, security clauses, indemnity—and the proof you should see: code audits, SAST/DAST, penetration tests, and meaningful logging around integrations.Cloud isn't a shortcut; it's a shift in responsibility. We map the questions that matter for SaaS, IaaS, and PaaS: data protection, tenant isolation, hypervisor hardening, API security, and event visibility into your SIEM. Then we stitch it all into an evaluation workflow you can run every time: functional fit, vendor validation, layered security assessment, compliance and licensing review, sandbox integration testing, and a deployment plan that defines fix‑forward and rollback before anything hits production. Wrap it with monitoring, periodic reassessment, and documentation that procurement, IT, and security can actually use, and you've built a trustworthy software supply chain.If this helped you think sharper about software risk and the CISSP exam, subscribe, share it with a teammate, and leave a quick review telling us your top vendor vetting question. Your feedback shapes future episodes.Gain exclusive access to 360 FREE CISSP Practice Questions at FreeCISSPQuestions.com and have them delivered directly to your inbox! Don't miss this valuable opportunity to strengthen your CISSP exam preparation and boost your chances of certification success. Join now and start your journey toward CISSP mastery today!

In this episode of Meet the Practitioner, Mark Bewick engages with Donna Xanthidis and Sharon Aggarwal from Invesco to discuss the evolution and practical applications of IT Experience Management (ITXM). They explore the limitations of traditional metrics like CSAT, KPIs, and SLAs, emphasizing the need for a more human-centered approach to feedback and communication. The conversation highlights the importance of actionable insights derived from customer experiences and the positive impact of effective communication on service delivery. The episode concludes with practical advice for organizations looking to implement ITXM, encouraging a culture of continuous improvement and adaptability.TakeawaysCSAT metrics are often incomplete and don't provide full insights.Effective communication enhances the user experience significantly.ITXM allows for a more human-centered approach to IT services.Feedback should be actionable and lead to real improvements.Prioritization should be based on user experience, not just internal assumptions.Positive feedback can motivate teams and improve service delivery.Implementing ITXM can lead to a culture of continuous improvement.Don't be afraid to start the process of gathering feedback.Data from ITXM can reveal unexpected insights about user preferences.Flexibility in approach allows for quick adjustments in strategy.Donna XanthidisAssociate Director, Technology Customer Experience at Invesco Ltd.https://www.linkedin.com/in/donna-xanthidis-b06945103/Sharon AggarwalService Delivery Manager, Manager Global Server Operations at Invesco Ltd.https://www.linkedin.com/in/sharon-aggarwal-89a888/--Subscribe to our newsletter:LinkedIn: ⁠⁠⁠⁠https://www.linkedin.com/newsletters/it-experience-insights-6996053129205026816/⁠⁠⁠⁠Email: ⁠⁠⁠⁠https://happysignals.com/itxm-insights

This episode is brought to you by B2B Better. Ross helps businesses prove that their marketing is driving revenue — and that's exactly the problem we help B2B service businesses solve with video-first podcasts. We build content systems that don't just generate attention, they generate pipeline your sales team can actually point to. Visit b2bbetter.com to see how we do it differently. Your thought leadership campaign is running. People are watching, listening, and engaging — but when your CFO asks if it's actually driving revenue, you've got nothing to say. In this episode of Pipe Dream, host Jason Bradwell sits down with Ross Breckenridge, Managing Director of Breckenridge and HubSpot Platinum Partner, to tackle the attribution problem that almost every B2B marketing team has but nobody wants to admit. Ross's core point is clear: this isn't a marketing problem. It's a business problem. Until your marketing, sales, and customer success teams are operating from a single unified strategy and a single tech stack, you'll never get the visibility you need. The conversation starts where Ross always starts with clients: customer journey mapping. Before you touch an attribution model, you need to understand where each content asset sits in the buying process — lead gen, nurture, sales enablement, or renewals. Most companies skip this step and end up measuring the wrong things entirely. From there, Ross unpacks the dark funnel and explains why the HubSpot Campaigns tool is the home of the marketer's attribution reporting. Bundle your content assets into one campaign, track who was created as a new contact and who was simply influenced along the way, and map that all the way through to closed-won revenue — including renewals that happen two years after someone first engaged. But none of it works if sales is living in a different system. The connection between content and revenue only becomes visible when marketing, sales, and customer success are using the same tools and held to the same SLAs. One client found that leaving a lead for more than 48 hours dropped their conversation rate from 70% to 20%. That kind of clarity only exists when everyone is looking at the same data. If you're tired of defending your content budget with correlation and vibes, this episode gives you the framework to fix it for good. Chapter Markers 00:00 - Introduction: Ross Breckenridge and Breckenridge Agency 02:00 - HubSpot onboarding, integrations, and the RevOps focus 04:00 - Is attribution a tools problem, a strategy problem, or the wrong metrics? 05:00 - Customer journey mapping as the foundation of all attribution 06:00 - Picking one attribution model and staying consistent 08:00 - The dark funnel: what it is and how HubSpot brings it to light 10:00 - Content-sourced vs content-influenced pipeline: the key difference 11:00 - The HubSpot Campaigns tool as the marketer's attribution home 13:00 - Connecting content consumption to leads, deals, and closed revenue 15:00 - Why attribution is a business problem, not a marketing problem 16:00 - Building the business case to get sales and CS on the same page 17:00 - SLAs, shared accountability, and the 48-hour lead follow-up rule 19:00 - Working in silos vs being more than the sum of your parts 21:00 - AI, buyer research, and why being genuinely helpful never changes 23:00 - Where to find Ross and learn more about Breckenridge Useful Links Connect with Jason Bradwell on LinkedIn Connect with Ross Breckenridge on LinkedIn Visit Breckenridge — HubSpot Platinum Partner and RevOps specialists Email Ross directly at ross@breckenridgeagency.com Explore the HubSpot Campaigns tool for attribution reporting Explore B2B Better website and the Pipe Dream podcast

Send a textWhen evaluating WMS systems for 2026, it is essential to recognize that this is a structurally best-of-breed category rather than an extension of ERP or eCommerce platforms. This analysis deliberately excludes lightweight warehouse workflows embedded in broader systems, which are primarily designed to pass transactions downstream into a true WMS and lack the functional depth, orchestration complexity, and automation readiness required by serious distribution operations. True WMS platforms represent a category in their own right, with broader suites, richer integration patterns, and materially different architectural demands. Compounding this complexity is the diversity of operational models the category must support, from 3PL-centric environments focused on billing logic, client segregation, SLAs, and rapid customer onboarding, to manufacturing- and retail-centric value chains that prioritize production staging, kitting, reverse logistics, store replenishment, and omnichannel fulfillment. These differences are further reinforced by the technical segmentation of the category into WMS, WCS, and WES layers, with some vendors offering unified suites and others remaining purely transactional without deep integration into ASRS, robotics, conveyors, or advanced warehouse technologies—distinctions that materially affect long-term system fit and scalability.In this episode, our host Sam Gupta discusses the top WMS systems in 2026. He also discusses several variables that influence the rankings of these WMS systems. Finally, he shares the pros and cons of each WMS system.Video: https://www.youtube.com/watch?v=78YHLvbCbuARead: https://www.elevatiq.com/post/top-wms-systems/Questions for Panelists?

WHAT YOU'LL LEARN Why balancing cost, speed, and quality is now table stakes in logistics strategy How to design a flexible 3PL platform without hardcoding yourself into rigidity The operational difference between supporting enterprise brands vs. high-growth brands Why scenario planning still matters in an era of tariffs, snowstorms, and volatility How to avoid over-engineering automation that limits long-term flexibility What defines a true strategic partnership beyond SLAs and QBRs Why solving problems together—not alone—is the real measure of partnership maturity TIMESTAMPED SEGMENTS 00:00 – 01:00 | Balancing Cost, Speed & Quality Post-Pandemic 01:00 – 02:30 | Becoming the Customer: Operational Audits & CX Insight 02:30 – 04:00 | Agility, Uncertainty & Platform-First Thinking 04:00 – 05:30 | Defining High-Growth vs. Enterprise Brands 05:30 – 07:00 | Capability-Based Support Models vs. Split Teams 07:00 – 09:00 | What Real Strategic Partnerships Actually Look Like TOP QUOTES  [00:01:00] “We know the cost of customer acquisition has increased exponentially. So the customer you have is the customer that you wanna keep.” - Laura Ritchey [00:03:00] “I think obviously the overused word of agility these days… how quickly can you divert to warehouses that aren't closed or to transportation options that are still running?” - Laura Ritchey [00:05:00] “We were doing 10,000 orders a day. All of a sudden we have to do 100,000, and that's really different.” - Laura Ritchey [00:08:15] “Are we solving them together, or are we solving them alone?” - Laura Ritchey [00:18:00] “The team is looking to us to be the calm in the storm.” - Laura Ritchey ABOUT THE GUEST Laura Ritchey is President & CEO of the Americas region at GEODIS and a member of the Group's Executive Board. She leads nearly 20,000 teammates across eight countries, overseeing contract logistics, freight forwarding, and transportation operations throughout North and South America. With more than 30 years of experience—including 15 years in supply chain leadership across retail and third-party logistics—Laura previously served as CEO of Radial, Inc., driving growth through operational excellence. Her background spans finance, sourcing, distribution, and strategic transformation. She holds a J.D., MBA, and bachelor's degree from The Ohio State University. LINKS MENTIONED Laura's LinkedIn: https://www.linkedin.com/in/laura-ritchey-55836a8/ GEODIS website: https://geodis.com/   Subscribe and Keep Learning!If you're a logistics leader looking to scale sustainably, don't miss out! Subscribe for more expert strategies on tackling modern supply chain challenges.Be sure to follow and tag the eCom Logistics Podcast on LinkedIn and YouTube

A 10‑day wait for a refrigerator became the spark for a smarter last mile. We sit down with OneRail CEO Bill Catania to unpack how a racing mindset—frugality, failure tolerance, and relentless iteration—translated into a platform that helps retailers move from static delivery workflows to real‑time orchestration at scale. Bill shares the throughline across three startups: aggregate fragmented supply, connect it cleanly to demand, and let data science make the hard choices in milliseconds.You'll hear how RaceFan aggregated 650 local tracks to unlock national sponsorships, why MDOT's 200‑millisecond cloud coupon switch won over skeptical retailers (and how Bill timed the sale), and the moment OneRail shifted from gig moving to an enterprise platform. We break down OneRail's three‑layer model—software first, an aggregated carrier network across sedans to flatbeds, and a human exception team—and how the company takes on risk under its authority to deliver accountability most intermediaries avoid.AI is not a bolt‑on here. Bill explains how courier “credit scores,” market‑level performance, and dynamic assignment replaced manual dispatch, enabling one person to triage roughly 4,000 orders instead of 80. We explore exceptions in furniture and cold chain, SKU‑level loss analysis, and how pushing intelligence upstream into order management can reshape cost to serve before a truck even moves. Along the way, Bill shares the “yes if” leadership mantra that keeps doors open while aligning risk and reward—fuel for winning enterprise trust and recognition like Lowe's Innovation Partner of the Year.If you care about last mile logistics, enterprise retail, or building resilient platforms, this conversation is a blueprint: aggregate wisely, decide precisely, own outcomes, and scale through partnerships. Subscribe, share with a teammate who obsesses over SLAs, and leave a review with your biggest “yes if” moment—we'll feature the best on a future show.Follow The Freight Pod and host Andrew Silver on LinkedIn.Thanks to our sponsors:Stuut Technologies: Your AI coworker that collects your cash automatically.https://www.stuut.ai/Cloneops.ai: Not just AI. Industry-born AI.https://www.cloneops.ai/Rapido Solutions Group: Nearshore solutions for logistics companies.https://www.gorapido.com/GenLogs: Freight Intelligence on every carrier, shipper, and asset via a nationwide sensor networkhttps://www.genlogs.io/

Ivan Cossu is Co-Founder and CEO of deskbird, a flexible workplace management platform that's scaled past $10 million ARR. Founded in April 2020 during COVID's most uncertain period, deskbird survived a near-death pivot just months in and scaled across 10 international markets within six months—an unconventional path that challenged conventional wisdom about market domination strategies. Ivan shares the tactical decisions behind their international expansion, the shift from founder-led to scalable sales, and why they're deliberately targeting an underfunded VC category. Topics Discussed: The critical pivot from an Airbnb for co-working spaces to workplace management software in July 2020, months before running out of capital The counterintuitive decision to scale internationally within six months rather than dominating a single market first Balancing consumer-grade UX with enterprise-level customization in a category where competitors felt like "database queries" The mechanics of transitioning from pure inbound to incorporating outbound without breaking what's working US market expansion from Europe with higher close rates than home markets—and what that signaled about timing Why traditional email outbound is dead in the AI era and what actually works for breaking through GTM Lessons For B2B Founders: Scale your proven funnel globally before you perfect it locally: When deskbird saw strong early traction, they launched landing pages across UK and US markets within months to test demand signals. Ivan's contrarian take: "If you have a good funnel that's working, be bold enough to scale it globally" rather than spending years dominating Germany first. The key qualifier—you need solid core product and conversion metrics, not just initial traction. They were "way too scared of going international because it always worked out way better than we thought," often seeing better metrics in new markets than home markets. Most founders over-index on local penetration when they should be testing international demand. Choose validation channels by cycle time, not potential scale: In the first 6-12 months, avoid any channel with an 18-month feedback loop, even if it's your eventual ICP. Ivan targeted paid search and lower mid-market specifically because "you get a good sample size quite fast." Fast feedback loops let you iterate positioning, messaging, and ICP assumptions weekly rather than annually. Once you have conviction from high-velocity channels, then layer in longer-cycle enterprise motions. This sequencing prevents burning 12+ months on the wrong strategy. Founder-led sales is a permanent muscle, not a phase to exit: At $10M+ ARR, Ivan still joins sales calls regularly, citing a top entrepreneur-investor's rule: "Sales always needs to remain a final topic." The evolution isn't binary—it's additive. First hires (around 9 months post-MVP) were generalist "hard workers" who could sell vision over process. Today's hires are more disciplined as repeatable plays emerged. But the founder never exits—they shift from doing all deals to strategic deals, competitive situations, and maintaining direct customer insight. Even Benioff at Salesforce's scale still jumps into deals. Outbound in the AI era requires anti-scale tactics: Ivan's blunt assessment: "I don't believe in emails and any kind of written communication, especially not in the age of AI—it's just inflated." What works: (1) Targeted account selection—not 1:1 but not 1:1000 either, find the sweet spot of focused ABM, (2) Physical mail and offline media, (3) Cold calling with proper infrastructure. The challenge isn't the tactic—it's "having all the BDRs and AEs knowing which accounts they have to call, seamlessly calling account after account." Most companies can't operationalize the calling machine. Best results come when marketing warms leads with intent data, then hands them to outbound teams—not pure cold outreach. Underfunded categories force better unit economics: Deskbird's space isn't flooded with VC dollars—Ivan mapped 50-60 European competitors but limited mega-rounds. His take: "There's a downside, it's harder to get VC money, but once you get it you don't have the problem that some spaces are overfunded and it's crazily driving up customer acquisition cost." Markets with excessive capital often have one winner and "very sad consolidation" for positions 2-4. Constrained capital forced deskbird to build profitably and focus on product differentiation (Airbnb-like UX meets enterprise customization) rather than outspending competitors. Close rates in new markets signal expansion timing better than absolute numbers: Deskbird closed US deals from Europe with European AEs in mismatched time zones—and saw the highest close rates of any market. Ivan's logic: "If we can close them from Europe with our European AEs working in different time zones who cannot deliver the same SLAs, and we then go to the US, it should get even better." Don't wait for perfect execution—if you're winning despite structural disadvantages, that's your signal to invest. They hired their first US-based team only after proving they could win remotely. // Sponsors: Front Lines — We help B2B tech companies launch, manage, and grow podcasts that drive demand, awareness, and thought leadership. www.FrontLines.io The Global Talent Co. — We help tech startups find, vet, hire, pay, and retain amazing marketing talent that costs 50-70% less than the US & Europe. www.GlobalTalent.co // Don't Miss: New Podcast Series — How I Hire Senior GTM leaders share the tactical hiring frameworks they use to build winning revenue teams. Hosted by Andy Mowat, who scaled 4 unicorns from $10M to $100M+ ARR and launched Whispered to help executives find their next role. Subscribe here: https://open.spotify.com/show/53yCHlPfLSMFimtv0riPyM

In this episode of Security Squawk, Bryan Hornung, Reginald Ande, & Randy Bryan break down three stories that should change how executives think about cyber risk. This is not about tools, alerts, or vendor promises. It is about operational dependency, leadership accountability, and financial exposure when systems fail. Story one focuses on active exploitation of SolarWinds Web Help Desk vulnerabilities being used as an entry point for ransomware staging. Researchers are seeing attackers move fast after initial access, blending in by using legitimate remote management and incident response tools. That is the point. When attackers use normal looking admin utilities, many organizations do not detect the intrusion until the business impact is already locked in. If you run Web Help Desk or you have not verified your patch posture, this is a governance issue, not an IT debate. Patch timelines and exposure management are leadership decisions because they directly affect business interruption risk. Story two is a warning about the ransomware market adapting. As more organizations refuse to pay for data theft only extortion, threat actors are expected to pivot back toward encryption. Encryption creates urgency because it disrupts operations. The financial exposure shifts toward downtime, recovery labor, lost revenue, and customer churn. Executives should treat restore capability like a business continuity requirement. If your recovery plan has not been tested under pressure, it is not a plan. Story three covers the BridgePay ransomware incident and the downstream impact on merchants and local government services. Even when payment card data is not confirmed compromised, availability failures still create real harm. Customers do not care which vendor was hit. They only see that your business cannot process transactions. This is a clear reminder to revisit vendor criticality, SLAs, outage communications, and contingency processing options. Security Squawk is built for business owners, executives, board members, and IT leaders who want the real world impact without the fear marketing. Subscribe, share, and support the show at https://buymeacoffee.com/securitysquawk

Send us a textThe weakest link is often sitting on the edge, blinking away with expired firmware and no vendor support. We kick off with a blunt reality check on outdated firewalls, load balancers, and IoT gateways, and why waiting two years to retire them is a gift to attackers. From there, we guide you through Domain 7.7 with a practical blueprint for operating and maintaining detective and preventive measures that actually hold up under pressure.We unpack firewall fundamentals with clear, real‑world tradeoffs: when a simple packet filter is enough, when stateful inspection and deep packet inspection earn their keep, and how a WAF stops the web attacks your L3/L4 controls will miss. You'll hear how RTBH can deflect denial‑of‑service floods upstream, and why segmentation is your best friend for reducing blast radius—whether you use internal segmentation firewalls for R&D, Purdue‑style tiers for industrial networks, or controlled air gaps for the most sensitive systems. In the cloud, we separate security groups from true firewalls and show how to stitch policies across hybrid environments without creating blind spots.Detection makes prevention smarter, so we break down IDS versus IPS in plain language. Baseline first, then block with intent to avoid outages. We compare host‑based and network‑based sensors, explain where to place them, and share tactics for cutting alert noise. You'll also get straight talk on allowlists and blacklists, the right way to maintain them, and why stale entries cause the ugliest outages. We explore sandboxing for safe detonation and learning, and give an unvarnished take on honeypots and honeynets—where they help, where they waste time, and what legal lines to respect.Not every team can build a 24x7 SOC, so we outline how MSSPs can extend your coverage with clear SLAs and ownership. Endpoint anti‑malware remains non‑negotiable, but tool sprawl is a trap—choose a strong EDR and manage it well. Finally, we dive into AI and machine learning: how they supercharge detection, triage, and response—and how adversaries use them too. The throughline is simple: shrink attack surface, raise signal quality, and respond faster than threats can pivot. If this helps you secure one more edge box or tune one more control, share it with a teammate, subscribe for more practical walkthroughs, and drop a review so we can keep raising the bar together.Gain exclusive access to 360 FREE CISSP Practice Questions at FreeCISSPQuestions.com and have them delivered directly to your inbox! Don't miss this valuable opportunity to strengthen your CISSP exam preparation and boost your chances of certification success. Join now and start your journey toward CISSP mastery today!

We welcome back Andrew Sillifant, Solution Director at Pure Storage, for a deep dive into the concept of data gravity. We start with the traditional 2010 definition coined by Dave McCrory—that data accumulates, making it harder to move, and forcing dependent systems to cluster nearby. However, Andrew presents his core thesis, arguing that this foundational principle is no longer sufficient in a world of exploding complexity. Our conversation emphasizes the need to re-examine data gravity through a modern lens, acknowledging the massive shift to cloud computing and the proliferation of interconnected systems over the last decade. Andrew introduces five crucial dimensions that now describe data's impact: Volume, redefined by context and classification; Dependency, now accelerated by API calls, integration points, and AI agents; Criticality, which includes regulations, security, and implicit SLAs; Velocity, measured by how many functions data is used for; and Latency, complicated by geographic requirements that skew response times. These dimensions highlight how non-physical constraints, like egress fees and data sovereignty laws, create artificial friction that compounds the problem beyond sheer data size. Our discussion concludes with a new framework of five sources of data gravity that IT leaders must address: Technical Gravity (the physical component and mobility), Economic Gravity (the costs of hosting and moving data, like egress fees), Regulatory Gravity (compliance and legal restrictions), Institutional Gravity (the dependency on a small number of people who know how to manage old systems), and Measurement Gravity (budgeting and decision-making risks). Finally, Andrew connects these challenges to Pure Storage, noting how platform features like deduplication and continuous innovation are actively working to lessen the effects of data gravity for customers. To learn more, visit https://blog.purestorage.com/purely-technical/the-economics-of-data-gravity/ Check out the new Pure Storage digital customer community to join the conversation with peers and Pure experts: https://purecommunity.purestorage.com/ 00:00 Intro and Welcome 01:05 Andrew Observations About the USA 04:19 Defining Data Gravity 07:30 Challenges Caused By Data Gravity 09:01 Real World Data Gravity Examples 17:15 Data Gravity Impact Vectors 33:02 New Dimensions of Data Gravity 40:30 Where Pure Helps with Data Gravity

Richard McGirr breaks down a detailed case study of a sponsored Best Ever webinar and how paid media can be used to responsibly scale capital raising. He explains why cold traffic struggles in high-trust investments, how sponsored webinars function as “rented” warm audiences, and why education-first positioning is critical when asking for six-figure commitments. Richard walks through the structure of the webinar, why capital protection and income resonated with investors, and how private real estate credit compares to equity in volatile markets. He also outlines his post-webinar follow-up systems, including rapid sales SLAs, email drips, and how long-tail conversions ultimately drive ROI from paid placements. Visit ⁠www.tribevestisc.com⁠ for more info. Try QUO for free PLUS get 20% off your first 6 months when you go to quo.com/BESTEVER  Join us at Best Ever Conference 2026! Find more info at: https://www.besteverconference.com/  Join the Best Ever Community  The Best Ever Community is live and growing - and we want serious commercial real estate investors like you inside. It's free to join, but you must apply and meet the criteria.  Connect with top operators, LPs, GPs, and more, get real insights, and be part of a curated network built to help you grow. Apply now at⁠ ⁠⁠⁠www.bestevercommunity.com⁠⁠ Podcast production done by⁠ ⁠Outlier Audio⁠ Learn more about your ad choices. Visit megaphone.fm/adchoices

professorjrod@gmail.comIn this episode of Technology Tap: CompTIA Study Guide, we dive deep into the concept of cybersecurity risk and why it's a critical factor in your IT skills development. Forget common myths and technical jargon — this episode breaks down risk into understandable elements: threat, vulnerability, likelihood, and impact. Perfect for CompTIA exam candidates, we provide practical IT certification tips that turn abstract fears into concrete strategies to protect your digital assets. Whether you're prepping for your CompTIA exam or interested in technology education, this discussion equips you with essential knowledge for effective tech exam prep.We walk through inherited risk (your baseline exposure) and residual risk (what remains after controls), and explain why zero risk is a dangerous fantasy. From there, we unpack the four response strategies—avoidance, mitigation, transfer, and acceptance—using clear examples you can bring to your Sec+, Net+, or A+ studies and your day job. You'll learn when quantitative numbers help, when qualitative scales are more honest, and how heat maps can mislead when assumptions go unchallenged.Because modern exposure doesn't end at your perimeter, we dive into vendor risk management: evaluating partners before you sign, setting expectations with NDAs, MSAs, SLAs, SOWs, and rules of engagement, and keeping continuous oversight to match changing realities. We also connect the dots to business impact analysis, translating risk into recovery targets with MTD, RTO, RPO, and WRT so you prioritize mission essential functions instead of treating every system the same. Finally, we clarify the role of internal and external assessments and demystify penetration testing as a snapshot that challenges assumptions rather than a guarantee of safety.If you want security that aligns with real-world priorities, this conversation gives you the mental model and vocabulary to make better decisions under uncertainty. Subscribe, share with a teammate, and leave a review with one insight you're taking back to your org. What risk will you accept—and why?Support the showArt By Sarah/DesmondMusic by Joakim KarudLittle chacha ProductionsJuan Rodriguez can be reached atTikTok @ProfessorJrodProfessorJRod@gmail.com@Prof_JRodInstagram ProfessorJRod

This episode examines why growing concern over AI-driven skills obsolescence is less about workforce displacement and more about authority, accountability, and liability for MSPs. As AI systems increasingly triage tickets, remediate issues, and shape outcomes, MSPs are absorbing responsibility for decisions made by tools they did not design and cannot fully audit. The mismatch between AI-driven operations and pre-AI contracts, SLAs, and pricing models creates a widening risk gap that directly threatens margins and client trust. The show then turns to AI infrastructure, focusing on Microsoft's response to rising power and water costs tied to data center expansion. While public commitments emphasize cost control and community investment, the underlying reality for IT service providers is continued volatility. AI workloads remain energy-intensive and politically sensitive, and those costs are likely to be passed downstream. MSPs that price AI-dependent services on today's assumptions risk margin erosion when infrastructure costs shift faster than contracts can be updated.Next, the episode explores how workplace AI tools from Anthropic and Slack are moving beyond assistance into shaping finished work. By summarizing conversations, organizing files, and producing artifacts that become the default record, these tools quietly define “what happened.” For MSPs, this pulls them deeper into advisory territory, as AI-generated outputs influence decisions, accountability, and client understanding—often without clear acknowledgment of what context or nuance was lost. Finally, the episode connects a wave of AI-driven acquisitions to a single strategic thread: vendors racing to own not just insight, but action. As platforms consolidate signals across usage, identity, cost, and observability, the pause between insight and execution disappears. For MSPs, the risk is not being replaced outright, but being sidelined as platforms decide faster than humans can intervene. The path forward is not resisting consolidation, but asserting value where judgment, context, and governance still matter.Four things to know today00:00 Report Warns 40 Percent of IT Skills May Become Obsolete as AI Reshapes Work04:42 Microsoft's AI Data Center Commitments Highlight the Growing Cost and Governance Risks of AI Infrastructure07:16 Anthropic and Slack Expand AI From Assistance to Shaping Finished Work11:00 AI-Driven Acquisitions Show Vendors Consolidating Signals to Move Faster From Insight to Action Supported by: https://cometbackup.com/

Matthew Gill joins The PowerShell Podcast to talk about what it means to be a Site Reliability Engineer (SRE) and how SRE thinking changes the way you approach automation, reliability, and problem solving. Matthew and host Andrew Pla break down core concepts like SLAs, SLOs, and SLIs, and why reliability through planning matters more than rushing straight to the keyboard.   They also dig into why PSFramework is worth the dependency for enterprise-grade logging and configuration, how community mentorship (including Fred Weinmann's impact) can fast-track growth, and why books like The Phoenix Project are game-changing for understanding DevOps culture and constraints.   Key Takeaways: • SRE is software engineering applied to operations — focus on measurable reliability, proper planning, and balancing change with stability using concepts like SLAs, SLOs, and SLIs. • PSFramework can eliminate “reinventing the wheel” — especially for logging and configuration handling, giving enterprises proven patterns and integrations without custom-built fragility. • Community is a career multiplier — mentorship, learning in public, and teaching others are some of the fastest ways to build confidence and advance your PowerShell journey.   Guest Bio: Matthew Gill is a Site Reliability Engineer and is the Co-Director of Content for the PowerShell + DevOps Global Summit. He has been a problem solver, systems administrator, and scripter for nearly 20 years. From working in the United States Marine Corps, education, radio, and currently the private sector, the majority of Matt's experience has been focused on solving problems in a variety of interesting and creative ways.Resource Links PowerShell + DevOps Global Summit – https://powershellsummit.org The Phoenix Project (Book) – https://itrevolution.com/product/the-phoenix-project/ The Unicorn Project (Book) – https://itrevolution.com/product/the-unicorn-project/ PSFramework – https://github.com/PowershellFrameworkCollective/psframework Matthew Gill's Blog – https://therealgill.com Andrew's Links - https://andrewpla.tech/links PDQ Discord – https://discord.gg/PDQ PowerShell Wednesdays – https://www.youtube.com/results?search_query=PowerShell+Wednesdays The PowerShell Podcast on YouTube: https://youtu.be/vkOLsjsPvYo

Send us a textA bus-powered hackathon, a $100K prize for a gloriously “useless” app, and keynotes that said AI so many times you could turn it into a supercut—re:Invent 2025 brought energy, irony, and real signals hiding in the noise. We're joined by AWS Hero Chris Williams to unpack what actually matters: where AI is genuinely useful, where it's lipstick on a feature, and how builders should adapt without losing the plot.We dig into the Road to re:Invent hackathon and why the winning project—turning a tiny script into a sprawling multi-repo monster—was the sharpest commentary on over-engineering all week. From there, we break down the AI-first keynotes, new Graviton efficiency gains that could tame power budgets, and the push to own the entire stack from silicon to agents. Kiro's spec-driven development gets real talk too: amazing for scaffolding, documentation, and repo exploration; risky when you ask a confident hallucination to write production without tests, reviews, or security controls.The conversation shifts to careers and craft with Werner Vogels' parting challenge: become a “Renaissance developer.” Learn systems, networking, security, and economics, then layer AI to explore design space faster. If you're just starting out, don't begin with prompts—build fundamentals and use AI to shape your learning plan. We wrap with the sleeper headline: first-party multi-cloud connectivity. It's overdue, it's serious, and it could reshape how enterprises stitch providers together while raising new questions about SLAs, accountability, and incident response between hyperscalers.Hit play for a clear-eyed debrief that filters the hype, celebrates real progress, and offers practical guidance for teams shipping in 2025. If this helped you make sense of re:Invent, follow the show, share it with a teammate, and drop your bold prediction for the year ahead.Where to find Chris:https://x.com/mistwirehttps://www.linkedin.com/in/chrisfwilliams/https://vbrownbag.com/Purchase Chris and Tim's book on AWS Cloud Networking: https://www.amazon.com/Certified-Advanced-Networking-Certification-certification/dp/1835080839/ Check out the Monthly Cloud Networking Newshttps://docs.google.com/document/d/1fkBWCGwXDUX9OfZ9_MvSVup8tJJzJeqrauaE6VPT2b0/Visit our website and subscribe: https://www.cables2clouds.com/Follow us on BlueSky: https://bsky.app/profile/cables2clouds.comFollow us on YouTube: https://www.youtube.com/@cables2clouds/Follow us on TikTok: https://www.tiktok.com/@cables2cloudsMerch Store: https://store.cables2clouds.com/Join the Discord Study group: https://artofneteng.com/iaatj

It's all about Data Pipelines. Join Pure Storage Field Solution Architect Chad Hendron and Solutions Director Andrew Silifant for a deep dive into the evolution of data management, focusing on the Data Lakehouse architecture and its role in the age of AI and ML. Our discussion looks at the Data Lakehouse as a powerful combination of a data lake and a data warehouse, solving problems like "data swamps” and proprietary formats of older systems. Viewers will learn about technological advancements, such as object storage and open table formats, that have made this new architecture possible, allowing for greater standardization and multiple tooling functions to access the same data. Our guests also explore current industry trends, including a look at Dremio's 2025 report showing the rapid adoption of Data Lakehouses, particularly as a replacement for older, inefficient systems like cloud data warehouses and traditional data lakes. Gain insight into the drivers behind this migration, including the exponential growth of unstructured data and the need to control cloud expenditure by being more prescriptive about what data is stored in the cloud versus on-premises. Andrew provides a detailed breakdown of processing architectures and the critical importance of meeting SLAs to avoid costly and frustrating pipeline breaks in regulated industries like banking. Finally, we provide practical takeaways and a real-world case study. Chad shares a customer success story about replacing a large, complex Hadoop cluster with a streamlined Dremio and Pure Storage solution, highlighting the massive reduction in physical space, power consumption, and management complexity. Both guests emphasize the need for better governance practices to manage cloud spend and risk. Andrew underscores the essential, full-circle role of databases—from the "alpha" of data creation to the "omega" of feature stores and vector databases for modern AI use cases like Retrieval-Augmented Generation (RAG). Tune in to understand how a holistic data strategy, including Pure's Enterprise Data Cloud, can simplify infrastructure and future-proof your organization for the next wave of data-intensive workloads. To learn more, visit https://www.purestorage.com/solutions/ai/data-warehouse-streaming-analytics.html Check out the new Pure Storage digital customer community to join the conversation with peers and Pure experts: https://purecommunity.purestorage.com/ 00:00 Intro and Welcome 03:15 Data Lakehouse Primer 08:31 Stat of the Episode on Lakehouse Usage 10:50 Challenges with Data Pipeline access 13:58 Assessing Organization Success with Data Cleaning 16:07 Use Cases for the Data Lakehouse 20:41 Case Study on Data Lakehouse Use Case 24:11 Hot Takes Segment

professorjrod@gmail.comWhat if your help desk could solve recurring IT problems in minutes, not hours? In this episode, we explore the backbone of reliable IT support, focusing on clear SOPs that remove guesswork, SLAs that align technical work with business risk, and an effective ticketing flow that transforms scattered fixes into measurable outcomes. Whether you're preparing for a CompTIA exam or seeking practical IT skills development, you'll find valuable insights here. We share real-world examples—from login failures to VPN drops—that demonstrate how documentation, escalation tiers, and knowledge bases reduce time-to-resolution and prevent repeat incidents, making technology education and effective IT support attainable goals.We also get candid about the human side of support. Professionalism is not a soft skill; it is operational. We talk punctuality, clean language, and the kind of active listening that clarifies issues without talking down to users. De-escalation matters, but so do boundaries; you can stay calm without tolerating abuse. And yes, social media can cost you your job—one vague post is all it takes. These habits shape trust with customers and credibility inside the org.To round it out, we map the OS landscape you actually support: Windows, macOS, Linux, and ChromeOS on the desktop, plus iOS and Android in the field. We cover MDM realities with JAMF and Google Workspace, why file systems like NTFS and ReFS or APFS and ext4 affect security and performance, and how hardware requirements such as TPM 2.0 should drive upgrade planning. You will leave with a sharper playbook and four cert-style practice questions to test your knowledge.If you found this useful, follow the show, share it with a teammate, and leave a quick review to help others find it. Got a help desk win or a hard lesson learned? Send it our way and join the conversation.Support the showArt By Sarah/DesmondMusic by Joakim KarudLittle chacha ProductionsJuan Rodriguez can be reached atTikTok @ProfessorJrodProfessorJRod@gmail.com@Prof_JRodInstagram ProfessorJRod

What does it really take to build an AI-ready network in 2025? In this episode of Tech Talks Daily, I speak with Vikas Butaney from Cisco and Ali Tehrani from Presidio to unpack the biggest announcements from Cisco's Partner Summit and discuss how their collaboration is helping enterprises modernise networks for the AI era. Together, we explore how businesses can move faster, strengthen security, and simplify operations while adapting to a world of continuous data flow and intelligent automation. Vikas shares how Cisco's strategy is built around three customer imperatives: AI ready data centers, future proof workplaces, and digital resilience. He talks about how Cisco is weaving these priorities into new innovations such as secure routers with five times the throughput, Wi Fi 7 access points, and unified dashboards that bring Catalyst Center and Meraki together for a single view of the network. He also introduces AI Canvas, a multiplayer workspace that allows NetOps and SecOps teams to collaborate in real time, showing what it looks like when AI becomes part of the operational fabric rather than an add on. Ali joins the conversation with the partner's perspective, explaining how Presidio brings Cisco's architecture to life through the last mile of execution. He describes how the Cisco Unified Branch initiative uses AI workflows and branches as code to deliver zero touch rollout across thousands of sites. By combining automation, golden configuration templates, and telemetry driven SLAs, Presidio helps customers reduce deployment times from weeks to minutes while maintaining consistent performance and security. Throughout our discussion, we compare AI for networking, where AI helps to run and optimise the network, with networking for AI, which provides the infrastructure to power high volume AI workloads. We talk about how Cisco is building security directly into the network with Access Manager, simplifying IoT segmentation, and preparing for a post quantum world. This episode offers a clear, inside look at how Cisco and Presidio are shaping the next generation of secure, intelligent networks. So, how ready is your organisation for this new era of AI driven connectivity?   You said: Please also insert these links Press Release: Cisco Supercharges its Secure Enterprise Network Architecture for the AI Era Blog: Unlocking the AI Era: How Cisco is Delivering on its Vision for a Secure, Simplified, and Scalable Network Blog: From Fragmented to Future-ready with Unified Branch: Powering IT in the AI Era   ChatGPT said: What does it really take to build an AI ready network in 2025? In this episode of Tech Talks Daily, I speak with Vikas Butaney from Cisco and Ali Tehrani from Presidio to unpack the biggest announcements from Cisco's Partner Summit and discuss how their collaboration is helping enterprises modernise networks for the AI era. Together, we explore how businesses can move faster, strengthen security, and simplify operations while adapting to a world of continuous data flow and intelligent automation. Vikas shares how Cisco's strategy is built around three customer imperatives: AI ready data centers, future proof workplaces, and digital resilience. He talks about how Cisco is weaving these priorities into new innovations such as secure routers with five times the throughput, Wi Fi 7 access points, and unified dashboards that bring Catalyst Center and Meraki together for a single view of the network. He also introduces AI Canvas, a multiplayer workspace that allows NetOps and SecOps teams to collaborate in real time, showing what it looks like when AI becomes part of the operational fabric rather than an add on. Ali joins the conversation with the partner's perspective, explaining how Presidio brings Cisco's architecture to life through the last mile of execution. He describes how the Cisco Unified Branch initiative uses AI workflows and branches as code to deliver zero touch rollout across thousands of sites. By combining automation, golden configuration templates, and telemetry driven SLAs, Presidio helps customers reduce deployment times from weeks to minutes while maintaining consistent performance and security. Throughout our discussion, we compare AI for networking, where AI helps to run and optimise the network, with networking for AI, which provides the infrastructure to power high volume AI workloads. We talk about how Cisco is building security directly into the network with Access Manager, simplifying IoT segmentation, and preparing for a post quantum world. If you want to learn more about Cisco's announcements and vision for the AI era, check out these resources: Cisco Supercharges its Secure Enterprise Network Architecture for the AI Era Unlocking the AI Era: How Cisco is Delivering on its Vision for a Secure, Simplified, and Scalable Network From Fragmented to Future Ready with Unified Branch: Powering IT in the AI Era This episode offers a clear, inside look at how Cisco and Presidio are shaping the next generation of secure, intelligent networks. So, how ready is your organisation for this new era of AI driven connectivity?   Tech Talks Daily is Sponsored by NordLayer: Get the exclusive Black Friday offer: 28% off NordLayer yearly plans with the coupon code: techdaily-28. Valid until December 10th, 2025. Try it risk-free with a 14-day money-back guarantee.