Podcasts about cloud services

Welcome to episode 308 of The Cloud Pod – where the forecast is always cloudy! Justin and Matt are on hand and ready to bring you an action packed episode. Unfortunately, this one is also lullaby free. Apologies. This week we're talking about Databricks and Lakebridge, Cedar Analysis, Amazon Q, Google's little hiccup, and updates to SQL – plus so much more! Thanks for joining us.  Titles we almost went with this week: KV Phone Home: When Your Key-Value Store Goes AWOL When Your Coreless Service Finds Its Core Problem Oracle’s Vanity Fair: Pretty URLs for Pretty Penny From Warehouse to Lakehouse: Your Free Ticket to Cloud Town 1⃣Databricks Uno: Because One is the Loneliest Number Free as in Beer, Smart as in Data Science Cedar Analysis: Because Your Authorization Policies Wood Never Lie Cedar Analysis: Teaching Old Policies New Proofs Amazon Q Finally Learns to Talk to Other Apps Tomorrow: Visual Studio’s Predictive Edit Revolution The Ghost of Edits Future: AI Haunts Your Code Before You Write It IAM What IAM: Google’s Identity Crisis Breaks the Internet Permission Denied: The Day Google Forgot Who Everyone Was 403 Forbidden: When Google’s Bouncer Called in Sick AWS Brings the Heat to Fusion Research Larry’s Cloud Nine: Oracle Stock Soars on Forecast Raise OCI You Later: Oracle Bets Big on Cloud Growth Oracle’s Crystal Ball Shows 40% Cloud Growth Ahead Meta Scales Up Its AI Ambitions with $14 Billion Investment From FAIR to Scale: Meta’s $14 Billion AI Makeover Congratulations Databricks one, you are now the new low code solution.  AWS burns power to figure out how power works AI Is Going Great – Or How ML Makes Money  02:12 Zuckerberg makes Meta’s biggest bet on AI, $14 billion Scale AI deal Meta is finalizing a $14 billion investment for a 49% stake in Scale AI, with CEO Alexandr Wang joining to lead a new AI research lab at Meta.  This follows similar moves by Google and Microsoft acquiring AI talent through investments rather than direct acquisitions to avoid regulatory scrutiny. Scale AI specializes in data labeling and annotation services critical for training AI models, serving major clients including OpenAI, Google, Microsoft, and Meta.  The company’s expertise covers approximately 70% of all AI models being built, providing Meta with valuable intelligence on competitor approaches to model development. The deal reflects Meta’s struggles with its Llama AI models, particularly the underwhelming reception of Llama 4 and delays in releasing the more powerful “Behemoth” model due to concerns about competitiveness with OpenAI and

Andrea Malagodi, CTO of Sonar, discusses how the company successfully transitioned from on-premise to SaaS, leveraging AWS partnership and maintaining focus on developer-centric code quality and security solutions.Topics Include:Andrea Malagodi is CTO of Sonar, guest on podcastSonar founded 16+ years ago by three software engineersFounders wanted to help developers understand code quality issuesFocus on giving developers precise, actionable insights for improvementProducts include SonarQube Server, Cloud, and IDE versionsRecent acquisitions: ACR, Tidelift, and Structure 101 companiesSaaS journey began seven years ago with SonarQube CloudInitially targeted individual developers, then expanded to enterprisesNow multi-region with comprehensive enterprise features availableSeven million developers rely on Sonar's solutions globally400,000 organizations and 28,000 enterprise customers use SonarStarted SaaS to test market demand, not assumptionsEngaged customers early to understand migration requirements neededRecommends alpha versions with design customers for feedbackFree tier for open-source code enables quick trialEnterprise certifications (ISO 27001, SOC 2) build trustAWS partnership includes enterprise support and technical resourcesUsed CDK for infrastructure-as-code, experienced early adoption challengesMulti-region strategy should be considered from the beginningAWS Learning partnership certified all engineers in cloudCloud enables faster development cycles than traditional infrastructureRecommends avoiding architectural one-way doors during transitionConsider data residency requirements for global customer baseAI-generated code creates productivity gains but needs validationSonar provides deterministic rules for AI-generated code reviewWorking on MCP protocol and AI code quality solutionsSecurity approach is "start left" not "shift left"Advanced Security offering includes dependency scanning and vulnerabilitiesAvailable on sonarsource.com and AWS MarketplaceFree tier offers 50,000 lines of code analysisParticipants:Andrea Malagodi – Chief Technical Officer, SonarFurther Links:Website: www.sonarsource.comSonar in the AWS MarketplaceSee how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/

Kanaiya Vasani, Chief Product Officer, explains how ExtraHop leverages AWS services and generative AI to help enterprise customers address the growing security challenges of uncontrolled AI adoption.Topics Include:ExtraHop reinventing network detection and response categoryPlatform addresses security, performance, compliance, forensic use casesBehavioral analysis identifies potential security threats in infrastructureNetwork observability and attack surface discovery capabilities includedApplication and network performance assurance built-in featuresTraditional IDS capability with rules and IOCs detectionPacket forensics for investigating threats and wire evidenceCloud-native implementations and compromised credential investigation supportExtraHop partnership with AWS spans 35-40 different servicesAWS handles infrastructure while ExtraHop focuses core competenciesExtraHop early adopter of generative AI in NDRNatural language interface enables rapid data access queriesEnglish questions replace complex query languages for usersAgentic AI experiments focus on SOC automation workflowsL1 and L2 analyst workflow automation improves productivityShadow AI creates major risk concern for customersUncontrolled chatbot usage risks accidental data leakageGovernance structures needed around enterprise gen AI usageVisibility required into LLM usage across infrastructure endpointsAI innovation pace challenges security industry keeping upModels evolved from billion to trillion parameters rapidlyTraditional security tools focus policies, miss real-time activity"Wire doesn't lie" - network traffic reveals actual behaviorExtraHop maps baseline behavior patterns across infrastructure endpointsAnomalous behavioral patterns flagged through network traffic analysisMCP servers enable LLM access through standardized protocolsStolen tokens allow adversaries unauthorized MCP server accessMachine learning identifies anomalous traffic patterns L2-L7 protocolsGen AI automates incident triage, investigation, response workflowsBest practices include clear policies, governance, monitoring, educationParticipants:Kanaiya Vasani – Chief Product Officer, ExtraHop NetworksSee how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/Notes:

Cribl's Field CISO Ed Bailey discusses how customers can manage the quality and quantity of data by providing intelligent controls between data sources and destinations.Topics Include:Cribl company name originCompany helps organizations screen data to find valuable insightsEd Bailey was Cribl's first customer back in 2018Data growth of 25% yearly created seven-figure cost increasesCEOs and CIOs complained about explosive data storage costsUsers demanded more data while budgets remained constrainedBailey discovered Cribl through a random Facebook advertisementCribl Stream sits between data sources and destinationsNo new agents required, uses existing infrastructure connectionsReduced data growth from 28% to 8% within yearDevelopment cycles shortened from six weeks to two weeksBailey managed global security and telemetry data systemsOperated large Splunk instance across forty different countriesTeam spent time collecting data instead of extracting valueCribl provided consistent data control plane for operationsSmart engineers could focus on machine learning solutionsMigrated from terrible SIEM to better security platformData strategy should focus on business requirements firstNot all data has the same business valueTier one: Critical data goes to expensive platformsTier two: Important data stored in cheaper lakesTier three: Compliance data in low-cost object storageSIEM costs around one dollar per gigabyte storedData lakes cost twelve to eighteen cents per gigabyteObject storage costs fractions of pennies per gigabyteAWS partnership provides scalable infrastructure for rapid growthEC2, EKS, and S3 are heavily utilized servicesCribl Search finds data directly in object storageAvoids costly data movement for search and analysisParticipants:Edward Bailey – Field CISO, CriblSee how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/

NASA is teaming up with the commercial sector to bring discoveries home from space.

EigenLayer is back with a major announcement: EigenCloud. Sreeram Kannan and JT Rose unveil the first crypto-native cloud platform—a verifiable, programmable environment for building applications beyond the limits of traditional blockchains. We explore how EigenCloud packages modules like EigenDA, EigenVerify, and EigenCompute into a developer-friendly product that brings cloud-scale computation and crypto-grade trust guarantees together. From meme coins and AI agents to fully sovereign applications, we dig into what makes this launch a pivotal step for crypto infrastructure and why it might just reignite Ethereum's original ambitions. ------

Saviynt Co-Founder Amit Saha discusses how their AWS partnership has enabled the identity security company to deliver comprehensive identity protection while minimizing organizational friction.Topics Include:Saviynt is leading identity security provider in marketSecures human, non-human, workforce, and privileged access identitiesEliminates friction while automating organizational access management processesBiggest challenge: reducing friction in new access processesSecond challenge: visibility into accumulated technical debt problemsLost business context makes access permissions difficult to unwindSaviynt provides quick visibility to prioritize identity risksShadow IT creates ungoverned workloads and cloud applicationsNeed integration with asset management and cloud providersMust derive intelligence from multiple disconnected information sourcesAWS partnership provides access to prolific customer baseAWS security owners are same buyers for SaviyntEleven-year AWS relationship with early security competencyISV Accelerate program connects with sellers and architectsRising Star program helps stand out in crowded marketplaceFind mutual customers for successful AWS partnership storiesGenAI in bad actors' hands compromises customer securityProduct engineering uses GenAI tools for better qualityAgentic AI creates new paradigm between human/non-human identitiesAgentic AI requires dynamic, fluid access management approachesAI agents can generate their own bots needing accessZero trust principles needed at broader scale for AINext twelve months: getting ahead of GenAI curveNew AWS services launch daily in GenAI spaceContributing to new standards like MCP and A2A protocolsAWS Marketplace simplifies procurement and buyer discovery processesEDP program and migration incentives benefit ISV transactionsAWS developer-friendly startup programs accelerate time to marketCloud-native approach enables predictable scaling and AWS integrationAWS-Saviynt partnership aims for once-in-generation security impactParticipants:Amit Saha – Co-Founder and Chief Growth Officer, SaviyntSee how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/

Chief Architect Russell Leighton discusses how Panther's cloud platform revolutionizes security operations by treating detections as Python code and AI enabled alert vetting turning responses from hours into minutes. Topics Include:Panther is a cloud security monitoring tool (cloud SIEM)Works at massive scale, more cost-effective than legacy systemsKey differentiator: "detections as code" written in PythonBrings software engineering best practices to security operationsEnables unit testing and version control for security detectionsRecently adopted generative AI to improve security workflowsSOC burnout is renowned due to tedious ticket processingAI has intelligence of security engineer, works much fasterExample: Alert shows "Russ Leighton removed branch protection"Old way: Manual log analysis, checking user profiles manuallyTakes hours of squinting at detailed log dataNew AI way: Automatic vetting happens in minutesAI checks user profile in Okta or IDPDetermines engineer status, assesses typical behavior patternsProvides risk assessment based on historical alert dataLow risk for engineers, high risk for unusual usersExample: HR person accessing production code is escalatedCustomer quote: Takes vetting "from hours to seconds"Panther customers get dedicated AWS accounts for securityCompany can't see customer data, only self-reported metricsAI provides summaries, risk assessments, timelines, visualizationsAlso suggests remediations like human security engineer wouldInitial concerns about putting AI in production environmentCustomer feedback exceeded expectations with feature requestsAWS Bedrock integration addresses customer security concernsUses Anthropic Claude as base LLM through BedrockCustomers can enable additional Bedrock guardrails independentlyAI transparency prevents hallucination concerns through explanationsClaude's extended thinking mode shows reasoning processAI visualizes thinking with flowcharts explaining decision processParticipants:Russell Leighton – Chief Architect, PantherFurther Links:Website: Panther.comAWS MarketplaceSee how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/

Security leaders from Anthropic and AWS discuss how agentic AI is transforming cybersecurity functions to autonomously handle everything from code reviews to SOC operations.Topics Include:Agentic AI differs from traditional AI through autonomy and agencyTraditional AI handles single workflow nodes, agents collapse multiple stepsHigher model intelligence enables understanding of broader business contextsAgents make intelligent decisions across complex multi-step workflows processesEnterprise security operations are seeing workflow consolidation through GenAIOrganizations embedding GenAI directly into customer-facing production applicationsSoftware-as-a-service transitioning to service-as-software through AI agentsSecuring AI requires guardrails to prevent hallucinations in applicationsNew vulnerabilities appear at interaction points between system componentsAttackers target RAG systems and identity/authorization layers insteadLLMs hallucinate non-existent packages, attackers create malicious honeypotsGovernance frameworks must be machine-readable for autonomous agent reasoningAmazon investing in automated reasoning to prove software correctnessAnthropic uses Claude to write over 50% of codeAutomated code review systems integrated into CI/CD pipelinesSecurity design reviews use MITRE ATT&CK framework automationLow-risk assessments enable developers to self-approve security reviews40% reduction in application security team review workloadAnthropic eliminated SOC, replaced entirely with Claude-based automationIT support roles transitioning to engineering as automation replaces frontlineCompliance questionnaires fully automated using agentic AI workflowsISO 42001 framework manages AI deployment risks alongside securityExecutive risk councils evaluate AI risks using traditional enterprise processesAWS embeds GenAI into testing, detection, and user experienceFinding summarization helps L1 analysts understand complex AWS environmentsAmazon encourages teams to "live in the future" with AIInterview candidates expected to demonstrate Claude usage during interviewsSecurity remains biggest barrier to enterprise AI adoption beyond POCsVirtual employees predicted to arrive within next 12 monthsModel Context Protocol (MCP) creates new supply chain security risksParticipants:Jason Clinton – Chief Information Security Officer, AnthropicGee Rittenhouse – Vice President, Security Services, AWSHart Rossman – Vice President, Global Services Security, AWSBrian Shadpour – GM of Security and B2B Software Sales, AWSSee how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/

Shereen, an Infrastructure Team Leader in Cloud Services at NEXT, shares her inspiring career journey from an IT apprentice at 16 to a team leader.She discusses the critical role of cybersecurity in today's world, emphasising how her team remediates vulnerabilities and defends against constant hacking attempts to ensure business continuity. Shereen also highlights the rewarding aspect of nurturing her team's growth and potential, fostering a supportive and fun work environment. Finally, she offers valuable insights on being a woman in tech, noting the positive shift towards greater female representation in the industry.Don't forget to subscribe to our channel and hit the notification bell to receive updates on everything Life at NEXT!Pursue your ambition and join the NEXT team → https://tinyurl.com/3esp3ux8Follow us!Instagram: www.instagram.com/lifeatnextTikTok: www.tiktok.com/@lifeatnextFacebook: www.facebook.com/lifeatnextLinkedIn: www.linkedin.com/company/lifeatnext#LifeAtNEXT #LetsTakeItOn

Spryker's Chief Product Officer, Elena Leonova, discusses the Spryker Business Intelligence platform and how working with AWS as a strategic advisor unlocked deeper opportunities for transformative growth.Topics Include:Elena Leonova introduces Spryker as digital commerce platformSpryker focuses on sophisticated B2B commerce transactionsTraditional industries: manufacturing, industrial goods, med techCustomers sell complex equipment like MRI machines, tractorsProducts are custom-built to order through procurement processesExtensive negotiation and aftermarket servicing are requiredCompetitors focus on fashion, food - not complex equipmentSpryker exclusively hosted on AWS cloud infrastructureAWS partnership enables new capabilities and customer innovationBusiness intelligence tools and AI capabilities now availableRicoh example: global manufacturer of industrial-grade printersRicoh sells through dealers and distributors worldwideS-Diverse: new automotive software marketplace partnership platformConnects automotive manufacturers with embedded software producersSpryker Business Intelligence powered by Amazon QuickSight launchedCommerce becoming more intelligent than traditional repeat purchasesComplex equipment buyers don't purchase MRI machines weeklyPlatform provides insights into customer portal navigation patternsCombines commerce data with search, CRM, competitive intelligenceHelps merchants identify revenue optimization signals from noiseBusiness intelligence integrated directly within Spryker platformCustomers should evaluate platform's future scalability and flexibilityRevenue optimization requires understanding what metrics to improveEasy-to-use data analysis prevents information overload problemsQuickSight's GenAI capabilities enable faster executive decision-makingAWS partnership provided cost optimization and innovation confidenceElena initially viewed AWS as just hosting providerBuilding shared vision with AWS unlocked deeper collaborationAWS became trusted advisor for strategy and partnershipsGenerative AI enables multi-persona communication across customer typesParticipants:Elena Leonova – Chief Product Officer, SprykerSee how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/

ActiveFence CEO Noam Schwartz discusses how his company evolved from protecting platforms against user-generated harmful content to helping companies deploy public-facing AI safely at scale.Topics Include:Noam Schwartz introduces himself as ActiveFence CEOFormer intelligence officer specializing in open source intelligenceMission: protect online experiences for everyone everywhereOnline platforms constantly hammered by various attacksAttacks include cybersecurity, abuse, hate speech, spamCompanies playing endless whack-a-mole game with violationsNeed scalable solution that works across languages/formatsDeveloped enterprise-grade technology for sophisticated companiesAmazon became customer and great partner early onGenerative AI introduction changed the game completelyLLMs non-deterministic unlike traditional programmed chatbotsSame input produces different outputs each timeAI deployed in customer support, healthcare, airlinesNew risks when models speak on company's behalfOne bad output creates legal and reputational damageCompanies need to deploy public-facing AI safelyTransition affects healthcare, finance, gaming, government sectorsBuilding on years of user-generated content expertiseNo specific ChatGPT moment triggered their AI pivotActiveFence was AI company since day oneModel companies like Amazon, Nvidia asked for helpRealized their expertise perfectly suited for AI safetyStaying on top of AI developments is impossibleFocus on customer adoption, not every new releaseMain enterprise challenge is trusting AI technologyUnrealistic expectations for 100% accuracy from AIMost companies will license existing models, not buildSecurity solutions remain independent like traditional cybersecurityParticipants:Noam Schwartz – CEO and Co-Founder, ActiveFenceOfer Oringher – Software and Technology Account Manager, AWSSee how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/

Jeff Moncrief discusses Sonrai Security's Cloud Permissions Firewall, and the best practices for using AI-powered summaries and orchestration to ensure security at all points.Topics Include:Jeff Moncrief introduces Sonrai Security and Cloud Permissions FirewallFocus on achieving least privilege access in AWS quicklyLightweight orchestration layer secures IAM from inside outEliminates need to write hundreds of individual policiesCustomers struggle with identity risk in CNAP/CSPM toolsGenerative AI adoption driving top security use casesBedrock and AI agents mentioned daily by customersProduct managers should consider underlying platform security risksAI models have control over infrastructure they run onIdentity is fundamental infrastructure enabling AWS AI modelsSonrai uses Bedrock capability inside Cloud Permissions FirewallJust-in-time access provides temporary, time-boxed AWS accessBedrock generates session summaries from audit logs automaticallyPlain English insights show what happened during sessionsSession summaries improve audit compliance and incident responseCustomer with 1000 accounts manually deployed service controlsFriday afternoon deployment caused very bad weekend disasterPolicy inheritance issues broke child accounts and OUsPlanning and orchestration essential for scaling AI securitySonrai platform built 100% cloud-native on AWSCoordinates service control policies and resource control policiesJust-in-time access relies on IAM Identity CenterParticipates in ISV Accelerate and AWS MarketplaceSecurity best practices start with identity as foundation"Hackers don't hack, they just log in" philosophyEliminate standing privileges with just-in-time access patternsRestrict AI services by user, location, and accountReview over-permissioned or inactive third-party vendor accessActionable insights through useful logging and AI summarizationFuture focus on protecting new services and permissionsParticipants:Jeff Moncrief – Field CTO & Director of Sales Engineering, Sonrai SecurityLinks:Website – Sonraisecurity.comAWS Marketplace – Sonrai SecuritySee how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/

Are you overwhelmed by the thousands of photos on your phone? Whether you're a busy mom or an entrepreneur, having a photo organization system is crucial.   Angela Andrieux, a fine art photographer and photography coach, explains how Mylio Photos can save you time and stress when searching for the perfect picture for your next project.   In this episode, we discuss: The significance of having a photo organization system for both personal and business needs Tips on starting your photo organization journey without feeling overwhelmed The 3-2-1 backup strategy to ensure your photos are safe and secure Benefits of using facial recognition and metadata for easy photo retrieval   Whether you have 1,500 photos or thousands, Angela provides actionable steps to help you take control of your digital memories. Don't let the chaos of your camera roll keep you up at night—tune in and learn how to create a system that works for you!   Check out Mylio Photos for organizing your photos.   Connect with Angela: Website: https://angelaandrieux.com  Instagram: https://www.instagram.com/angandrieux    ✨ Join my Mompreneur Glow Up email list. It's your go-to source for all things life, leadHERship, and mindset.  

Akanksha Bilani of Intel shares how businesses can successfully adopt generative AI with significant performance gains while saving on costs.Topics Include:Akanksha runs go-to-market team for Amazon at IntelPersonal and business devices transformed how we communicateForrester predicts 500 billion connected devices by 20265,000 billion sensors will be smartly connected online40% of machines will communicate machine-to-machineWe're living in a world of data delugeAI and Gen AI help make data effectiveGoal is making businesses more profitable and effectiveVarious industries need Gen AI and data transformationIntel advises companies as partners with AWSThree factors determine which Gen AI use cases adoptFactor one: availability and ease of use casesHow unique and important are they for business?Does it have enough data for right analytics?Factor two: purchasing power for Gen AI adoption70% of companies target Gen AI but lack clarityLeaders must ensure capability and purchasing power existFactor three: necessary skill sets for implementationNeed access to right partnerships if lacking skillsIntel and AWS partnered for 18 years since inceptionIntel provides latest silicon customized for Amazon servicesEngineer-to-engineer collaboration on each processor generation92% of EC2 runs on Intel processorsIntel powers compute capability for EC2-based servicesIntel ensures access to skillsets making cloud aliveAWS services include Bedrock, SageMaker, DLAMIs, KinesisPerformance is the top three priorities for successNot every use case requires expensive GPU acceleratorsCPUs can power AI inference and training effectivelyEvery GPU has a CPU head node component Participants:Akanksha Bilani – Global Sales Director, IntelSee how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon/isv/

Victoria Chin of Asana and Michael Horn of AWS demonstrate how Amazon Q integrates with Asana to enable AI-powered workflows while dramatically reducing manual work and improving cross-functional collaboration.Topics Include:Victoria Chin introduces herself as Asana's CPO Chief of StaffMichael Horn from AWS discusses customer feedback on generative AIAI agents limited by quality of data pulled into themAmazon Q Business created to analyze information and take actionHundreds of customers using Q Business across various industries dailyAWS hosts most business applications, ideal for AI journeyAmazon Q has most built-in, managed, secure data connectors availableQ Index creates comprehensive, accessible index of all company dataSecurity permissions automatically pulled in, no manual configuration neededSupports both structured and unstructured data from multiple sourcesVictoria returns to discuss Asana's integration with Q IndexBillions invested in integrations, but usage still lags behindTeams switch between apps 1000 times daily, missing connectionsRoot problem: no reliable way to track who/what/when/whyContent platforms store work but don't manage or coordinateAsana bridges content and communication for effective teamwork scalingAI disrupting software, but questions remain about real valueSoftware must provide structured framework to guide LLMs effectivelyAI needs data AND structure to separate signal from noiseAsana Work Graph maps how work actually gets done organizationallyWork Graph visualized as interconnected data, not rows and columnsMost strategic work is cross-functional, requiring multiple teams collaboratingTraditional integrations require manual setup and knowing when to useQ Index gives Asana access to 40+ different data connectorsUsers can ask questions, get answers with cross-application contextAI Studio enables no-code building of workflows with AI agentsProduct launch example shows intake, planning, execution, and reporting stagesAI can surface relevant documents, research, and updates automaticallyChat is tip of iceberg; real power comes from embedded workflowsIntegration evolves from feature-level to AI-powered product-level connectionsParticipants:Victoria J. Chin – Chief of Staff / Product Strategy, AI, AsanaMichael Horn – Principal Head of Business Development – Artificial Intelligence & Machine Learning, AWSSee how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon/isv/

AWS leaders commemorate the podcast's 100th episode while looking ahead to expanded coverage of technology partners and continued focus on generative AI, modern data strategies, agentic AI solutions and more!Topics Include:Episode 100 celebrates milestone of AWS software companies podcastWeekly podcast shares ISV stories, best practices, guidanceToday features AWS leader thoughts on ISV communityArym Diamond heads North America data and AI salesSpecialist team helps win deals, create happy customersISV customers do cutting-edge work on AWS platformISVs create force multiplier effect for entire companyBuilding community through podcast video and audio contentKristen Backeberg leads global ISV partner marketing at AWSPodcast featured 157 ISV leaders from 121 companiesReached over 30,000 listeners across 90+ countries worldwideISV partners drive cloud innovation across all industriesAWS supports growth from startups to enterprise leadersAPN network designed to help partners succeed, scaleOlawale Oladehin directs ISV solutions architecture in North AmericaPodcast shares customer insights, journeys, and innovationsAWS technology continues evolving to meet customer needsCarol Potts leads North America ISV sales at AWSPodcast started less than two years agoFirst episode titled "Data the Engine for Growth"Customer obsession drives everything AWS does for ISVsDeep collaboration focused on joint ISV success partnershipsVishal Sanghvi heads ISV marketing for North AmericaISVs face pressure delivering products at generative AI paceModern data strategy foundational for ISV product successFavorite episodes include Snowflake, Wiz, Coupang discussionsAWS offers programs for every ISV persona typeFuture episodes focus on generative AI, cybersecurity, dataAgentic AI becoming important for production phase evolutionPodcast expanding scope to include technology partnersParticipants:Kristen Backeberg – Director, Global ISV, Solutions Enterprise and Alliance Partner Marketing, Amazon Web ServicesArym Diamond – Director, US ISV Specialists, Amazon Web ServicesOlawale Oladehin – Director, ISV, Solutions Architecture, North America, Amazon Web ServicesCarol Potts – GM, ISV Sales Segment, North America, Amazon Web ServicesVishal Sanghvi - Head of ISV Field Marketing, North America, Amazon Web ServicesSee how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/

Executive leaders from UneeQ and Zeta Global discuss the revolutionary impact of AI technologies that enable enhanced customer experiences and improved sales performances.Topics Include:Dave Cristini introduces panel on AI in advertising and marketing.Panel explores personalized experiences at scale with privacy focus.UneeQ creates AI-powered digital humans for brand interactions.Zeta Global uses AI to optimize customer messaging.LLMs combined with traditional ML empowers marketers to create models.Marketers can now build models without needing data scientists.AI agents integrated into systems can take action, not just respond.Agent chaining orchestrates sophisticated marketing actions automatically.AWS Bedrock provides tools to shape AI marketing future.Hyper-personalization becoming more achievable through AI automation.Ethics requires authenticity in brand AI representation.Transparency about data usage builds customer trust.Win-win approach: AI should augment teams, not just reduce costs.Integration difficulties remain a major challenge for AI implementation.AI agents have limited context windows and memory.Solution: Create specialized agents with persistent viewpoints.Companies need strong integration capabilities before implementing AI.Privacy regulations impact AI use in global marketing.Highly regulated industries require careful AI implementation strategies.Generative AI creates compliance challenges with unpredictable outputs.Digital humans eliminate judgment, revealing new customer insights.Banking clients discovered customers didn't understand financial terminology.Zeta improved onboarding with AI agents for data mapping.AI data mapping increased NPS scores and accelerated monetization.CMOs and CIOs increasingly collaborating on AI initiatives.Tension exists between marketing (quick wins) and IT (security).Strategic alignment with approved infrastructure enables scaling AI solutions.CEOs have critical role in aligning AI goals across departments.Internal AI use case: practicing sales with digital humans.Sales teams achieved 500% higher sales through AI role-playing.Participants:Danny Tomsett – Chief Executive Officer, UneeQRoman Gun – Vice President, Product, Zeta GlobalDavid Cristini – Director, ISV Sales, North America – Business Applications, AWSSee how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/

Join Kamyabi Network: https://kamyabinetwork.com/Guest Introduction: Joining us today is Zeeshan Sikander, the Founder & CEO of Zenkoders, a cutting-edge software company he's been passionately building since 2019. With over 10 years of experience in Software Development and Project Management, Zeeshan has grown Zenkoders from a solo venture into a team of 80+ talented individuals. His background also includes experience as a Product Development Engineer at Habib Bank Limited, where he focused on designing and developing HBL's mobile apps. At Zenkoders, they specialize in turning ideas into tangible success, offering services ranging from Mobile Apps and Web Development to Cloud Services and E-commerce. Zeeshan's vision is to lead Zenkoders to the forefront of the global software landscape, and he's always open to innovative collaborations.Do not forget to subscribe and press the bell icon to catch on to some amazing conversations coming your way!Socials:TBT's Official Instagram: https://www.instagram.com/thoughtbehindthings      Muzamil's Instagram: https://www.instagram.com/muzamilhasan  Muzamil's LinkedIn: https://www.linkedin.com/in/muzamilhasan    Zeeshan's LinkedIn: https://www.linkedin.com/in/mzeeshansikander/Podcast Links:Spotify: https://spoti.fi/3z1cE7F       Google Podcast: https://bit.ly/2S84VEd        Apple Podcast: https://apple.co/3cgIkf 

In this episode of Campus Technology Insider Podcast Shorts, host Rhea Kelly covers the key tech stories in higher education. Highlights include Fortinet's report on the critical role of identity in cloud security, Meta's launch of a standalone AI app featuring Llama 4, and a Cloudera survey revealing data privacy as a top concern for AI adoption. Tune in for more insights on these stories and their implications for the education sector. 00:00 Introduction and Host Welcome 00:17 Critical Security Perimeter in Cloud Services 00:48 Meta Platforms Launches Standalone AI App 01:21 Cloudera Survey on AI Agents and Data Privacy 01:57 Conclusion and Further Resources Source links: Report: Identity Has Become a Critical Security Perimeter for Cloud Services Meta Launches Stand-Alone AI App Study: Data Privacy a Top Concern as Orgs Scale Up AI Agents Campus Technology Insider Podcast Shorts are curated by humans and narrated by AI.

Ash Pembroke, Portfolio CTO of Caylent, discusses the critical balance of data accuracy in the era of Gen AI for the benefit of boosting innovation.Topics Include:Ash Pembroke, Portfolio CTO of Caylent, self-identifies as a "recovering data scientist."Caylent is an AWS native services company.Data quality remains an issue despite Gen AI.Contrasts legalism versus mysticism in data quality.Legalism: accurate data when applications need it.Mysticism: insights that help decision-making.Traditional data foundations approach is being challenged weekly.Gen AI developments force rethinking of solution architectures.Teams share solutions through giant Slack threads.Example: Vector databases questioned after model context protocol.Still do traditional data assessments, but stay flexible.Integration and data processing constantly get abstracted.Data strategy equals architecture strategy equals business strategy.Traditional approach: standardize data across engineering teams.New approach: allow business users to innovate.Bring valuable techniques back to the organization.Case study: North Sea wind turbine alerts.Initially seen as data quality issue, revealed new predictive failure signal.Gen AI enables local experimentation by business users.Blurring lines between enterprise enablement and software building.BrainBox AI case study: energy optimization across buildings.Architecture decisions impact ability to scale products.Work with business edges rather than looking for patterns.Gen AI can process information from these working groups.Think about data as a product, not asset.Redimensionalize dependencies across your organization.Now's a good time to attack data quality.New tools help visualize complexity across organizations.Participants:· Ash Pembroke – Portfolio CTO, CaylentSee how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/

In this episode of Market Bites, the team review earnings reports from Meta, Microsoft, Apple, and Amazon, focusing on AI investments, cloud services, and tariff impacts. They highlight strong performance across the board and discuss how these tech giants are strategically adapting to a changing economic and regulatory landscape. .

New Relic's Head of AI and ML Innovation, Camden Swita discusses their four-cornered AI strategy and envisions a future of "agentic orchestration" with specialized agents.Topics Include:Introduction of Camden Swita, Head of AI at New Relic.New Relic invented the observability space for monitoring applications.Started with Java workloads monitoring and APM.Evolved into full-stack observability with infrastructure and browser monitoring.Uses advanced query language (NRQL) with time series database.AI strategy focuses on AI ops for automation.First cornerstone: Intelligent detection capabilities with machine learning.Second cornerstone: Incident response with generative AI assistance.Third cornerstone: Problem management with root cause analysis.Fourth cornerstone: Knowledge management to improve future detection.Initially overwhelmed by "ocean of possibilities" with LLMs.Needed narrow scope and guardrails for measurable progress.Natural language to NRQL translation proved immensely complex.Selecting from thousands of possible events caused accuracy issues.Shifted from "one tool" approach to many specialized tools.Created routing layer to select right tool for each job.Evaluation of NRQL is challenging even when syntactically correct.Implemented multi-stage validation with user confirmation step.AWS partnership involves fine-tuning models for NRQL translation.Using Bedrock to select appropriate models for different tasks.Initially advised prototyping on biggest, best available models.Now recommends considering specialized, targeted models from start.Agent development platforms have improved significantly since beginning.Future focus: "Agentic orchestration" with specialized agents.Envisions agents communicating through APIs without human prompts.Integration with AWS tools like Amazon Q.Industry possibly plateauing in large language model improvements.Increasing focus on inference-time compute in newer models.Context and quality prompts remain crucial despite model advances.Potential pros and cons to inference-time compute approach.Participants:Camden Swita – Head of AI & ML Innovation, Product Management, New RelicSee how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon/isv/

Police have been warned that shifting information to the cloud could have "severe detrimental impacts" on people if they aren't careful. Phil Pennington spoke to Corin Dann.

Jon Yoo, CEO of Suger, shares how his company automates the complex & challenging workflows of selling software through cloud marketplaces like AWS.Topics Include:Jon Yoo is co-founder/CEO of Suger.Suger automates B2B marketplace workflows.Handles listing, contracts, offers, billing for marketplaces like AWS.Co-founder previously led Confluent's marketplace enablement product.Confluent had 40-50% revenue through cloud marketplaces.Required 10-20 engineers working solely on marketplace integration.Engineers prefer core product work over marketplace integration.Product/engineering leaders struggle with marketplace deployment requirements.Marketplace customers adopt without marketing, creating unexpected management needs.Version control is challenging for marketplace-deployed products.License management through marketplace creates engineering challenges.Suger helps sell, resell, co-sell through AWS Marketplace.Marketplace integration isn't one-time; requires ongoing maintenance.Business users constantly request marketplace automation features.Suger works with Snowflake, Intel, and AI startups.Data security concerns drive self-hosted AI deployments.AI products increasingly deploy via AMI/container solutions.AI products use usage-based pricing, not seat-based.Usage-based pricing creates complex billing challenges.AI products are tested at unprecedented rates.Two deployment options: vendor cloud or customer cloud.SaaS requires reporting usage to marketplace APIs.Customer-hosted deployment simplifies some billing aspects.Marketplaces need integration with ERP systems.Version control particularly challenging for AI products.Companies need automated updates for marketplace-deployed products.License management includes scaling up/down and expiration handling.Suger aims to integrate with GitHub for automatic updates.Participants:· Jon Yoo – CEO and Co-founder, SugerSee how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon/isv/

Show DescriptionWhat are the non-US cloud services options, falling off the blogging train and trying to get back on, working on vacation, Chris recaps the Alaskan Folk Festival experience, how often do you go back and clean out JavaScript, and the idea of gilding just one lily on a new project. Listen on Website →Links European Alternatives A lack of frequency increases the pressure to deliver quality Trap (2024) Reviews Polyfilling Concepts ex-Googler · April 10, 2025 Gild Just One Lily Blog Questions Challenge CodePen Development CSS clip-path maker Sponsors

SentinelOne's Ric Smith shares how Purple AI, built on Amazon Bedrock, helps security teams handle increasing threat volumes while facing budget constraints and talent shortages.Topics Include:Introduction of Ric Smith, President of Product Technology and OperationsSentinelOne overview: cybersecurity company focused on endpoint and data securityCustomer range: small businesses to Fortune 10 companiesProducts protect endpoints, cloud environments, and provide enterprise observabilityRic oversees 65% of company operationsPurple AI launched on AWS BedrockPurple AI helps security teams become more efficient and productiveSecurity teams face budget constraints and talent shortagesPurple AI helps teams manage increasing alert volumesTop security challenge: increased malware variants through AIAI enables more convincing spear-phishing attemptsIdentity breaches through social engineering are increasingVoice deepfakes used to bypass security protocolsFuture threats: autonomous AI agents conducting orchestrated attacksSentinelOne helps with productivity and advanced detection capabilitiesSentinelOne primarily deployed on AWS infrastructureUsing SageMaker and Bedrock for AI capabilitiesBest practice: find partners for AI training and deploymentCustomer insight: Purple AI made teams more confident and creativeAI frees security teams from constant anxietySentinelOne's hyper-automation handles cascading remediation tasksMultiple operational modes: fully automated or human-in-the-loopAgent-to-agent interactions expected within 24 monthsCommon misconception: generative AI is infallibleAI helps with "blank slate problem" providing starting frameworksAI content still requires human personalization and reviewAWS partnership provides cost efficiency and governance benefitsParticipants:· Ric Smith – President – Product, Technology and Operations, SentinelOneSee how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon/isv/

Sam Gantner, Chief Product Officer of Nexthink, reveals how DEX is moving IT from reactive firefighting to proactive problem prevention and transforming enterprise productivity.Topics Include:DEX stands for Digital Employee ExperienceDEX eliminates IT issues preventing employee productivityShifts IT from reactive to proactive problem-solvingEmployees often serve as IT problem alerting systemsBest IT is transparent to employeesDEX solves device sluggishness and slow application issuesNetwork problems consistently appear across organizationsIT teams often lack visibility into employee experiencesMany organizations waste money on unused software licensesDEX Score measures comprehensive employee IT experienceSurveys capture subjective aspects of technology experienceReduction of actual problems differs from ticket reductionNexthink uses lightweight agents on employee devicesBrowser monitoring essential as browsers become application platformsEmployee engagement metrics capture real-time feedbackNexthink rebuilt as cloud-native platform using AWS servicesCompany deploys across 10+ global AWS regions30% of engineering resources dedicated to AI developmentOne customer eliminated 50% of IT ticketsAnother recovered 37,000 productivity hours worth $3M annuallyA third saved $1.3M by identifying unused licensesAI implementation requires dedicated employee trainingGood AI now better than perfect AI neverTechnology adoption is the next DEX frontierDigital dexterity becoming critical for maximizing IT investmentsParticipants:Samuele Gantner – Chief Product Officer, NexthinkSee how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon/isv/

Linda Ivy-Rosser, Vice President for Forrester, outlines the evolution of business applications and forward thinking predictions of their future.Topics Include:Linda Ivy-Rosser has extensive business applications experience since the 1990s.Business applications historically seen as rigid and lethargic.1990s: On-premise software with limited scale and flexibility.2000s: SaaS emergence with Salesforce, AWS, and Azure.2010s: Mobile-first applications focused on accessibility.Present: AI-driven applications characterize the "AI economy."Purpose of applications evolved from basic to complex capabilities.User expectations grew from friendly interfaces to intelligent systems.Four agreements: AI-infused, composable, cloud-native, ecosystem-driven.AI-infused: 69% consider essential/important in vendor selection.Composability expected to grow in importance with API architectures.Cloud-native: 79% view as foundation for digital transformation.Ecosystem-driven: 68% recognize importance of strategic alliances.Challenges: integration, interoperability, data accessibility, user adoption.43% prioritizing cross-functional workflow and data accessibility capabilities.Tech convergence recycles as horizontal strategy for software companies.Data contextualization crucial for employee adoption of intelligent applications.Explainable AI necessary to build trust in recommendations.Case study: 83% of operators rejected AI recommendations without explanations.Tulip example demonstrated three of four agreements successfully.Software giants using strategic alliances as competitive advantage.AWS offers comprehensive AI infrastructure, platforms, models, and services.Salesforce created ecosystem both within and outside their platform.SaaS marketplaces bridge AI model providers and businesses.Innovation requires partnerships between software vendors and ISVs.Enterprises forming cohorts with startups to solve business challenges.Software supply chain transparency increasingly important.Government sector slower to adopt cloud and AI technologies.Change resistance remains significant challenge for adoption.69% prioritize improving innovation capability over next year.Participants:Linda Ivy-Rosser - Vice President, Enterprise Software, IT services and Digital Transformation Executive Portfolio, ForresterSee how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon/isv/

New Relic's Chief Customer Officer Arnaldo (Arnie) Lopez details how their observability platform helps 70,000+ customers monitor cloud performance through AWS infrastructure while introducing AI capabilities that simplify operations.Topics Include:Arnie Lopez is SVP, Chief Customer Officer at New Relic.Oversees pre-sales, post-sales, technical support, and enablement teams.New Relic University offers customer certifications.Founded in 2008, pioneered application performance monitoring (APM).Now offers "Observability 3.0" for full-stack visibility.Prevents interruptions during cloud migration and operations.Serves 70,000+ customers across various industries.16,000 enterprise-level paying customers.Platform consolidates multiple monitoring tools into one solution.Helps detect issues before customers experience performance problems.Market challenge: customers using disparate observability solutions.Reduces TCO by eliminating multiple monitoring tools.Targets VPs, CTOs, CIOs, and sometimes CEOs.Decade-long partnership with AWS.Platform built on largest unified telemetry data cloud.Uses AWS Graviton instances and Amazon EKS.AWS partnership enables innovation and customer trust.Three AI approaches: user assistance, LLM monitoring, faster insights.New Relic AI helps write query language (NURCLs).Monitors LLMs in customer environments.Uses AI to accelerate incident resolution.Lesson learned: should have started AI implementation sooner.Many customers still cautiously adopting AI technologies.Goal: continue growth with AWS partnership.Offers compute-based pricing model.Customers only pay for what they use.Announced one-step AWS monitoring for enterprise scale.Amazon Q Business and New Relic AI integration.Agent-to-agent AI eliminates data silos.Embeds performance insights into business application workflows.Participants:Arnie Lopez – SVP Chief Customer Officer, New RelicSee how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon/isv/

PDI Technologies' Steve Antonakakis shares how his company is implementing generative AI across their fuel and retail technology ecosystem through a practical, customer-focused approach using Amazon Bedrock.Topics Include:PDI's COO/CTO discussing generative AI implementationPractical step-by-step approach to AI integrationTesting in real-world settings with customer feedbackAWS Bedrock and Nova models exceeded expectationsEarly adoption phase with huge potentialFuel/retail industry processes many in-person transactionsPDI began in 1983 as ERP providerGrew through 33+ acquisitionsProvides end-to-end fuel industry solutionsOwns GasBuddy and Shell Fuel RewardsProcesses millions of transactions dailyGenerative AI fits into their intelligence plane architectureAWS Bedrock integrates well with existing infrastructureFocus on trusted, controlled, accountable AIProductizing AI features harder than traditional featuresCreated entrepreneurial structure alongside regular product teamsTeam designed to fail fast but stay customer-focusedAI features can access databases without disrupting applicationsCustomers want summarization across different business areasAI provides insights and actionable recommendationsConversational AI replaces traditional reporting limitationsWorking closely with customers to solve problems togetherBeyond prototyping phase, now in implementationAWS Nova provides excellent cost-to-value ratioFocus on measuring customer value over immediate profitabilityRFP use case saved half a million dollarsEarly prompts were massive, now more structuredSetting realistic customer expectations is importantData security approach same as other applicationsTreating AI outputs with same data classification standardsParticipants:Steve Antonakakis – COO & CTO, Retail & Energy, PDI TechnologiesSee how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon/isv/

AWS partners Braze, Qualtrics, and Tealium share strategies for marketplace success, vertical industry expansion, and generative AI integration that have driven significant business growth. Topics Include:Jason Warren introduces AWS Business Application Partnerships panel.Three key topics: Marketplace Strategy, Vertical Expansion, Gen-AI Integration.Alex Rees of Braze, Matthew Gray of Tealium, and Jason Mann of Qualtrics join discussion.Braze experienced triple-digit percentage growth through AWS Marketplace.Braze dedicating resources specifically to Marketplace procurement.Tealium accelerated deal velocity by listing on Marketplace.Tealium saw broader use case expansion with AWS co-selling.Qualtrics views Marketplace listing as earning a "diploma."Understanding AWS incentives and metrics is crucial.Knowing AWS "love language" helps partnership success.Braze saw transaction volume increase between Q1 and Q4.Aligning with industry verticals unlocked faster growth.Tealium sees bigger deals and faster close times.Tealium moved from transactional to strategic marketplace approach.Private offers work well for complex enterprise agreements.Qualtrics measures AWS partnership through "influence, intel, introductions."AWS relationships help navigate IT and procurement challenges.Propensity-to-buy data guides AWS engagement strategy.Marketplace strategy evolving with new capabilities and international expansion.Brazilian marketplace distribution reduces currency and tax challenges.Partnership evolution: sell first, then market, then co-innovate.Braze penetrated airline market through AWS Travel & Hospitality.RFP introductions show tangible partnership benefits.Tealium partnering with Virgin Australia and United Airlines.MUFG bank case study shows joint AWS-Tealium success.Qualtrics won awards despite not completing formal competencies.Focus on fewer verticals yields better results.Gen AI brings both opportunities and regulatory concerns.First-party data rights critical for AI implementation.AWS Bedrock integration provides security and prescriptive solutions.Participants:Alex Rees – Director Tech Partnerships, BrazeJason Mann – Global AWS Alliance Lead, QualtricsMatthew Gray - SVP, Partnerships & Alliances, TealiumJason Warren - Head of Business Applications ISV Partnerships (Americas), AWSSee how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon/isv/

Yashodha Bhavnani, Head of AI at Box, reveals Box's vision for intelligent content management that transforms unstructured data into actionable insights. Topics Include:Yashodha Bhavnani leads AI products at Box.Box's mission: power how the world works together.Box serves customers globally across various industries.Works with majority of Fortune 500 companies.AI agents will join workforce for repetitive tasks.Workflows like hiring will become easily automated with AI.Content will work for users, not vice versa.Customers demand better experiences with generative AI.Box calls this shift "intelligent content management."90% of enterprise content is unstructured data.AI thrives on unstructured data.Current content systems are unproductive and unsecured.AI can generate insights from scattered company knowledge.AI extracts metadata automatically from documents like contracts.Automated workflows triggered by AI-extracted data.Box provides enterprise-grade AI connected to your content.AI follows same permissions as the content itself.Customer data never used to train AI models.AI helps classify sensitive data to prevent leaks.Box offers choice of AI models to customers.AI is seamlessly connected with customer content.Administrators control AI deployment across their organization.Partnership with AWS Bedrock brings frontier models to Box.Box supports customers using their own custom models.Box preparing for AI agents to join workforce.Introduced "AI Units" for flexible pricing.Basic AI included free with Business Plus tiers.Both horizontal and vertical multi-agent architectures planned.Working toward agent-to-agent communication protocols.Participants:Yashodha Bhavnani - VP of Product Management, AI products, BoxSee how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon/isv/

Tech leaders from RingCentral, Zoom and AWS discuss how generative AI is transforming business communications while balancing challenges & regulatory concerns in this rapidly evolving landscape.Topics Include:Introduction of panel on generative AI's impact on businesses.How to transition AI from prototypes to production.Understanding value creation for customers through AI.Introduction of Khurram Tajji from RingCentral.Introduction of Brendan Ittleson from Zoom.How generative AI fits into Zoom's product offerings.Zoom's AI companion available to all paid customers.Zoom's federated approach to AI model selection.RingCentral's new AI Receptionist (AIR) launch.How AIR routes calls using generative AI capabilities.AI improving customer experience through sentiment analysis.The disproportionate value of real-time AI assistance.Economics of delivering real-time AI capabilities.Real-time AI compliance monitoring in banking.Value of preventing regulatory fines through AI.Voice cloning detection through AI security.Democratizing AI access across Zoom's platform.Monetizing specialized AI solutions for business value.Challenges in taking AI prototypes to production.Importance of selecting the right AI models.Privacy considerations when training AI models.Maintaining quality without using customer data for training.Co-innovation with customers during product development.Scaling challenges for AI businesses.Case study of AI in legal case assessment.Ensuring unit economics work before scaling AI applications.Zoom's approach to scaling AI across products.Importance of centralizing but federating AI capabilities.Breaking down data silos for effective AI context.Navigating evolving regulations around AI.EU AI Act restrictions on emotion inference.Balancing regulations with customer experience needs.Future of AI agents interacting with other agents.How AI enhances human connection by handling routine tasks.Impact of AI on company valuations and M&A activity.Participants:Khurram Tajji – Group CMO & Partnerships, RingCentralBrendan Ittleson – Chief Ecosystem Officer, ZoomSirish Chandrasekaran – VP of Analytics, AWSSee how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon/isv/

CEO Joe Kim shares how Sumo Logic has implemented generative AI to democratize data analytics, leveraging AWS Bedrock's multi-agent capabilities to dramatically improve accuracy.Topics Include:Introduction of Joe Kim, CEO of Sumo Logic.Question: Overview of Sumo Logic's products and customers?Sumo Logic specializes in observability and security markets.Company leverages industry-leading log management and analytics capabilities.Question: How has generative AI entered this space?Kim's background is in product, strategy and engineering.Non-experts struggle to extract value from complex telemetry data.Generative AI provides easier interface for interacting with data.Question: How do you measure success of AI initiatives?Focus on customer problems, not retrofitting AI everywhere.Launched "Mo, the co-pilot" at AWS re:Invent.Mo enables natural language queries of complex data.Mo suggests visualizations and follow-up questions during incidents.Question: What challenges did you face implementing AI?Team knew competitors would eventually implement similar capabilities.Single model approach topped out at 80% accuracy.Multi-agent approach with AWS Bedrock achieved mid-90% accuracy.Bedrock offered security benefits and multiple model capabilities.Question: How was working with the AWS team?Partnered with Bedrock team and tribe.ai for implementation.Partners helped avoid pitfalls from thousands of prior projects.Question: What advice for other software leaders?Don't implement AI just to satisfy board pressure.Identify problems without mentioning generative AI first.Innovation should come from listening to customers.Question: Future plans with AWS partnership?Moving toward automated remediation beyond just analysis.Question: Has Sumo Logic monetized generative AI?Changed pricing from data ingestion to data usage.New model encourages more data sharing without cost barriers.Participants:Joe Kim – Chief Executive Officer, Sumo LogicSee how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon/isv/

CTO Arun Kumar discusses how Socure leverages AWS and generative AI to collect billions of data points each day in order to combat sophisticated online fraud at scale.Topics Include:Introduction of Arun Kumar, CTO of SocureWhat does Socure specialize in?KYC and anti-money laundering checksMission: eliminate 100% fraud on the internetFraud has increased since COVIDSocure blocks fraud at entry pointWorks with top banks and government agenciesCTO responsibilities include product and engineeringFocus on increasing efficiency through technologyTwo goals: internal efficiency and combating fraudCountering tools like FraudGPT on dark webMeasuring success through reduced human capital needsFraud investigations reduced from hours to minutesImproved success rates in uncovering fraud ringsDetecting multi-hop connections in fraud networksQuestion: Who's winning - fraudsters or AI?It's a constant "cat and mouse game"Creating a fraud "red team" similar to cybersecurityPartnership details with AWSAmazon Bedrock provides multiple LLM optionsBuilding world's largest identity graph with NeptuneReal-time suspicious activity detectionBlocking account takeovers through phone number changesSuccess story: detecting deepfake across 3,000 IDsCollecting hundreds of data points per identityChallenges: adding selfie checks and liveness detectionFuture strategy: 10x-100x performance improvementsCreating second and third-order intelligence signalsInternal efficiency applications of generative AIAI-powered sales tools and legal document reviewParticipants:Arun Kumar – Chief Technical Officer, SocureSee how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon/isv/

Oron Noah of Wiz outlines how organizations evolve their security practices to address new vulnerabilities in AI systems through improved visibility, risk assessment, and pipeline protection.Topics Include:Introduction of Oron Noah, VP at Wiz.Wiz: largest private service security company.$1.9 billion raised from leading VCs.45% of Fortune 100 use Wiz.Wiz scans 60+ Amazon native services.Cloud introduced visibility challenges.Cloud created risk prioritization issues.Security ownership shifted from CISOs to everyone.Wiz offers a unified security platform.Three pillars: Wiz Cloud, Code, and Defend.Wiz democratizes cloud security for all teams.Security Graph uses Amazon Neptune.Wiz has 150+ available integrations.Risk analysis connects to cloud environments.Wiz identifies critical attack paths.AI assists in security graph searches.AI helps with remediation scripts.AI introduces new security challenges.70% of customers already use AI services.AI security requires visibility, risk assessment, pipeline protection.AI introduces risks like prompt injection.Data poisoning can manipulate AI results.Model vulnerabilities create attack vectors.AI Security Posture Management (ASPM) introduced.Four key questions for AI security.AI pipelines resemble traditional cloud infrastructure.Wiz researchers found real AI security vulnerabilities.Wiz AI ASPM provides agentless visibility.Supports major AI services (AWS, OpenAI, etc.).Built-in rules detect AI service misconfigurations.Participants:Oron Noah – VP Product Extensibility & Partnerships, WizSee how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon/isv/

Ruslan Kusov of SoftServe presents how their Application Modernization Framework accelerates ISV modernization, assesses legacy code, and delivers modernized applications through platform engineering principles.Topics Include:Introduction of Ruslan Kusov, Cloud CoE Director at SoftServeSoftServe builds code for top ISVsSuccess case: accelerated security ISV modernization by six monthsHealthcare tech company assessment: 1.6 million code lines in weeksBusiness need: product development acceleration for competitive advantageBusiness need: intelligent operations automationBusiness need: ecosystem integration and "sizeification" to cloudBusiness need: secure and compliant solutionsBusiness need: customer-centric platforms with personalized experiencesBusiness need: AWS marketplace integrationDistinguishing intentional from unintentional complexityPlatform engineering concept introductionSelf-service internal platforms for standardizationApplying platform engineering across teams (GenAI, CSO, etc.)No one-size-fits-all approach to modernizationSAMP/SEMP framework introductionCore components: EKS, ECS, or LambdaModular structure with interchangeable componentsCase study: ISV switching from hardware to software productsFour-week MVP instead of planned ten weeksSix-month full modernization versus planned twelve monthsAssessment phase importance for business case developmentCalculating cost of doing nothing during modernization decisionsHealthcare customer case: 1.6 million code lines assessedBenefits: platform deployment in under 20 minutesBenefits: 5x reduced assessment timeBenefits: 30% lower infrastructure costsBenefits: 20% increased development productivity with GenAIIntegration with Amazon Q for developer productivityClosing Q&A on security modernization and ongoing managementParticipants:Ruslan Kusov – Cloud CoE Director, SoftserveSee how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon/isv/

Send us a textIn this conversation, Amit Saar shares his journey from software engineering at Microsoft to founding OpenOps. He focuses on the challenges and solutions in FinOps. He highlights the need for automation, accountability, and balancing innovation with governance in managing cloud costs. Amit points out the fatigue that engineering managers face due to overwhelming demands. He stresses the need for better tools and practices to streamline FinOps processes. The discussion also covers the challenges of automating FinOps, the role of no-code platforms, and the importance of community engagement through open sourcing.Topics include the fragmentation of systems in enterprises and the advantages of a no-code approach for automation. Amit discusses monetization strategies for sustaining an open-source model. The conversation wraps up with practical advice on getting started with OpenOps.

Richard Sonnenblick and Lee Rehwinkel of Planview discuss their transition to Amazon Bedrock for a multi-agent AI system while sharing valuable implementation and user experience lessons.Topics Include:Introduction to Planview's 18-month journey creating an AI co-pilot.Planview builds solutions for strategic portfolio and agile planning.5,000+ companies with millions of users leverage Planview solutions.Co-pilot vision: AI assistant sidebar across multiple applications.RAG used to ingest customer success center documents.Tracking product data, screens, charts, and tables.Incorporating industry best practices and methodologies.Can ingest customer-specific documents to understand company terminology.Key benefit: Making every user a power user.Key benefit: Saving time on tedious and redundant tasks.Key benefit: De-risking initiatives through early risk identification.Cost challenges: GPT-4 initially cost $60 per million tokens.Cost now only $1.20 per million tokens.Market evolution: AI features becoming table stakes.Performance rubrics created for different personas and applications.Multi-agent architecture provides technical and organizational scalability.Initial implementation used Azure and GPT-4 models.Migration to AWS Bedrock brought model choice benefits.Bedrock allowed optimization across cost, benchmarking, and speed dimensions.Added AWS guardrails and knowledge base capabilities.Lesson #1: Users hate typing; provide clickable options.Lesson #2: Users don't like waiting; optimize for speed.Lesson #3: Users take time to trust AI; provide auditable answers.Question about role-based access control and permissions.Co-pilot uses user authentication to access application data.Question about subscription pricing for AI features.Need to educate customers about AI's value proposition.Question about reasoning modes and timing expectations.Showing users the work process makes waiting more tolerable.Participants:Richard Sonnenblick - Chief Data Scientist, PlanviewLee Rehwinkel – Principal Data Scientist, PlanviewSee how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon/isv/

Executives from DataRobot, LaunchDarkly and ServiceNow share strategies, actions and recommendations to achieve profitable growth in today's competitive SaaS landscape.Topics Include:Introduction of panelists from DataRobot, LaunchDarkly & ServiceNowServiceNow's journey from service management to workflow orchestration platform.DataRobot's evolution as comprehensive AI platform before AI boom.LaunchDarkly's focus on helping teams decouple release from deploy.Rule of 40: balancing revenue growth and profit margin.ServiceNow exceeding standards with Rule of 50-60 approach.Vertical markets expansion as key strategy for sustainable growth.AWS Marketplace enabling largest-ever deal for ServiceNow.R&D investment effectiveness through experimentation and feature management.Developer efficiency as driver of profitable SaaS growth.Competition through data-driven decisions rather than guesswork.Speed and iteration frequency determining competitive advantage in SaaS.Balancing innovation with early customer adoption for AI products.Product managers should adopt revenue goals and variable compensation.Product-led growth versus sales-led motion: strategies and frictions.Sales-led growth optimized for enterprise; PLG for practitioners.Marketplace-led growth as complementary go-to-market strategy.Customer acquisition cost (CAC) as primary driver of margin erosion.Pricing and packaging philosophy: platform versus consumption models.Value realization must precede pricing and packaging discussions.Good-better-best pricing model used by LaunchDarkly.Security as foundation of trust in software delivery.LaunchDarkly's Guardian Edition for high-risk software release scenarios.Security for regulated industries through public cloud partnerships.GenAI security: benchmarks, tests, and governance to prevent issues.M&A strategy: ServiceNow's 33 acquisitions for features, not revenue.Replatforming acquisitions into core architecture for consistent experience.Balancing technology integration with people aspects during acquisitions.Trends in buying groups: AI budgets and tool consolidation.Implementing revenue goals in product teams for new initiatives.Participants:Prajakta Damle – Head of Product / SVP of Product, DataRobotClaire Vo – Chief Product & Technology Officer, LaunchDarklyAnshuman Didwania – VP/GM, Hyperscalers Business Group, ServiceNowAkshay Patel – Global SaaS Strategist, Amazon Web ServicesSee how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon/isv/

In this episode, Anurag Goel, founder and CEO of Render, explores the challenges of competing with major cloud providers, the evolution of cloud infrastructure, and Render's mission to simplify DevOps complexities. He shares insights from his journey, including his early programming experiences in India and the importance of fostering a supportive environment for success. Anurag reflects on his time at various companies, including startups and his pivotal role in Stripe's early development. He also emphasizes the significance of developer relations and the need for flexible product offerings to accommodate diverse customer needs.00:00 Introduction00:30 What is Anurag Doing Today?07:30 Cloud Infrastructure and Render20:00 First Memory of a Computer22:00 Education in India34:00 Early Career and Growth44:30 The Rise of Stripe1:00:00 Building Render1:11:30 The Importance of Pricing in Cloud Services1:14:15 Streamlined Deployment and Ops 1:27:25 Contact InfoConnect with Anurag: Email: anurag@render.comLinkedin: https://www.linkedin.com/in/anuragoel/X: https://x.com/anuraggoelMentioned in this Episode:Render: https://render.com/Stripe: https://stripe.com/Want more from Ardan Labs? You can learn Go, Kubernetes, Docker & more through our video training, live events, or through our blog!Online Courses : https://ardanlabs.com/education/ Live Events : https://www.ardanlabs.com/live-training-events/ Blog : https://www.ardanlabs.com/blog Github : https://github.com/ardanlabs

Ryan Steeb shares DTEX Systems' strategic approach to implementing generative AI with AWS Bedrock, reducing risk while focusing on meaningful customer outcomes.Topics Include:Introduction of Ryan Steeb, Head of Product at DTEX Systems Explanation of insider risk challenges Three categories of insider risk (malicious, negligent, compromised) How DTEX Systems is using generative AI Collection of proprietary data to map human behavior on networks Three key areas leveraging Gen AI: customer value, services acceleration, operations How partnership with AWS has impacted DTEX's AI capabilities Value of AWS expertise for discovering AI possibilities AWS Bedrock providing flexibility in AI implementation Collaboration on unique applications beyond conventional chat assistants AWS OpenSearch as a foundational component Creating invisible AI workflows that simplify user experiences The path to monetization for generative AI Three approaches: direct pricing, service efficiency, operational improvements Second and third-order effects (retention, NPS, reduced churn) How DTEX prioritizes Gen AI projects Starting with customer problems vs. finding problems for AI solutions Business impact prioritization framework Technical capability considerations Benefits of moving AI solutions to AWS Bedrock Fostering a culture of experimentation and innovation Adopting Amazon's "working backwards" philosophy Balancing customer-driven evolution with original innovation Time machine advice: start experimenting with Gen AI earlier Importance of leveraging peer groups and experts Future outlook: concerns about innovation outpacing risk mitigation Security implications of Gen AI adoption Participation in the OpenSearch Linux Foundation initiative Final thoughts on the DTEX-AWS partnershipParticipants:Ryan Steeb – Head of Product, DTEX SystemsSee how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon/isv/

From cost management to practical implementation, Sage's Amaya Souarez shares invaluable insights on building AI-powered business tools that deliver measurable value to customers.Topics Include:Amaya Souarez introduced as EVP Cloud Services at SageOverview of Sage: offers accounting, finance, HR and payroll tech for small businessesCompany emphasizes human values alongside technology developmentAmaya oversees core cloud services and operations across 200+ productsSage Co-Pilot announced as new AI assistant – helping automate invoicing and cash flow managementCommon misconceptions with Generative AIAI solutions aren't always solution to every problemCompares AI hype to previous blockchain enthusiasmEmphasizes starting with clear use cases before implementationDifference between task-based and reporting-based use casesPartnering with AWS to build accounting-specific language modelsDifferent accounting terminology varies by countryUsing AWS Bedrock and Lex for a domain-specific language model developmentMultiple AI models may be needed for single solutionCustomer feedback drives project funding decisionsAI development integrated into regular product roadmapsFocus on reducing cost per user for AI featuresSuccess story: reducing 20-hour task to 5 minutesTracks AI usage costs per customer interactionEarly Gen AI hype caused confusion in the marketPlans to make domain-specific models available via APIWill offer language models on AWS MarketplaceEmphasizes practical AI application over blind implementationParticipants:Amaya Souarez - EVP Cloud Services and Operations, SageSee how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon/isv/

Box's Chief Product Officer Diego Dugatkin discusses how the enterprise content management platform is leveraging AI through partnerships with AWS Bedrock and continuing to innovate for their customers.Topics Include:Introduction of Diego Dugatkin as Box's Chief Product OfficerBox provides cloud content management for enterprise customersFocus on Intelligent Content ManagementBox serves 115,000 customers including 70% of Fortune 500Company manages approximately one exabyte of enterprise dataBox expanding product portfolio to offer more customer valuePartnership with AWS Bedrock for AI implementation announcedCollaboration with Anthropic for LLM technology integrationBox offers neutral approach letting customers choose preferred LLMsCommon misconceptions about generative AI capabilities and limitationsGenerative AI helps accelerate contract analysis and classification processesBox Hubs enables content curation and multi-document queriesSuccess measured through hub creation and query accuracy metricsLong-term AWS partnership continues expanding with new technologiesAmazon is major Box customer while Box uses AWSAPI integration important for third-party developer implementationsAI development exceeding speed expectations in efficiency improvementsChallenges remain in defining AI agent roles and capabilitiesContent strategy crucial for deploying intelligent content managementCompanies must prepare for AI agents in workplaceFlexibility in tech stack recommended over single-vendor approachNext 12-24 months will see accelerated industry changesBox maintains innovative culture through intrapreneurship approachCompany regularly hosts internal and external hackathonsFocus on maintaining integrated platform while acquiring companiesPartnership between Box and AWS continues growing strongerParticipants:Diego Dugatkin – Chief Product Officer, BoxSee how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon/isv/

Through case studies of Graviton implementation and GPU integration, Justin Fitzhugh, Snowflake's VP of Engineering, demonstrates how cloud-native architecture combined with strategic partnerships can drive technical innovation and build business value.Topics Include:Cloud engineering and AWS partnershipTraditional databases had fixed hardware ratios for compute/storageSnowflake built cloud-native with separated storage and computeCompany has never owned physical infrastructureApplications must be cloud-optimized to leverage elastic scalingSnowflake uses credit system for customer billingCredits loosely based on compute resources providedCompany maintains cloud-agnostic approach across providersInitially aimed for identical pricing across cloud providersNow allows price variation while maintaining consistent experienceConsumption-based revenue model ties to actual usagePerformance improvements can actually decrease revenueCompany tracked ARM's move to data centersInitially skeptical of Graviton performance claimsPorting to ARM required complete pipeline reconstructionDiscovered floating point rounding differences between architecturesAmazon partnership crucial for library optimizationGraviton migration took two years instead of oneAchieved 25% performance gain with 20% cost reductionTeam requested thousands of GPUs within two monthsGPU infrastructure was new territory for SnowflakeNeeded flexible pricing for uncertain future needsSigned three to five-year contracts with flexibilityTeam pivoted from building to fine-tuning modelsPartnership allowed adaptation to business changesEmphasizes importance of leveraging provider expertiseRecommends early engagement with cloud providersBuild relationships before infrastructure needs ariseMaintain personal connections with provider executivesParticipants:Justin Fitzhugh – VP of Engineering, SnowflakeSee how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon/isv/

In this episode, I provide an update on the UK regulator investigation into the cloud services market, I talk an increase of Windows 11 adoption, I discuss a helpful script to combat a vulnerability exploit and much more! Reference Links: https://www.rorymon.com/blog/report-on-cloud-service-market-win11-on-the-rise-dell-orders-return-to-the-office/

In this AWS panel discussion, Naveen Rao, VP of AI of Databricks and Vijay Karunamurthy, Field CTO of Scale AI share practical insights on implementing generative AI in enterprises, leveraging private data effectively, and building reliable production systems.Topics Include:Sherry Marcus introduces panel discussion on generative AI adoptionScale AI helps make AI models more reliableDatabricks focuses on customizing AI with company dataCompanies often stressed about where to start with AIBoard-level pressure driving many enterprise AI initiativesStart by defining specific goals and success metricsBuild evaluations first before implementing AI solutionsAvoid rushing into demos without proper planningEnterprise data vastly exceeds public training data volumeCustomer support histories valuable for AI trainingModels learning to anticipate customer follow-up questionsProduction concerns: cost, latency, and accuracy trade-offsGood telemetry crucial for diagnosing AI application issuesSpeed matters more for prose, accuracy for legal documentsCost becomes important once systems begin scaling upOrganizations struggle with poor quality existing dataPrivacy crucial when leveraging internal business dataRole-based access control essential for regulated industriesAI can help locate relevant data across legacy systemsModels need organizational awareness to find data effectivelyPrivate data behind firewalls most valuable for AICustomization gives competitive advantage over generic modelsCurrent AI models primarily do flexible data recallNext few years: focus on deriving business valueFuture developments in causal inference expected post-5 yearsComplex multi-agent systems becoming more importantScale AI developing "humanity's last exam" evaluation metricDiscussion of responsibility and liability in AI decisionsCompanies must stand behind their AI system outputsExisting compliance frameworks can be adapted for AIParticipants:Naveen Rao – VP of AI, DatabricksVijay Karunamurthy – Field CTO, Scale AISherry Marcus Ph.D. - Director, Applied Science, AWSSee how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon/isv/

Plus, Google fights $4.55 billion EU antitrust fine over Android. And, tech stocks rebound after yesterday's DeepSeek rout. Julie Chang hosts. Learn more about your ad choices. Visit megaphone.fm/adchoices

Alan Rozenshtein, Associate Professor at the University of Minnesota Law School and Senior Editor at Lawfare, sits down with David Kris, founder of Culper Partners and the former Assistant Attorney General for National Security in the Obama administration, to talk about a new paper that David has published as part of Lawfare's ongoing Digital Social Contract series, entitled "A Data Proxy for Clients of Cloud Service Providers.”Kris argues that cloud storage offers significant benefits for security and efficiency, but many organizations may be hesitant to adopt it due to the risk of secret disclosure: the practice by which law enforcement can compel cloud service providers to turn over customer data while legally prohibiting them from notifying the customer. To address this concern, Kris proposes the appointment of a "data proxy," a highly trusted individual (like a retired federal judge) who would be contractually authorized to represent the organization's interests when it cannot represent itself due to a nondisclosure order.To receive ad-free podcasts, become a Lawfare Material Supporter at www.patreon.com/lawfare. You can also support Lawfare by making a one-time donation at https://givebutter.com/c/trumptrials.Support this show http://supporter.acast.com/lawfare. Hosted on Acast. See acast.com/privacy for more information.