AWS for Software Companies Podcast

• Ep181: AWS Agentic AI Marketplace as your Growth Multiplier with Atlassian and Netskope

  Matt Yanchyshyn, AWS Marketplace and Partner Services VP, reveals how AI agents are transforming enterprises worldwide while Atlassian and Netskope leaders share strategies for scaling up Agentic AI marketplace deals.Topics Include:Matt Yanchyshyn of AWS opens with massive shift to multi-agent production systemsEnterprise software seeing huge AI adoption: 33% will include AI by year endAutomated agents now handle Matt's daily workflow, prioritizing emails and messages autonomouslyReal business transformation across financial reporting, demand forecasting, and automated incident managementAWS Marketplace team productivity up 31%, deploying software 27% faster with agentsNew agent mode for Marketplace uses autonomous data collection improving customer experiencesSuccess requires proper data governance with fine-grained access controls for safe operationsQ Developer and Qiro CLI integrate seamlessly into developer workflows without disruptionAWS maintains 400+ MCP servers, shared spec farms enabling teams to collaborate effectivelyEmbedded experts and principal engineers spread agent knowledge and measure productivity closelyAndy Horwitz notes security leads Marketplace growth, primarily through private offer expansionNetskope's new DSPM product addresses AI data security, driving strong customer adoption momentumEnterprise customers now ask if vendors are AWS badged, deals 41-58% largerAndy advises ISVs: prepare sales teams thoroughly, focus co-sell, secure executive buy-inBill Hustad emphasizes distinct marketplace strategy, seller training, and ruthless operational tracking for successParticipants:Bill Hustad - Global Head of Channel and GTM Ecosystems, AtlassianAndy Horwitz – SVP, Global Partner Ecosystems, NetskopeMatt Yanchyshyn – VP, AWS Marketplace & Partner Services, 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/

  --------  

  33:37

  --------

  33:37
• Ep180: Agent-Based Learning Systems - How Scale AI Transforms Enterprise Knowledge into Business Value

  Raviteja Yelamanchili shares how Scale AI transformed banking cycles from one year to real-time and why your most valuable enterprise data isn't being collected.Topics Include:Scale evolved from data annotations company to enterprise AI solutions providerHealthcare system transformed patient transcriptions into value using reinforcement learning researchBlank slate customer problems allow Scale to experiment with latest methodsMany customers propose solutions before explaining their actual underlying business problemsBiggest AI misconception: technology will replace jobs rather than augment productivityDon't wait for perfect AI—start learning through iteration and evolution nowBanking credit cycle transformed from one-year process to real-time strategic insightsScale deploys flexibly across EC2, EKS, or Bedrock based on customer requirementsEnterprises want business value generation more than academic research papers aloneNext 12-24 months focus: making data consumable and leveraging unused datasetsTribal knowledge from experienced SMEs represents most valuable yet uncollected dataAgent-based learning captures expertise through feedback loops on Scale's SGP platformParticipants:Raviteja Yelamanchili - Head of Solution Engineering, Scale AISee how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/

  --------  

  26:58

  --------

  26:58
• Ep179: How AI is Changing Everything for All of Us – McKinsey & Company's Lareina Yee on the new software innovator’s dilemma

  In a keynote address from re:Invent, McKinsey & Company's Lareina Yee shares fascinating data, trends and best practices on AI adoption, the future of skillsets, and leadership insights that are needed for AI transformation at scale.Topics Include:Over 80% of companies have adopted AI in at least one business function currently.Despite heavy investment, 62% of companies remain in experimental or pilot phases with AI.Only 7% of organizations have achieved full-scale AI implementation, up from 2% earlier this year.Agentic AI has proliferated rapidly across functions from knowledge management to manufacturing in one year.Between 45% and 5% of companies have implemented AI agents across different business functions today.AI's productivity potential represents $4.4 trillion in economic value beyond just cost savings opportunities.Innovation ranks as the number one goal for AI investments, ahead of cost reduction priorities.Employee satisfaction, customer satisfaction, and competitive differentiation drive AI adoption alongside revenue growth and cost.High AI performers view implementation as total enterprise transformation, not just technology deployment projects.Leading companies spend 4.9 times more budget on AI investments compared to average performing organizations.Traditional software stacks evolved to SaaS, now transforming into AI-ready tech stacks within one generation.Job outlook remains mixed: 32% expect losses, 13% expect increases, 43% see no major change.Since 2023, significant skill shifts show increased demand for software development and business intelligence capabilities.AI fluency has increased seven times as the most sought-after skill across all job types.AI fluency means using AI in everyday work, not building models or creating large language models.Skills like driving records, coaching, customer service, and management remain harder to automate with current AI.Transactional, data-driven repetitive tasks like inventory management and invoicing face highest automation exposure currently.Historical technology revolutions like electricity created six to eight jobs for every one job displaced.New roles like prompt engineering emerge, requiring skills like effective questioning rather than technical coding.Participants:Lareina Yee - Director of Technology Research, McKinsey & CompanySee how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/

  --------  

  32:47

  --------

  32:47
• Ep178: Agents meet SaaS - Inside the next generation of software delivery

  AWS Principal Solutions Architect Wallace Printz explains how agents are reshaping SaaS business models, pricing strategies, and technical architectures.Topics Include:Wallace Printz discusses agentic workloads transforming SaaS with largest AWS customersNew interaction models include generative UI, voice agents, and proactive workAgents extending SaaS products to interact with external systems and businessesVirtual teammates enabling cross-department collaboration and upskilling non-expert users effectivelyMonetization strategies evolving as predictable costs become variable with agentsThree patterns: dedicated agents, shared agents, and multi-tenant personalized agentsMulti-tenant agents enable hyper-personalized experiences using individual tenant context enrichmentAgent-centric business strategy requires real assessment beyond AI hype cycleAgent orchestration complexity grows with multiple specialized agents interacting togetherTenant isolation requires JWT tokens and AWS Bedrock Agent Core identityCost-per-tenant management needs LLM throttling, tiering, and unified control planeMulti-tenancy creates sticky personalized experiences; AWS white paper releasing soonParticipants:Wallace Printz - Principal Solution Architect, 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/

  --------  

  43:53

  --------

  43:53
• Ep177: Agentic AI for business transformation with Boomi, Demandbase and Smarsh

  Industry leaders from Boomi, Demandbase and Smarsh share hard-won lessons on balancing AI creativity with guardrails, why data quality trumps frameworks, and deploying AI at scale.Topics Include:Three industry leaders share experiences building AI solutions at Boomi, Demandbase, and Smarsh.Smarsh manages trillion communications for financial services, detecting bad actors across multiple channels.Boomi built agent studio, garden, and control tower while spawning 33,000 internal agents.Chris Timmerman used vibe coding to build embeddable Boomi in five months solo.Companies balance creativity with guardrails, starting with IT policies before unleashing innovation.Internal adoption driven by empowering teams to build their own solutions versus top-down.Demandbase saw 70% adoption within six months through grassroots approach and local champions.Measuring success proves challenging, comparable to tracking Excel usage rather than specific KPIs.Companies focus on outcomes like touch-free bug fixes and support metrics versus raw usage.Biggest lesson: Data quality and context determine success more than agentic frameworks.Need scaling framework from low-risk UX improvements to high-risk automation with appropriate guardrails.Industry created fatigue by overpromising; should have started smaller with realistic expectations.Participants:Chris Timmerman – Vice President, Global Services Delivery, BoomiHarshal Dedhia – Vice President of AI, DemandbaseBrandon Carl - Executive Vice President of AI and Product Strategy, SmarshAllison Johnson - AMER Technology Partnerships Leader, 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/

  --------  

  44:23

  --------

  44:23

More Business podcasts

Trending Business podcasts

About AWS for Software Companies Podcast