
Show overview
AWS for Software Companies Podcast has been publishing since 2023, and across the 3 years since has built a catalogue of 206 episodes. That works out to roughly 95 hours of audio in total. Releases follow a weekly cadence.
Episodes typically run twenty to thirty-five minutes — most land between 20 min and 33 min — though episode length varies meaningfully from one episode to the next. None of the episodes are flagged explicit by the publisher. It is catalogued as a EN-language Technology show.
The show is actively publishing — the most recent episode landed 3 days ago, with 21 episodes already out so far this year. The busiest year was 2025, with 113 episodes published. Published by Nate Goyer.
From the publisher
Stay ahead of the rapidly evolving cloud and AI landscape with the AWS for Software Companies podcast. Hear from renowned software leaders, respected industry analysts, and experienced consultants alongside AWS experts as they explore the technologies shaping the future—from generative AI and agentic systems to intelligent cloud architectures, and modern data management. Learn how AI agents are transforming enterprise workflows, how leading companies are modernizing their cloud strategies with security best practices at the core, and what's driving the next wave of SaaS innovation. New episodes drop regularly to keep you informed on the trends that matter most to your business.
Latest Episodes
View all 206 episodesEp206: Building Agentic Products at Enterprise Scale with Datadog, Fireworks, Okta, Writer AI and AWS
Ep205: AI Teammates Are Here - Asana's Multiplayer Approach to an Agentic Future
Ep204: Hacker Mindset at Scale: Inside Detectify's AI-Powered Security Platform on AWS
Ep203: Beyond Observability - How Dynatrace Uses AI to Fix Problems Before You Know They Exist
Ep202: Self-Driving Infrastructure - How Vercel Is Automating the Future of Web Deployment
Ep201: Agentic AI - Business and Technical Trends with Olawale Oladehin
Ep200: Scaling and Monetizing AI-Powered Products with ServiceNow, TwelveLabs and AWS

Ep 199Ep199: From Reactive to Proactive: The Observability Revolution with LogicMonitor
From 3am war rooms to self-healing infrastructure, LogicMonitor's GM of AI shares a compelling vision for how observability and agentic AI are transforming IT organizations worldwide.Topics Include:LogicMonitor is a 15-year-old AI-powered hybrid observability company.Their AI product, Edwin AI, targets IT alert fatigue and noise.Enterprise IT teams are drowning in signals from dozens of monitoring tools.Generative AI evolved from machine learning — agents are the next frontier.LogicMonitor's first Edwin use case: help teams know what to focus on.Key lesson learned: stop chasing perfection and start experimenting faster.AI adoption requires serious change management, not just technical deployment.Success metrics should be process efficiency, not vanity adoption numbers.LogicMonitor accelerated software releases from monthly to weekly to daily.AWS Bedrock powers Edwin AI; Agent Core reduces infrastructure complexity.Agentic AI will run long, complex workflows without human intervention.The future is self-healing infrastructure — systems that sense, fix, and notify.Participants:Karthik Sj – General Manager of AI, LogicMonitorSee how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/

Ep 198Ep198: Protect, Secure, Recover: How Cohesity Keeps Enterprise Data Resilient
Cohesity CPO Vasu Murthy breaks down how enterprise data protection has evolved into a 24/7 cyber recovery operation — and why the battle against ransomware is now being fought with AI on both sides.Topics Include:Cohesity protects, secures, and provides insights into enterprise data globally.70% of Fortune 500 companies trust Cohesity with their critical data.Cyber attacks are now the dominant threat to enterprise data resilience.Cohesity recently merged with Veritas, dramatically expanding its customer base.Real-world rescue: a cyber-hit company ran payroll on time anyway.Recovery operations run 24/7, with dozens of active rescues at any time.The threat landscape is now AI versus AI — and escalating fast.Cohesity enables customers to practice cyber recovery drills through automation.AI is accelerating product cycles — planning that took months now takes weeks.More than a third of Cohesity's latest release was AI-assisted code.Flatter teams and less hierarchy are defining the new CPO playbook.AWS partnership innovations like Glacier Instant Retrieval delivered 30% cost savings.Participants:Vasu Murthy – Chief Product Officer, CohesitySee how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/

Ep 197Ep197: From Dashboards to Agents: How Qlik Is Reinventing Data Analytics with AI
CTO Sam Pierson explains how Qlik’s associative engine and agentic AI are transforming the way businesses uncover insights and what’s next on the data frontier.Topics Include:Qlik is a 30-year-old data analytics and AI company with global customers.Qlik's associative engine surfaces insights from data you aren't even examining.A paper manufacturer optimized supply chain routing and navigated tariff complexity.Generative AI can't easily query databases — Qlik's engine bridges that gap.Qlik built an agentic layer enabling natural language conversations with your data.MCP integration lets users access Qlik insights directly from tools like Claude Desktop.Qlik runs entirely on AWS, with global regions built around local compliance requirements.The AWS partnership prioritizes mutual success over transactional service relationships.Agents will mature in 2026; some agentic bets will succeed, others will be refactored.Fine-tuned, smaller language models will grow in importance alongside larger ones.AI adoption requires restructuring workflows end-to-end, from product spec to go-to-market.Qlik is hiring for curiosity and agency — people who experiment without waiting for permission.Participants:Sam Pierson – Chief Technology Officer, QlikSee how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/

Ep 196Ep196: Agentic AI and the Future of Cloud Security with Sumo Logic
Sumo Logic's VP of Security Strategy reveals how a ground-up agentic framework transformed their platform, and why clean data and autonomous agents are rewriting the rules of cloud security.Topics Include:Sumo Logic is a cloud analytics platform ingesting data from complex IT stacks.Built on AWS from the start, leveraging microservices for scalable solutions.Early AI efforts produced a natural language query co-pilot for security data.Bolting AI onto existing platforms proved brittle and one-dimensional.Customer feedback drove a decision to redesign AI from the ground up.The Dojo AI framework unifies purpose-built agents across the entire platform.New agents include a SOC analyst agent, knowledge agent, and MCP server.New frontier models on Bedrock give the whole platform an instant brain transplant.Autonomous agents require rethinking security controls beyond traditional programmatic guardrails.Federal and global customers demand rigorous, levelled-up security across all regions.Clean, normalized data proved the biggest unlock for reliable AI query results.Agent-to-agent communication and MCP will define the next era of AI platforms.Participants:Chas Clawson – Vice President, Security Strategy, Sumo LogicSee how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/

Ep 195Ep195: Tax Compliance at Scale: How Avalara Is Rewriting the Rules with AI and AWS
Avalara's Chief Architect Tim Diekmann reveals how AI and agentic technology are transforming tax compliance and accuracy across 40,000 jurisdictions leveraging AWS.Topics Include:Avalara provides tax compliance software across North America, Europe, and beyond.They operate between commerce and government, covering 40,000+ jurisdictions.Services span registration, sales tax calculation, and certificate management.Avalara was the only company keeping pace with rapid tariff changes.AI is used to parse unstructured documents like tax notices and publications.Intelligent mapping automates ERP integration across vastly different system configurations.GenAI lets customers query billions of transactions using plain conversational language.Avalara and AWS are now engaged in a promising co-selling motion.Time-to-go-live and transaction accuracy are the key success metrics tracked.Amazon Q was rolled out company-wide, achieving 95% developer adoption.AI literacy is now prioritized across legal, HR, and engineering teams alike.Agentic AI will embed Avalara directly inside customer ERP systems going forward.Participants:Tim Diekmann – SVP of Engineering, Chief Architect, AvalaraSee how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/

Ep 194Ep194: Measuring What Matters: A Future of Transparency, Safety and Honest Productivity with Honeycomb
Honeycomb Co-founder and CTO Charity Majors explains why measuring the right engineering metrics in the age of AI matters more than chasing numbers.Topics Include:Charity Majors introduces Honeycomb as the original observability company for complex systemsHoneycomb solves high cardinality problems across millions of individual customer experiencesTheir MCP tool ranked top five in Stack Overflow's most-used listCanva lets developers interact with production software directly from their IDEAI acts as an amplifier requiring strong reliability and observability foundationsMeasuring success requires multiple metrics to avoid gaming single numbersHoneycomb adopted Intercom's 2X productivity challenge enlisting employees to identify gainsWriting code was never the hard part even before generative AI arrivedHoneycomb created AI values prioritizing transparency and emotional safety for employeesStaff tested boundaries on resources and environmental impact prompting honest discussionsHoneycomb acquired Grok and shipped Query Assistant Canvas and MCP productsFuture concerns include AI economics shifting and AI-native developers lacking foundational expertiseParticipants:Charity Majors – Co-Founder/CTO, Honeycomb.ioSee how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/

Ep 193Ep193: The Conductor Behind Your Data Orchestra: Astronomer's Approach to AI Pipeline Management
Astronomer's Steven Hillion reveals how OpenAI, Anthropic, Uber, and Lyft use Apache Airflow to orchestrate AI and machine learning pipelines at scale on AWS.Topics Include:Steven Hillion leads data and AI at AstronomerApache Airflow surpassed Spark and Kafka in community metricsAstronomer coordinates data flow like conductor orchestrating instrumental platformsOrganizations with data engineering teams use Airflow at scaleCustomers already used Airflow for ML before official promotionUber and Lyft orchestrate pricing models using AirflowAstronomer runs on AWS with close integration partnershipsOpenAI Anthropic and GitHub Copilot use Airflow for operationsInternal data team uses Airflow creating feedback loopsEvolved from constrained AI reports to agentic workflowsPlatform monitors generative AI output quality at user interactionsMetadata and context increasingly critical for AI applicationsLearn more at Astronomer’s Data FlowCast podcastParticipants:Steven Hillion – SVP, Data and AI, AstronomerSee how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/

Ep 192Ep192: Human-in-the-Loop: How Docupace Balances Innovation and Risk in Wealth Tech
Learn how Docupace transformed from cloud-native platform to AI-powered wealth tech leader, leveraging AWS partnerships and customer obsession to accelerate growth.Topics Include:Docupace Technologies has served wealth management firms for twenty years.Three SaaS product lines streamline advisor workflows and back offices.AI transforms both customer operations and Docupace's internal business practices.Trust between advisors and investors drives conservative technology adoption approach.Serving seven top-ten broker dealers demands careful data security strategies.AI shifts financial systems from deterministic certainty to probabilistic outcomes.Industry began AI adoption with simple meeting note-taking applications.Docupace's agentic AI framework enables safe, observable, orchestrated agent deployment.Multiple verification layers and human oversight ensure zero-error financial operations.Internal AI implementation required nine months navigating change management hurdles.Team curiosity and rapid experimentation matter more than traditional skill sets.AWS customer obsession and partnership programs dramatically accelerate business growth.Participants:Michael Pinsker – Founder and President, Docupace TechnologiesSee how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/

Ep 191Ep191: Building AI Success - How Boomi Automates Anything and Connects Everything
Boomi CEO Steve Lucas reveals how to flip AI's 95% failure rate to your favour with practical integration strategies, real-world agent deployments, and an AWS partnership.Topics Include:Boomi solves the forever problem of complexity across applications and systemsTwenty-five thousand customers use Boomi to automate anything and connect everythingBoomi moves more data per second than the entire Visa networkAI agents now integrate systems through simple commands, no coding requiredAgentic platform built with AWS creates custom AI agents in real timeUse cases include expense monitoring and heart defibrillator battery checks dailyAutomotive companies use AI agents to assess tariff risks across supply chainsHospitals deploy agents to detect patient falls and alert medical professionals immediatelyControl Tower co-innovated with AWS monitors and manages all AI agents centrallyDeterministic processes like payroll shouldn't use AI, probabilistic challenges shouldNinety-five percent of AI projects fail due to data access problemsAgentic workshops help companies identify high-ROI opportunities and achieve AI successParticipants:Steve Lucas – Chairman & CEO, BoomiSee how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/

Ep 190Ep190: The Future of Commerce Automation: How Fabric is Transforming Retail Operations
Fabric CTO Ankush Goyal reveals how AI Search is transforming commerce discovery and why merchants need AI agents to compete effectively.Topics Include:Fabric builds AI agents for commerce, solving merchant visibility challengesCommerce shifting due to AI Search channels and smaller retail teamsProduct Agent monitors and improves product visibility across AI channelsPetMeds uses Fabric to optimize AI Search and automate SKU onboardingFabric evolved from commerce platform company to AI agent solutionsAgentic and generative AI work together to optimize product catalogsFabric uses AWS EKS, Bedrock, S3, and Nova models heavilyAWS partnership connects Fabric with industry leaders and growth opportunitiesAWS services enable reliable, cost-effective, and performant enterprise AI agentsPrototyping agents is easy, but enterprise-grade reliability is extremely challengingFour key learnings: workflow reliability, context engineering, cost effectiveness, feedback loopsCTOs should define agent goals, guardrails, context, and evaluations earlyLong-running workflow durability and snapshots prevent costly repeated work failuresFuture innovations focus on specialized models, retrieval frameworks, automated evaluationsMerchants can evaluate AI Search performance at fabric.inc or LinkedInParticipants:Ankush Goyal – Chief Technology Officer, FabricSee how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/

Ep 189Ep189: Banking on AI - How Abrigo is Revolutionizing Community Finance with Intelligent Automation
Abrigo's Chief Product Technology Officer reveals how they're leveling the playing field for 2,400 community banks using AWS-powered AI to compete with billion-dollar financial institutions.Topics Include:Abrigo serves 2,400 community banks and credit unions across the USThey provide risk management, fraud detection, and digital loan origination solutionsConnect platform delivers data analytics for institutions with legacy systemsCommunity banks need instant digital experiences to compete with fintech upstartsCustomers expect Uber-like speed from application to cash within hoursThree technology waves transformed finance: iPhone, cloud computing, then AIChatGPT changed conversational experiences and knowledge search expectations in bankingAI enables instant policy search for new employee onboarding needsEvery minute saved from grunt work gets redeployed into customer relationshipsSimple borrower experiences work across all demographics from boomers to millennialsAbrigo embraced agentic AI early using AWS Bedrock and Agent CoreNew guardrails and evaluations accelerate deterministic workflow reimagination with agentsParticipants:Ravikumar Nemalikanti – Chief Product and Technology Officer, AbrigoSee how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/

Ep 188Ep188: Disruption, Culture and Technology – Halo's Unique Approach to Enterprise Innovation
Hear how Halo manages market disruption and technology innovation with their unique culture, helping them scale to be a leader in workflow automation software.Topics Include:Halo serves 125,000 teams across 75 countries with enterprise ITSM solutionsPaul Hamilton founded company 21 years ago as freelance IT consultantBuilt ticketing software to track their own freelance client work originallyNo marketing budget so mastered organic SEO without paid advertising spendReached number one Google ranking globally for help desk software 2006Hired first employee in 2011 when co-founder wanted outAWS partnership began years ago recognizing trajectory not current snapshot sizeAWS team proactively delivered 20 percent infrastructure optimization cost savings recentlyHalo reducing prices using savings for customer value creationHires graduates and trains them rather than poaching experienced enterprise talentMonday morning all-company meetings ensure transparency with minimal management hierarchy levelsNo traditional sales teams, culture emphasizes autonomy and employee ownership stakesTechnology completely rebuilt 2017-2018 delivering deployments in one-third typical timeframesTotal cost ownership 70 percent lower than competitors while winning tendersVision transcends software through music festivals, documentaries pioneering fulfilling workplace cultureParticipants:Paul Hamilton – CEO and Founder, HaloAlison Kay – Vice President / Managing Director, AWS UKISee how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/

Ep 187Ep187: Beyond Vector Search - How Neo4j Delivers Context for Intelligent Agents
Neo4j's Ajay Singh discusses future shifts in AI and why knowledge graphs may be the missing layer in your Gen AI strategy.Topics Include:Ajay Singh from Neo4j discusses graph intelligence platform serving 80+ Fortune 100 companies.Financial services firms use Neo4j knowledge graphs to detect fraud rings and accounts.IT companies build digital twins of infrastructure to analyze attack surfaces and vulnerabilities.Knowledge graphs provide richer context for Gen AI agents beyond what vector search offers.Gaming company achieved 10x faster insights and 92% reduction in analyst data gathering.Transportation company improved tariff code workflow from 50% abandonment to 95% completion rate.Neo4j has partnered with AWS since 2013, running on AWS infrastructure and Marketplace.Customers combine Neo4j with AWS Bedrock and SageMaker to build agentic AI applications.Neo4j evolved from late-stage AWS collaboration to early-stage joint customer solution development approach.Success requires business-first mindset over technology-first to avoid POCs that never reach production.Effective Gen AI needs semantic layers and knowledge graphs, not just throwing documents at LLMs.Future agents will tackle outcome-based objectives requiring explainability, security, and proper LLM operations.Participants:Ajay Singh – Global Vice President, Neo4jSee how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/