Podcast
AWS for Software Companies Podcast
Hosted by AWS - Amazon Web Services · EN
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.
29episodes
Episodes
Newest firstAll episodes
Ep209: Starburst Data's Blueprint for the AI Era with AWS
3d ago00:16:42Tap to summarizeFrom cracked data foundations to multi-agent AI, Starburst Data's co-founder shares hard-won lessons on getting the right data, not just more of it.Topics Include:Matthew Fuller, co-founder and VP of Product at Starburst Data, joins the show.Starburst is built on Trino, a fast SQL engine for federated data queries.Their platform lets users query data across lakes, stores, and databases seamlessly.Governed "data products" give organizations access to their full data estate in context.A strong data foundation is essential before any AI use case can succeed.AI doesn't create data problems — it exposes the cracks already there.Common mistake: assuming everyone in an org defines "customer" or "revenue" the same way.More data isn't always better — getting the right data is what matters.Customers include HSBC, Comcast, Zalando, ZoomInfo, and DBS, many running on AWS.AWS partnership spans technical support, SLA reliability, and proactive product briefings.Advice for product leaders: always anchor new technology back to the customer problem.2026 will be defined by specialized multi-agents working together autonomously.Participants:Matt Fuller – Co-Founder, Vice President of Product, Starburst DataSee how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/
Transcribe →Ep208: Built to Survive: CockroachDB's Role in the Agentic AI Era
1w ago00:17:26Tap to summarizeFind out why the world's largest banks and enterprises trust CockroachDB for mission-critical infrastructure, and what a decade of AWS partnership means for the future of cloud-native data.Topics Include:Cockroach Labs makes CockroachDB, a distributed SQL database built for resilience.It delivers cloud-native consistency that legacy relational databases simply cannot match.The name "cockroach" reflects survivability — it's designed to never go down.Target customers include major banks, trading platforms, retailers, and gaming companies.AI is forcing enterprises to accelerate database modernization from the board level down.AWS has been a foundational cloud partner for Cockroach Labs for a decade.The CockroachDB-AWS integration spans EC2, S3, Bedrock, and Amazon Q-Transform.AWS partnership shapes both product roadmap decisions and go-to-market execution.New partners should educate themselves first — AWS programs are deep and extensive.CockroachDB now supports native vector search for RAG and generative AI applications.Agentic AI could mean trillions of digital agents demanding real-time data infrastructure.Database modernization and AI adoption will only accelerate dramatically through 2027.Participants:Cassie Zimmerman – Senior Director, Global Strategic Partnerships, Cockroach LabsSee how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/
Transcribe →Ep207: The AI Arms Race: How Vectra AI Uses Agentic AI to Outpace Cyber Attackers
2w ago00:13:31Tap to summarizeGreg Murphy of Vectra AI explains why no single security tool is enough in 2026, and how AI is transforming overwhelmed security teams into lean, highly responsive defense operations.Topics Include:Vectra AI helps enterprises detect and respond to cyberattacks before they become breaches.CISOs face millions of alerts monthly with dangerously understaffed security teams.Vectra pioneered AI-driven triage to prioritize only the most critical threats.The result: analysts act on two or three alerts, not thousands.Generative AI is now actively being weaponized by sophisticated bad actors.The first fully AI-orchestrated cyberattack by a nation state has already happened.Vectra and AWS Bedrock are building autonomous agents to fight back.Agentic AI can investigate thousands of incidents and surface only what matters.Over-reliance on single tools like EDR leaves dangerous gaps in defense.Modern attacks move fluidly across identity, network, and cloud environments simultaneously.AI stitches cross-surface signals together, revealing attacks hidden in isolated events.Best practice: assume breach, expand your network definition, and layer best-of-breed solutions.Participants:Greg Murphy – Chief Business Officer, Vectra AISee how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/
Transcribe →Ep206: Building Agentic Products at Enterprise Scale with Datadog, Fireworks, Okta, Writer AI and AWS
3w ago00:56:31Tap to summarizeIf you're betting on agentic AI, hear directly from the builders navigating the challenges, innovating pricing models, and creating the coming reality where every employee manages thousands of agents.Topics Include:Four panelists represent the full AI stack: build, run, secure, monitor.Agentic AI moved faster than anyone predicted just 18 months ago.Writer AI's no-code agent builder missed both its target personas entirely.Non-technical users now just prompt agents instead of building workflows.Fireworks AI processes over ten trillion tokens daily across open models.DeepSeek's Christmas release tripled Fireworks' capacity needs almost overnight.Okta identified agent identity as a security problem from day one.91% of organizations are already using AI agents in some capacity.Datadog evolved naturally from dashboards to autonomous investigative agents.Bits.ai agents now diagnose production incidents before engineers wake up.Trust requires explainability — black-box agents stall enterprise adoption cold.Human-in-the-loop remains essential; risk tolerance varies wildly by organization.Writer AI compressed a four-month retail workflow down to one week.Multi-provider inference consistency is one of the hardest unsolved infrastructure problems.Agentic pricing models are fundamentally broken for enterprise budget planning today.Agents managing agents means every employee becomes a manager of thousands.POC data gaps are the most underrated blocker to production deployment.Security must be designed in from the start — retrofitting is painful.Build evaluations first so you know if you're actually improving anything.Find your uniquely differentiated data and build your agentic bet there.Participants:Yannick Guillerm – Regional Manager, Sales Engineering, DatadogRay Thai – Director of Product Management, Fireworks AIAndrew Yu – Vice President of Engineering, OktaMatan-Paul Shetrit – Director of Product Management, Writer AIModerator: Carol Potts – General Manager, North America ISV Sales, AWSSee how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/
Transcribe →Ep205: AI Teammates Are Here - Asana's Multiplayer Approach to an Agentic Future
May 500:21:32Tap to summarizeAsana CPO Arnab Bose breaks down how AI agents are transforming collaborative work management with multiplayer AI teammates that any team member can coach and correct.Topics Include:Asana is a collaborative work management platform used by 170,000+ companies worldwide.The "Pyramid of Clarity" connects individual tasks all the way up to company strategy.Asana's "work graph" maps tasks, teams, projects, and portfolios in one connected system.Generative AI now converts unstructured data like emails into structured project plans.Asana integrates directly with AWS, Gemini, and Claude to automate that conversion.AI Teammates are first-party agents that take on and complete tasks inside Asana.These agents work in multiplayer mode — visible, collaborative, and team-correctable.A third AI unlock is coming: letting any external agent builder plug into Asana's interface.Asana runs entirely on AWS, including a new FedRAMP moderate GovCloud deployment.AWS Marketplace listings help customers transact faster using existing AWS credits.Arnab advises startups to bet on AWS long-term rather than chasing short-term LLM trends.His 2026 prediction: multi-agent orchestration standards will be the enterprise AI battleground.Participants:Arnab Bose – Chief Product Officer, AsanaSee how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/
Transcribe →Ep204: Hacker Mindset at Scale: Inside Detectify's AI-Powered Security Platform on AWS
Apr 2800:29:20Tap to summarizeDiscover how Detectify's hacker-DNA culture, multi-account AWS architecture, and Claude Code on Bedrock helped a lean security team deliver zero-day protection to customers before they even knew they needed it.Topics Include:Haris Kabiljagić leads cloud operations, data, and scanning at Detectify.Detectify started in 2013 as a group of ethical hackers in Stockholm.The platform continuously scans customers' attack surfaces for exploitable vulnerabilities.A global community of elite ethical hackers feeds real-world payloads into the engine.Early on, a centralized cloud team caused over 40 service disruptions monthly.A multi-account AWS strategy via Control Tower eliminated disruptions entirely.The hardest part of decentralizing wasn't technology — it was the culture shift.Cloud ops had to evolve from gatekeepers into enablers of secure, fast deployment.Detectify's architecture runs on three pillars: scalability, event-driven services, and security.MSK and Amazon MQ replaced self-hosted RabbitMQ, enabling true event-driven microservices.AWS Security Hub provides a single pane of glass for security posture visibility.When the CAPS zero-day hit, Detectify delivered a live test to customers same day.Customers logged in braced for panic — and found the threat was already handled.AI-assisted development via Claude Code on Bedrock accelerated code migration 30x.The team moved from five modules per week to 150, without sacrificing review quality.Success is now measured by speed of remediation, not volume of vulnerabilities found.A new internal scanner lets customers protect applications before they ever reach production.Detectify's roadmap: make security effortlessly native inside the pipelines teams already use.Participants:Haris Kabiljagić - Head of Developer Services, DetectifyJohan Broman – EMEA ISV, Head of Solutions Architecture, 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/
Transcribe →Ep203: Beyond Observability - How Dynatrace Uses AI to Fix Problems Before You Know They Exist
Apr 2100:25:20Tap to summarizeDynatrace's Chief Technology Strategist Alois Reitbauer explains how AI-powered observability is moving beyond monitoring to autonomously fixing software issues — and why the best AI doesn't replace human judgment, it sharpens it.Topics Include:Dynatrace helps global enterprise companies observe, optimize, and protect their software.The platform goes beyond monitoring — it takes automated action to fix issues.Business observability connects technical data to real-world operational decisions.Dynatrace has been investing in AI for 14 years, starting with root cause analysis.AI eliminates human confirmation bias when diagnosing critical system failures.Generative AI now enables Dynatrace to propose and implement code-level fixes.AI works best augmenting humans — like a GPS, not an autopilot.The Dynatrace-AWS partnership began with aligning on a shared long-term vision.Joint engineering calls and shared roadmaps made the two teams feel like one.Dynatrace experienced Amazon's famous silent document-reading meeting culture firsthand.Good partnerships require honesty, investment, and knowing when to say no.AI is maturing from an efficiency play toward genuine human augmentation.Participants:Alois Reitbauer – Chief Technology Strategist, DynatraceSee how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/
Transcribe →Ep202: Self-Driving Infrastructure - How Vercel Is Automating the Future of Web Deployment
Apr 1400:28:59Tap to summarizeVercel's VP of Engineering Lindsey Simon unpacks how AI is transforming web deployment — from self-driving infrastructure and automatic rollbacks to prompt-to-app magic and what coding will look like by 2027.Topics Include:Vercel turns a simple git push into a live URL, fastCustomers range from solo indie devs to major enterprises globallyUnder Armour, Reuters, and Polymarket all run on Vercel's platformAI agents can detect failed deployments and automatically suggest fixesVercel calls this approach "self-driving infrastructure" — a post-AI evolutionThe AI SDK lets developers write model-agnostic code across any providerV0 lets anyone generate a full app just by typing a promptThe AI Gateway provides intelligent model fallbacks and cost efficiencyVitamins vs. painkillers: Vercel only builds what customers genuinely needAI works best when code has structure, types, and tests already in placeAWS Bedrock helped Vercel scale V0 when it went unexpectedly viralVercel's AI philosophy: "let it rip" — with smart guardrails around dataWeekly "Demo Days" put every engineer in front of 200 colleagues to presentDesign is a company-wide discipline, from product UI to office signageA new AWS integration makes provisioning Aurora and DynamoDB just a few clicksParticipants:Lindsey Simon – Vice President of Engineering, VercelSee how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/
Transcribe →Ep201: Agentic AI - Business and Technical Trends with Olawale Oladehin
Apr 700:43:25Tap to summarizeAWS leader Olawale Oladehin breaks down the architectural patterns, flywheel dynamics, and human skills product teams need to win in the rapidly evolving agentic era.Topics Include:AI represents the biggest product opportunity since the invention of cloud computing.Software companies are updating AI systems faster than ever before.Engineering team roles are fundamentally changing in the agentic era.OpenAI hit a $30B run rate in under three years.The economics of building software have permanently and radically changed.AI-native startups are reaching $100M revenue with fewer than 50 people.Your company's best product may not yet be on the roadmap.The biggest AI white spaces are automation, healthcare, sales, and finance.Disruption isn't the right frame — recalibration is.Existing customers, distribution, and domain expertise are structural advantages.Five differentiators: data, workflow depth, domain expertise, feedback loops, and trust.Every quarter of delay lets competitors complete their flywheel ahead of you.Six flagship AI models released in just 25 days recently.Open-weight models are rapidly closing the gap with frontier models.Model modularity is now essential — today's frontier is tomorrow's commodity.Durable truths matter more than chasing every new technology shift.Speed, integration depth, and compounding trust are enduring customer priorities.Agentic workloads consume 50K tokens versus 1–2K for simple chatbots.Multi-agent orchestration mirrors the shift from monoliths to microservices.Observability, guardrails, and compliance must be pulled up, not pushed down.Vertical specialization will consistently outperform horizontal scale over time.The World Economic Forum ranks AI literacy as the fastest-rising workforce skill.As automation grows, human skills like empathy and creativity matter more.AI is compressing the PM workflow from weeks of research to two hours.Culture, change leadership, and continuous learning are now competitive advantages.Participants:Olawale Oladehin – Managing Director, NAMER Technology Segments, 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/
Transcribe →Ep200: Scaling and Monetizing AI-Powered Products with ServiceNow, TwelveLabs and AWS
Mar 3100:44:32Tap to summarizeExecutives from ServiceNow, TwelveLabs, and AWS share unfiltered lessons on organizational change, data strategy, and best practices for scaling AI products worldwide.Topics Include:Three panelists explore scaling and monetizing agentic AI products.ServiceNow built entirely new prompt engineering roles from scratch.Evaluations-first culture replaced traditional QA — a major mindset shift.TwelveLabs' "Tokens Never Sleep" initiative broke down team AI resistance.Unlimited token usage revealed how underused AI actually is.Rich: the competitive window for acting on AI is closing.ServiceNow's DART program governs customer data for evaluation only.Enterprise data governance is fundamentally different from consumer companies.Disorganized internal data breaks agentic systems — structure comes first.Your data, not your model, is your competitive advantage.Krish's surprise: enterprise governance made model training nearly impossible.Jae: powerful AI tools erode human opinions faster than expected.Rich: boardroom-to-shop-floor AI adoption is unlike any previous wave.Customers began favoring velocity after watching competitors win with it.ServiceNow shipped agents at 20% resolution — then iterated upward.Focus early agents on reversible, low-risk, two-way-door actions.AWS tracks internal AI adoption in a structured weekly mechanism.TwelveLabs' two models power sophisticated video RAG workflows at scale.A Hollywood studio cut full episodes to four minutes using them.Voice agent worked perfectly in demos — broke immediately in production.Customers now measure how fast a product is getting smarter.Future-proofing infrastructure is every product leader's top anxiety today.MCP and A2A enable message-passing — but deeper problems remain.Semantic mismatch, agent identity, and trace governance remain unsolved.Tiered autonomy, trust, and data foundations define who ultimately wins.Participants:Krish Ganapathy | VP, AI Science, Architecture and Tools, ServiceNowJae Lee | CEO & Co-Founder, TwelveLabsRich Geraffo | Vice President & Managing Director, North America, AWSModerator: Connie de Lange | Marketing Director, North America, AWSSee how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/
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