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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.

From alert to root cause in one minute - how PagerDuty built autonomous incident response on Amazon Bedrock, and the future of triage and trust. Topics Include:PagerDuty's agents must perform during 2am outages — stakes are highSoftware shipping accelerated dramatically; production environments largely did notA 9:30pm slowdown traced to a race condition solved two years earlierThe fix was documented — but the context wasn't at handPagerDuty Advance ships four agents: SRE, Scribe, Shift, InsightsWhy four, not one? Focus and predictability in non-deterministic systemsSaurabh Shanbhag: Bedrock is far more than a model serviceZero data retention, PrivateLink, TLS — why enterprises pick BedrockFrontier models everywhere burns tokens; classify, route, distill, fine-tuneSRE agent triages alerts before you even join the callOne minute to root cause — context beat raw intelligenceHuman surfaces versus machine surfaces: MCP and CLI move fastest"The model eats the harness" — every upgrade invalidates foundational componentsFeeding agents everything failed; compartmentalised investigation threads work betterNew York Life's three stages of trust, and the seatbelt override that wasn't Participants:Tom Hogarty - Senior Director Product Management, PagerDutySaurabh Shanbhag – Sr Partner Solution Architect, Amazon Web Services See how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/

Domo and AWS reveal how AI agents freed sales reps from 20 hours of weekly busywork, turning scattered data into real-time coaching and forecasting.Topics Include:Domo and AWS teams introduce today's session on AI agents in sales.Topic: using AI agents to transform sales operations, from insight to action.IT teams increasingly asked to turn data into actionable outcomes, not just access.Domo's CRO wanted AI agents to boost sales rep efficiency significantly.Reps act like "archaeologists," digging through scattered systems for basic context.This digging eats roughly 20 hours weekly, half of reps' time.Goal: personal AI agent per rep, understanding their book of business.Live demo begins: agent app surfaces urgent items needing attention.Agent tracks deal milestones, timelines, and forecasts from call and email data."Deal coach" feature grades rep performance and suggests next actions.Agent tone can be tuned from gentle to direct, aiding tough feedback.Architecture overview begins: building an AI-ready data foundation first.Data from CRM, calls, and emails flows into a cloud warehouse.Two agents built: automated deal analysis and personalized deal coach.Agents write insights back to CRM, preserving human edit control.Recipe: build foundation, activate with agents, distribute to people.Governance must be embedded throughout, not bolted on afterward.Second example: Fogo do Chão uses AI to analyze restaurant reviews.AWS architecture explained: Domo runs on Bedrock, defaulting to Anthropic models.Q&A: sales team adoption was immediate and enthusiastic post-rollout.Participants:Jason Longhurst – Head of Product Marketing, DomoAman Tiwari - Sr Solutions Architect, ISV, Amazon Web Services See how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/

Curious how AI can query your enterprise data without moving it or making things up? AWS and Teradata break down a trustworthy analyst agent built for real production use.Topics Include:Neha Wadhera (AWS) introduces Trinath Yarlagadda and the Teradata Analyst AgentEnterprise AI data prep is costly, stalling most orgs at experimentationAgent answers plain-English questions via traceable SQL, zero data movementBarrier removal drives 3.7x ROI and 40% productivity gainsHealthcare demo setup: hospital COPD readmissions, ~$10K cost per incidentFour design principles: traceability, no data movement, deterministic-first, governance as codeMain orchestrator agent plans, writes SQL, calls Teradata MCP serverComplex questions escalate to a context-isolated data scientist agentBuilt on Claude Agent SDK, running Bedrock Claude Sonnet/Haiku/OpusLive demo: COPD readmission rates explored through iterative agent reasoningDelegation demo: data scientist agent runs in-database analysis, surfaces factorsPre/post tool hooks log every step and cost to CloudWatchAgent hosted on Amazon Bedrock AgentCore, fully serverless and scalableAgentCore delivers runtime, memory, identity, and observability out of the boxLessons learned: guardrails first, deterministic ops, multi-agent registry, ongoing evaluationParticipants:Trinath Yarlagadda – Principal Solution Architect – Agentic AI, TeradataNeha Wadhera – Sr Solutions Architect, Amazon Web Services See how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/

Learn how Vercel's "self-driving infrastructure" vision pairs with AWS databases to eliminate backend friction, securely cutting Aurora Serverless creation time from minutes to seconds.Topics Include:Hedieh Zandi (Vercel) and Manbeen Kohli (AWS) introduce prompt-to-production sessionVercel powers 18 million developers, maintains Next.js and AI SDKVercel's agentic infrastructure runs on AWS Lambda, CloudFront, and S3AI now generates frontend, APIs, and workflows for small teamsBackend friction remains: credentials, provisioning, database configuration still hardVercel envisions "self-driving infrastructure" that adapts automatically to appsNew AWS partnership brings native Aurora DSQL and Postgres integrationManbeen explains databases now built into Vercel Marketplace and v0Aurora Serverless database creation sped up from minutes to secondsAurora Postgres, DynamoDB, and DSQL scale prototypes without rewritesPre-configured templates help builders start RAG or shopping AI appsDatabase security uses OIDC and IAM tokens, no stored passwordsAWS chosen for agents: low latency, autonomy, one-click simplicityskills.sh gives agents reusable instructions, mirrors AWS Kiro's "powers"v0 lets users build full-stack apps using natural language promptsv0 uses Bedrock models and deploys directly on Vercel infrastructureLive demo: v0 builds restaurant app, provisions database, adds Stripe checkoutDemo ends at AWS console; Rauch quote and hackathon close sessionParticipants:Hedieh Zandi - Product Lead, VercelManbeen Kohli - Director of Product Management, Aurora and RDS Databases, Amazon Web Services See how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/

Kaltura's Ruthie Eisenberg and Yair Neumann reveal how the video giant is reinventing itself as an agentic digital experience company built on AI avatars and hyper-personalized content.Topics Include:Kaltura founded 2006, went public on NASDAQ in 2021.Kaltura reinventing itself from video company to agentic digital experience company.Shift from static content delivery to hyper-personalized conversational experiences.Partners and customers now demand intelligence, not just video infrastructure.Kaltura's mission: powering agentic experiences across customer and learner journeys.AWS co-sell motion strengthened as Kaltura runs on AWS AI infrastructure.Camille used a Kaltura avatar to scale her own presentations.Most enterprise websites bury content behind thousands of static links.Kaltura builds personalised web pages on the fly, in real time.Over 80% of content users see is surfaced for the very first time.Acquisitions of eSelf.ai and PassFactory complete Kaltura's agentic content flywheel.PassFactory answers: what should this specific person see next?eSelf.ai enables multimodal conversational avatars that guide users emotionally.20 years of behavioral data underpins Kaltura's content intelligence advantage.GPU scarcity and compute costs shape every AI architecture decision Kaltura makes.Kaltura optimises model tiers — strongest for planning, lighter models for execution.Fidelity, speed, and cost form a constant triangle in every AI product decision.Go-to-market and product teams now work closer together than ever before.Pricing shifting from seat-based SaaS to consumption and outcome-based models.Kaltura co-creating pricing frameworks with customers across different verticals.Internal product agent now handles research, stories, and data analysis autonomously.Small two-to-three person squads move fastest in the current AI environment.Yair's advice: fail at least once a week, succeed once a quarter.Kaltura scaled its CEO via avatar for a live investor earnings call.Ruthie's advice: keep the customer at the centre of every single decision.Participants:Ruthie Eisenberg – Vice President, Strategic Partnerships, KalturaYair Neumann – Senior Vice President of Product, KalturaKamil Davidov – Sales Leader Israel ISV-BizApps, Amazon Web ServicesJohan 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/

With 250,000 customers and $1.2B in revenue, Monday.com's CPTO explains why they threw out their roadmap and rebuilt everything around agentic AI.Topics Include:Daniel Lereya joined Monday.com when it had just 30 people and five engineers.He grew the R&D org from five engineers to roughly 900 over a decade.Three years ago Daniel became Monday.com's first ever CPTO.Monday.com initially approached AI by adding small features across the product.They called this early phase "sprinkling AI dust" — helpful but not transformative.A pivotal board meeting made Daniel realise AI hadn't changed Monday's core value.Monday.com decided to rethink its mission from first principles around AI.The new mission: AI agents that actually execute work, not just manage it.AI gives businesses an "infinite workforce" regardless of company size.Agents can now do hyper-personalised work at a scale humans simply cannot.Monday's platform puts agents at the centre, replacing boards and dashboards.Shared context and human-in-the-loop handoffs make their agents uniquely powerful.Monday ran an "AI month" — pausing the entire 900-person builder org to transform.The month rebuilt team mindset and energy, reminding staff of early startup days.Monday also ran an "agentic week" where every department built their own agents.Finance built agents to automatically match incoming payments to customer accounts.Scaling AI adoption internally remains the biggest challenge across businesses today.Monday introduced "effective AI" — balancing capability with cost efficiency.They acquired voice AI startup One AI to add specialised model capabilities.On pricing, Monday shifted to a hybrid seats-plus-AI-credits consumption model.Participants:Daniel Lereya – Chief Product and Technology Officer, Monday.comKamil Davidov – Sales Leader Israel ISV-BizApps, Amazon Web ServicesJohan 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/

PagerDuty SVP Rukmini Reddy explains why AI is making software operations exponentially more complex — and why the companies that learn and recover fastest will be the ones that win.Topics Include:PagerDuty powers critical digital operations for enterprises and AI-native companies.Founded by early AWS employees who experienced always-on system failures firsthand.The platform evolved from simple alerting into a full operational intelligence platform.Complexity exploded with microservices, cloud-native infrastructure, and multi-cloud environments.Reliability must be a core value — not an operational afterthought.PagerDuty's culture champions the customer above everything else.Employee recognition extends beyond sales to celebrate the whole business.AI is accelerating software creation but making operations far more complex.AI fails differently — silently, unpredictably, with a much larger blast radius.Enterprises should leverage their operational history as a competitive AI asset.AI-native companies must build operational resilience early, not bolt it on later.The winners won't build fastest — they'll learn and recover fastest.Participants:Rukmini Reddy – Senior Vice President of Engineering, PagerDutySee how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/

From 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/

Find 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/

Greg 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/