AWS for Software Companies Podcast

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 session
Vercel powers 18 million developers, maintains Next.js and AI SDK
Vercel's agentic infrastructure runs on AWS Lambda, CloudFront, and S3
AI now generates frontend, APIs, and workflows for small teams
Backend friction remains: credentials, provisioning, database configuration still hard
Vercel envisions "self-driving infrastructure" that adapts automatically to apps
New AWS partnership brings native Aurora DSQL and Postgres integration
Manbeen explains databases now built into Vercel Marketplace and v0
Aurora Serverless database creation sped up from minutes to seconds
Aurora Postgres, DynamoDB, and DSQL scale prototypes without rewrites
Pre-configured templates help builders start RAG or shopping AI apps
Database security uses OIDC and IAM tokens, no stored passwords
AWS chosen for agents: low latency, autonomy, one-click simplicity
skills.sh gives agents reusable instructions, mirrors AWS Kiro's "powers"
v0 lets users build full-stack apps using natural language prompts
v0 uses Bedrock models and deploys directly on Vercel infrastructure
Live demo: v0 builds restaurant app, provisions database, adds Stripe checkout
Demo ends at AWS console; Rauch quote and hackathon close session

Participants:
Hedieh Zandi - Product Lead, Vercel
Manbeen 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, Kaltura
Yair Neumann – Senior Vice President of Product, Kaltura
Kamil Davidov – Sales Leader Israel ISV-BizApps, Amazon Web Services
Johan Broman – EMEA ISV Head of Solutions Architecture, 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/

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.com
Kamil Davidov – Sales Leader Israel ISV-BizApps, Amazon Web Services
Johan Broman – EMEA ISV Head of Solutions Architecture, 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/

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, PagerDuty

See 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 Data

See how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/