AWS for Software Companies Podcast

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/

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 Labs

See 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 AI

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