AWS for Software Companies Podcast

Discover 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, Detectify
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/

Dynatrace'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, Dynatrace

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

Vercel'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, fast
Customers range from solo indie devs to major enterprises globally
Under Armour, Reuters, and Polymarket all run on Vercel's platform
AI agents can detect failed deployments and automatically suggest fixes
Vercel calls this approach "self-driving infrastructure" — a post-AI evolution
The AI SDK lets developers write model-agnostic code across any provider
V0 lets anyone generate a full app just by typing a prompt
The AI Gateway provides intelligent model fallbacks and cost efficiency
Vitamins vs. painkillers: Vercel only builds what customers genuinely need
AI works best when code has structure, types, and tests already in place
AWS Bedrock helped Vercel scale V0 when it went unexpectedly viral
Vercel's AI philosophy: "let it rip" — with smart guardrails around data
Weekly "Demo Days" put every engineer in front of 200 colleagues to present
Design is a company-wide discipline, from product UI to office signage
A new AWS integration makes provisioning Aurora and DynamoDB just a few clicks

Participants:
Lindsey Simon – Vice President of Engineering, Vercel

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

AWS 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 Services

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

Executives 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, ServiceNow
Jae Lee | CEO & Co-Founder, TwelveLabs
Rich Geraffo | Vice President & Managing Director, North America, AWS
Moderator: Connie de Lange | Marketing Director, North America, AWS

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