AWS for Software Companies Podcast

Latest Episodes:

Ep107: Cloud-Scale Security Monitoring – How Panther and AI are Revolutionizing Cybersecurity Jun 11, 2025

Show notes

Chief Architect Russell Leighton discusses how Panther's cloud platform revolutionizes security operations by treating detections as Python code and AI enabled alert vetting turning responses from hours into minutes.

Topics Include:

Panther is a cloud security monitoring tool (cloud SIEM)
Works at massive scale, more cost-effective than legacy systems
Key differentiator: "detections as code" written in Python
Brings software engineering best practices to security operations
Enables unit testing and version control for security detections
Recently adopted generative AI to improve security workflows
SOC burnout is renowned due to tedious ticket processing
AI has intelligence of security engineer, works much faster
Example: Alert shows "Russ Leighton removed branch protection"
Old way: Manual log analysis, checking user profiles manually
Takes hours of squinting at detailed log data
New AI way: Automatic vetting happens in minutes
AI checks user profile in Okta or IDP
Determines engineer status, assesses typical behavior patterns
Provides risk assessment based on historical alert data
Low risk for engineers, high risk for unusual users
Example: HR person accessing production code is escalated
Customer quote: Takes vetting "from hours to seconds"
Panther customers get dedicated AWS accounts for security
Company can't see customer data, only self-reported metrics
AI provides summaries, risk assessments, timelines, visualizations
Also suggests remediations like human security engineer would
Initial concerns about putting AI in production environment
Customer feedback exceeded expectations with feature requests
AWS Bedrock integration addresses customer security concerns
Uses Anthropic Claude as base LLM through Bedrock
Customers can enable additional Bedrock guardrails independently
AI transparency prevents hallucination concerns through explanations
Claude's extended thinking mode shows reasoning process
AI visualizes thinking with flowcharts explaining decision process

Participants:

Russell Leighton – Chief Architect, Panther

Further Links:

Website: Panther.com
AWS Marketplace

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

Ep106: Building Secure and Agile AI Agents at Scale with Anthropic and AWS Jun 10, 2025

Show notes

Security leaders from Anthropic and AWS discuss how agentic AI is transforming cybersecurity functions to autonomously handle everything from code reviews to SOC operations.

Topics Include:

Agentic AI differs from traditional AI through autonomy and agency
Traditional AI handles single workflow nodes, agents collapse multiple steps
Higher model intelligence enables understanding of broader business contexts
Agents make intelligent decisions across complex multi-step workflows processes
Enterprise security operations are seeing workflow consolidation through GenAI
Organizations embedding GenAI directly into customer-facing production applications
Software-as-a-service transitioning to service-as-software through AI agents
Securing AI requires guardrails to prevent hallucinations in applications
New vulnerabilities appear at interaction points between system components
Attackers target RAG systems and identity/authorization layers instead
LLMs hallucinate non-existent packages, attackers create malicious honeypots
Governance frameworks must be machine-readable for autonomous agent reasoning
Amazon investing in automated reasoning to prove software correctness
Anthropic uses Claude to write over 50% of code
Automated code review systems integrated into CI/CD pipelines
Security design reviews use MITRE ATT&CK framework automation
Low-risk assessments enable developers to self-approve security reviews
40% reduction in application security team review workload
Anthropic eliminated SOC, replaced entirely with Claude-based automation
IT support roles transitioning to engineering as automation replaces frontline
Compliance questionnaires fully automated using agentic AI workflows
ISO 42001 framework manages AI deployment risks alongside security
Executive risk councils evaluate AI risks using traditional enterprise processes
AWS embeds GenAI into testing, detection, and user experience
Finding summarization helps L1 analysts understand complex AWS environments
Amazon encourages teams to "live in the future" with AI
Interview candidates expected to demonstrate Claude usage during interviews
Security remains biggest barrier to enterprise AI adoption beyond POCs
Virtual employees predicted to arrive within next 12 months
Model Context Protocol (MCP) creates new supply chain security risks

Participants:

Jason Clinton – Chief Information Security Officer, Anthropic
Gee Rittenhouse – Vice President, Security Services, AWS
Hart Rossman – Vice President, Global Services Security, AWS
Brian Shadpour – GM of Security and B2B Software Sales, AWS

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

Ep105: Transforming B2B - How Spryker Powers Complex B2B Commerce with AWS Jun 09, 2025

Show notes

Spryker’s Chief Product Officer, Elena Leonova, discusses the Spryker Business Intelligence platform and how working with AWS as a strategic advisor unlocked deeper opportunities for transformative growth.

Topics Include:

Elena Leonova introduces Spryker as digital commerce platform
Spryker focuses on sophisticated B2B commerce transactions
Traditional industries: manufacturing, industrial goods, med tech
Customers sell complex equipment like MRI machines, tractors
Products are custom-built to order through procurement processes
Extensive negotiation and aftermarket servicing are required
Competitors focus on fashion, food - not complex equipment
Spryker exclusively hosted on AWS cloud infrastructure
AWS partnership enables new capabilities and customer innovation
Business intelligence tools and AI capabilities now available
Ricoh example: global manufacturer of industrial-grade printers
Ricoh sells through dealers and distributors worldwide
S-Diverse: new automotive software marketplace partnership platform
Connects automotive manufacturers with embedded software producers
Spryker Business Intelligence powered by Amazon QuickSight launched
Commerce becoming more intelligent than traditional repeat purchases
Complex equipment buyers don't purchase MRI machines weekly
Platform provides insights into customer portal navigation patterns
Combines commerce data with search, CRM, competitive intelligence
Helps merchants identify revenue optimization signals from noise
Business intelligence integrated directly within Spryker platform
Customers should evaluate platform's future scalability and flexibility
Revenue optimization requires understanding what metrics to improve
Easy-to-use data analysis prevents information overload problems
QuickSight's GenAI capabilities enable faster executive decision-making
AWS partnership provided cost optimization and innovation confidence
Elena initially viewed AWS as just hosting provider
Building shared vision with AWS unlocked deeper collaboration
AWS became trusted advisor for strategy and partnerships
Generative AI enables multi-persona communication across customer types

Participants:

Elena Leonova – Chief Product Officer, Spryker

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

Ep104: Partnership in Innovation - How ActiveFence and AWS are De-risking AI Jun 04, 2025

Show notes

ActiveFence CEO Noam Schwartz discusses how his company evolved from protecting platforms against user-generated harmful content to helping companies deploy public-facing AI safely at scale.

Topics Include:

Noam Schwartz introduces himself as ActiveFence CEO
Former intelligence officer specializing in open source intelligence
Mission: protect online experiences for everyone everywhere
Online platforms constantly hammered by various attacks
Attacks include cybersecurity, abuse, hate speech, spam
Companies playing endless whack-a-mole game with violations
Need scalable solution that works across languages/formats
Developed enterprise-grade technology for sophisticated companies
Amazon became customer and great partner early on
Generative AI introduction changed the game completely
LLMs non-deterministic unlike traditional programmed chatbots
Same input produces different outputs each time
AI deployed in customer support, healthcare, airlines
New risks when models speak on company's behalf
One bad output creates legal and reputational damage
Companies need to deploy public-facing AI safely
Transition affects healthcare, finance, gaming, government sectors
Building on years of user-generated content expertise
No specific ChatGPT moment triggered their AI pivot
ActiveFence was AI company since day one
Model companies like Amazon, Nvidia asked for help
Realized their expertise perfectly suited for AI safety
Staying on top of AI developments is impossible
Focus on customer adoption, not every new release
Main enterprise challenge is trusting AI technology
Unrealistic expectations for 100% accuracy from AI
Most companies will license existing models, not build
Security solutions remain independent like traditional cybersecurity

Participants:

Noam Schwartz – CEO and Co-Founder, ActiveFence
Ofer Oringher – Software and Technology Account Manager, AWS

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

Ep103: Supercharging Security with GenAI – Best Practice Sharing with Sonrai Security Jun 02, 2025

Show notes

Jeff Moncrief discusses Sonrai Security's Cloud Permissions Firewall, and the best practices for using AI-powered summaries and orchestration to ensure security at all points.

Topics Include:

Jeff Moncrief introduces Sonrai Security and Cloud Permissions Firewall
Focus on achieving least privilege access in AWS quickly
Lightweight orchestration layer secures IAM from inside out
Eliminates need to write hundreds of individual policies
Customers struggle with identity risk in CNAP/CSPM tools
Generative AI adoption driving top security use cases
Bedrock and AI agents mentioned daily by customers
Product managers should consider underlying platform security risks
AI models have control over infrastructure they run on
Identity is fundamental infrastructure enabling AWS AI models
Sonrai uses Bedrock capability inside Cloud Permissions Firewall
Just-in-time access provides temporary, time-boxed AWS access
Bedrock generates session summaries from audit logs automatically
Plain English insights show what happened during sessions
Session summaries improve audit compliance and incident response
Customer with 1000 accounts manually deployed service controls
Friday afternoon deployment caused very bad weekend disaster
Policy inheritance issues broke child accounts and OUs
Planning and orchestration essential for scaling AI security
Sonrai platform built 100% cloud-native on AWS
Coordinates service control policies and resource control policies
Just-in-time access relies on IAM Identity Center
Participates in ISV Accelerate and AWS Marketplace
Security best practices start with identity as foundation
"Hackers don't hack, they just log in" philosophy
Eliminate standing privileges with just-in-time access patterns
Restrict AI services by user, location, and account
Review over-permissioned or inactive third-party vendor access
Actionable insights through useful logging and AI summarization
Future focus on protecting new services and permissions

Participants:

Jeff Moncrief – Field CTO & Director of Sales Engineering, Sonrai Security

Links:

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

Ep102: 500 Billion Connected Devices: Intel's Investment in improving Enterprise AI May 29, 2025

Show notes

Akanksha Bilani of Intel shares how businesses can successfully adopt generative AI with significant performance gains while saving on costs.

Topics Include:

Akanksha runs go-to-market team for Amazon at Intel
Personal and business devices transformed how we communicate
Forrester predicts 500 billion connected devices by 2026
5,000 billion sensors will be smartly connected online
40% of machines will communicate machine-to-machine
We're living in a world of data deluge
AI and Gen AI help make data effective
Goal is making businesses more profitable and effective
Various industries need Gen AI and data transformation
Intel advises companies as partners with AWS
Three factors determine which Gen AI use cases adopt
Factor one: availability and ease of use cases
How unique and important are they for business?
Does it have enough data for right analytics?
Factor two: purchasing power for Gen AI adoption
70% of companies target Gen AI but lack clarity
Leaders must ensure capability and purchasing power exist
Factor three: necessary skill sets for implementation
Need access to right partnerships if lacking skills
Intel and AWS partnered for 18 years since inception
Intel provides latest silicon customized for Amazon services
Engineer-to-engineer collaboration on each processor generation
92% of EC2 runs on Intel processors
Intel powers compute capability for EC2-based services
Intel ensures access to skillsets making cloud alive
AWS services include Bedrock, SageMaker, DLAMIs, Kinesis
Performance is the top three priorities for success
Not every use case requires expensive GPU accelerators
CPUs can power AI inference and training effectively
Every GPU has a CPU head node component

Participants:

Akanksha Bilani – Global Sales Director, Intel

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

Ep101: Beyond Chat - How Asana and Amazon Q Are Embedding AI Into Enterprise Workflows May 27, 2025

Show notes

Victoria Chin of Asana and Michael Horn of AWS demonstrate how Amazon Q integrates with Asana to enable AI-powered workflows while dramatically reducing manual work and improving cross-functional collaboration.

Topics Include:

Victoria Chin introduces herself as Asana's CPO Chief of Staff
Michael Horn from AWS discusses customer feedback on generative AI
AI agents limited by quality of data pulled into them
Amazon Q Business created to analyze information and take action
Hundreds of customers using Q Business across various industries daily
AWS hosts most business applications, ideal for AI journey
Amazon Q has most built-in, managed, secure data connectors available
Q Index creates comprehensive, accessible index of all company data
Security permissions automatically pulled in, no manual configuration needed
Supports both structured and unstructured data from multiple sources
Victoria returns to discuss Asana's integration with Q Index
Billions invested in integrations, but usage still lags behind
Teams switch between apps 1000 times daily, missing connections
Root problem: no reliable way to track who/what/when/why
Content platforms store work but don't manage or coordinate
Asana bridges content and communication for effective teamwork scaling
AI disrupting software, but questions remain about real value
Software must provide structured framework to guide LLMs effectively
AI needs data AND structure to separate signal from noise
Asana Work Graph maps how work actually gets done organizationally
Work Graph visualized as interconnected data, not rows and columns
Most strategic work is cross-functional, requiring multiple teams collaborating
Traditional integrations require manual setup and knowing when to use
Q Index gives Asana access to 40+ different data connectors
Users can ask questions, get answers with cross-application context
AI Studio enables no-code building of workflows with AI agents
Product launch example shows intake, planning, execution, and reporting stages
AI can surface relevant documents, research, and updates automatically
Chat is tip of iceberg; real power comes from embedded workflows
Integration evolves from feature-level to AI-powered product-level connections

Participants:

Victoria J. Chin – Chief of Staff / Product Strategy, AI, Asana
Michael Horn – Principal Head of Business Development – Artificial Intelligence & Machine Learning, AWS

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

Ep100: The Power of ISV Community - Celebrating 100 Episodes with ISV Customers and AWS Leaders May 22, 2025

Show notes

AWS leaders commemorate the podcast's 100th episode while looking ahead to expanded coverage of technology partners and continued focus on generative AI, modern data strategies, agentic AI solutions and more!

Topics Include:

Episode 100 celebrates milestone of AWS software companies podcast
Weekly podcast shares ISV stories, best practices, guidance
Today features AWS leader thoughts on ISV community
Arym Diamond heads North America data and AI sales
Specialist team helps win deals, create happy customers
ISV customers do cutting-edge work on AWS platform
ISVs create force multiplier effect for entire company
Building community through podcast video and audio content
Kristen Backeberg leads global ISV partner marketing at AWS
Podcast featured 157 ISV leaders from 121 companies
Reached over 30,000 listeners across 90+ countries worldwide
ISV partners drive cloud innovation across all industries
AWS supports growth from startups to enterprise leaders
APN network designed to help partners succeed, scale
Olawale Oladehin directs ISV solutions architecture in North America
Podcast shares customer insights, journeys, and innovations
AWS technology continues evolving to meet customer needs
Carol Potts leads North America ISV sales at AWS
Podcast started less than two years ago
First episode titled "Data the Engine for Growth"
Customer obsession drives everything AWS does for ISVs
Deep collaboration focused on joint ISV success partnerships
Vishal Sanghvi heads ISV marketing for North America
ISVs face pressure delivering products at generative AI pace
Modern data strategy foundational for ISV product success
Favorite episodes include Snowflake, Wiz, Coupang discussions
AWS offers programs for every ISV persona type
Future episodes focus on generative AI, cybersecurity, data
Agentic AI becoming important for production phase evolution
Podcast expanding scope to include technology partners

Participants:

Kristen Backeberg – Director, Global ISV, Solutions Enterprise and Alliance Partner Marketing, Amazon Web Services
Arym Diamond – Director, US ISV Specialists, Amazon Web Services
Olawale Oladehin – Director, ISV, Solutions Architecture, North America, Amazon Web Services
Carol Potts – GM, ISV Sales Segment, North America, Amazon Web Services
Vishal Sanghvi - Head of ISV Field Marketing, North America, 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/

Ep099: Marketing Transformed: Reimagining Advertising and MarTech with Amazon Bedrock May 13, 2025

Show notes

Executive leaders from UneeQ and Zeta Global discuss the revolutionary impact of AI technologies that enable enhanced customer experiences and improved sales performances.

Topics Include:

Dave Cristini introduces panel on AI in advertising and marketing.
Panel explores personalized experiences at scale with privacy focus.
UneeQ creates AI-powered digital humans for brand interactions.
Zeta Global uses AI to optimize customer messaging.
LLMs combined with traditional ML empowers marketers to create models.
Marketers can now build models without needing data scientists.
AI agents integrated into systems can take action, not just respond.
Agent chaining orchestrates sophisticated marketing actions automatically.
AWS Bedrock provides tools to shape AI marketing future.
Hyper-personalization becoming more achievable through AI automation.
Ethics requires authenticity in brand AI representation.
Transparency about data usage builds customer trust.
Win-win approach: AI should augment teams, not just reduce costs.
Integration difficulties remain a major challenge for AI implementation.
AI agents have limited context windows and memory.
Solution: Create specialized agents with persistent viewpoints.
Companies need strong integration capabilities before implementing AI.
Privacy regulations impact AI use in global marketing.
Highly regulated industries require careful AI implementation strategies.
Generative AI creates compliance challenges with unpredictable outputs.
Digital humans eliminate judgment, revealing new customer insights.
Banking clients discovered customers didn't understand financial terminology.
Zeta improved onboarding with AI agents for data mapping.
AI data mapping increased NPS scores and accelerated monetization.
CMOs and CIOs increasingly collaborating on AI initiatives.
Tension exists between marketing (quick wins) and IT (security).
Strategic alignment with approved infrastructure enables scaling AI solutions.
CEOs have critical role in aligning AI goals across departments.
Internal AI use case: practicing sales with digital humans.
Sales teams achieved 500% higher sales through AI role-playing.

Participants:

Danny Tomsett – Chief Executive Officer, UneeQ
Roman Gun – Vice President, Product, Zeta Global
David Cristini – Director, ISV Sales, North America – Business Applications, AWS

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

Ep098: From BI to Gen AI: A CTO's Journey Through Data Evolution May 07, 2025

Show notes

Ash Pembroke, Portfolio CTO of Caylent, discusses the critical balance of data accuracy in the era of Gen AI for the benefit of boosting innovation.

Topics Include:

Ash Pembroke, Portfolio CTO of Caylent, self-identifies as a "recovering data scientist."
Caylent is an AWS native services company.
Data quality remains an issue despite Gen AI.
Contrasts legalism versus mysticism in data quality.
Legalism: accurate data when applications need it.
Mysticism: insights that help decision-making.
Traditional data foundations approach is being challenged weekly.
Gen AI developments force rethinking of solution architectures.
Teams share solutions through giant Slack threads.
Example: Vector databases questioned after model context protocol.
Still do traditional data assessments, but stay flexible.
Integration and data processing constantly get abstracted.
Data strategy equals architecture strategy equals business strategy.
Traditional approach: standardize data across engineering teams.
New approach: allow business users to innovate.
Bring valuable techniques back to the organization.
Case study: North Sea wind turbine alerts.
Initially seen as data quality issue, revealed new predictive failure signal.
Gen AI enables local experimentation by business users.
Blurring lines between enterprise enablement and software building.
BrainBox AI case study: energy optimization across buildings.
Architecture decisions impact ability to scale products.
Work with business edges rather than looking for patterns.
Gen AI can process information from these working groups.
Think about data as a product, not asset.
Redimensionalize dependencies across your organization.
Now's a good time to attack data quality.
New tools help visualize complexity across organizations.

Participants:

· Ash Pembroke – Portfolio CTO, Caylent

See 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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