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 – Head of North America Data & AI Sales, 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 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/

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/

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/

New Relic's Head of AI and ML Innovation, Camden Swita discusses their four-cornered AI strategy and envisions a future of "agentic orchestration" with specialized agents.

Topics Include:

• Introduction of Camden Swita, Head of AI at New Relic.
• New Relic invented the observability space for monitoring applications.
• Started with Java workloads monitoring and APM.
• Evolved into full-stack observability with infrastructure and browser monitoring.
• Uses advanced query language (NRQL) with time series database.
• AI strategy focuses on AI ops for automation.
• First cornerstone: Intelligent detection capabilities with machine learning.
• Second cornerstone: Incident response with generative AI assistance.
• Third cornerstone: Problem management with root cause analysis.
• Fourth cornerstone: Knowledge management to improve future detection.
• Initially overwhelmed by "ocean of possibilities" with LLMs.
• Needed narrow scope and guardrails for measurable progress.
• Natural language to NRQL translation proved immensely complex.
• Selecting from thousands of possible events caused accuracy issues.
• Shifted from "one tool" approach to many specialized tools.
• Created routing layer to select right tool for each job.
• Evaluation of NRQL is challenging even when syntactically correct.
• Implemented multi-stage validation with user confirmation step.
• AWS partnership involves fine-tuning models for NRQL translation.
• Using Bedrock to select appropriate models for different tasks.
• Initially advised prototyping on biggest, best available models.
• Now recommends considering specialized, targeted models from start.
• Agent development platforms have improved significantly since beginning.
• Future focus: "Agentic orchestration" with specialized agents.
• Envisions agents communicating through APIs without human prompts.
• Integration with AWS tools like Amazon Q.
• Industry possibly plateauing in large language model improvements.
• Increasing focus on inference-time compute in newer models.
• Context and quality prompts remain crucial despite model advances.
• Potential pros and cons to inference-time compute approach.

Participants:

• Camden Swita – Head of AI & ML Innovation, Product Management, New Relic

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

Jon Yoo, CEO of Suger, shares how his company automates the complex & challenging workflows of selling software through cloud marketplaces like AWS.

Topics Include:

• Jon Yoo is co-founder/CEO of Suger.
• Suger automates B2B marketplace workflows.
• Handles listing, contracts, offers, billing for marketplaces like AWS.
• Co-founder previously led Confluent's marketplace enablement product.
• Confluent had 40-50% revenue through cloud marketplaces.
• Required 10-20 engineers working solely on marketplace integration.
• Engineers prefer core product work over marketplace integration.
• Product/engineering leaders struggle with marketplace deployment requirements.
• Marketplace customers adopt without marketing, creating unexpected management needs.
• Version control is challenging for marketplace-deployed products.
• License management through marketplace creates engineering challenges.
• Suger helps sell, resell, co-sell through AWS Marketplace.
• Marketplace integration isn't one-time; requires ongoing maintenance.
• Business users constantly request marketplace automation features.
• Suger works with Snowflake, Intel, and AI startups.
• Data security concerns drive self-hosted AI deployments.
• AI products increasingly deploy via AMI/container solutions.
• AI products use usage-based pricing, not seat-based.
• Usage-based pricing creates complex billing challenges.
• AI products are tested at unprecedented rates.
• Two deployment options: vendor cloud or customer cloud.
• SaaS requires reporting usage to marketplace APIs.
• Customer-hosted deployment simplifies some billing aspects.
• Marketplaces need integration with ERP systems.
• Version control particularly challenging for AI products.
• Companies need automated updates for marketplace-deployed products.
• License management includes scaling up/down and expiration handling.
• Suger aims to integrate with GitHub for automatic updates.

Participants:

·        Jon Yoo – CEO and Co-founder, Suger

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

SentinelOne's Ric Smith shares how Purple AI, built on Amazon Bedrock, helps security teams handle increasing threat volumes while facing budget constraints and talent shortages.

Topics Include:

• Introduction of Ric Smith, President of Product Technology and Operations
• SentinelOne overview: cybersecurity company focused on endpoint and data security
• Customer range: small businesses to Fortune 10 companies
• Products protect endpoints, cloud environments, and provide enterprise observability
• Ric oversees 65% of company operations
• Purple AI launched on AWS Bedrock
• Purple AI helps security teams become more efficient and productive
• Security teams face budget constraints and talent shortages
• Purple AI helps teams manage increasing alert volumes
• Top security challenge: increased malware variants through AI
• AI enables more convincing spear-phishing attempts
• Identity breaches through social engineering are increasing
• Voice deepfakes used to bypass security protocols
• Future threats: autonomous AI agents conducting orchestrated attacks
• SentinelOne helps with productivity and advanced detection capabilities
• SentinelOne primarily deployed on AWS infrastructure
• Using SageMaker and Bedrock for AI capabilities
• Best practice: find partners for AI training and deployment
• Customer insight: Purple AI made teams more confident and creative
• AI frees security teams from constant anxiety
• SentinelOne's hyper-automation handles cascading remediation tasks
• Multiple operational modes: fully automated or human-in-the-loop
• Agent-to-agent interactions expected within 24 months
• Common misconception: generative AI is infallible
• AI helps with "blank slate problem" providing starting frameworks
• AI content still requires human personalization and review
• AWS partnership provides cost efficiency and governance benefits

Participants:

·        Ric Smith – President – Product, Technology and Operations, SentinelOne

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

Sam Gantner, Chief Product Officer of Nexthink, reveals how DEX is moving IT from reactive firefighting to proactive problem prevention and transforming enterprise productivity.

Topics Include:

• DEX stands for Digital Employee Experience
• DEX eliminates IT issues preventing employee productivity
• Shifts IT from reactive to proactive problem-solving
• Employees often serve as IT problem alerting systems
• Best IT is transparent to employees
• DEX solves device sluggishness and slow application issues
• Network problems consistently appear across organizations
• IT teams often lack visibility into employee experiences
• Many organizations waste money on unused software licenses
• DEX Score measures comprehensive employee IT experience
• Surveys capture subjective aspects of technology experience
• Reduction of actual problems differs from ticket reduction
• Nexthink uses lightweight agents on employee devices
• Browser monitoring essential as browsers become application platforms
• Employee engagement metrics capture real-time feedback
• Nexthink rebuilt as cloud-native platform using AWS services
• Company deploys across 10+ global AWS regions
• 30% of engineering resources dedicated to AI development
• One customer eliminated 50% of IT tickets
• Another recovered 37,000 productivity hours worth $3M annually
• A third saved $1.3M by identifying unused licenses
• AI implementation requires dedicated employee training
• Good AI now better than perfect AI never
• Technology adoption is the next DEX frontier
• Digital dexterity becoming critical for maximizing IT investments

Participants:

• Samuele Gantner – Chief Product Officer, Nexthink

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

Linda Ivy-Rosser, Vice President for Forrester, outlines the evolution of business applications and forward thinking predictions of their future.

Topics Include:

• Linda Ivy-Rosser has extensive business applications experience since the 1990s.
• Business applications historically seen as rigid and lethargic.
• 1990s: On-premise software with limited scale and flexibility.
• 2000s: SaaS emergence with Salesforce, AWS, and Azure.
• 2010s: Mobile-first applications focused on accessibility.
• Present: AI-driven applications characterize the "AI economy."
• Purpose of applications evolved from basic to complex capabilities.
• User expectations grew from friendly interfaces to intelligent systems.
• Four agreements: AI-infused, composable, cloud-native, ecosystem-driven.
• AI-infused: 69% consider essential/important in vendor selection.
• Composability expected to grow in importance with API architectures.
• Cloud-native: 79% view as foundation for digital transformation.
• Ecosystem-driven: 68% recognize importance of strategic alliances.
• Challenges: integration, interoperability, data accessibility, user adoption.
• 43% prioritizing cross-functional workflow and data accessibility capabilities.
• Tech convergence recycles as horizontal strategy for software companies.
• Data contextualization crucial for employee adoption of intelligent applications.
• Explainable AI necessary to build trust in recommendations.
• Case study: 83% of operators rejected AI recommendations without explanations.
• Tulip example demonstrated three of four agreements successfully.
• Software giants using strategic alliances as competitive advantage.
• AWS offers comprehensive AI infrastructure, platforms, models, and services.
• Salesforce created ecosystem both within and outside their platform.
• SaaS marketplaces bridge AI model providers and businesses.
• Innovation requires partnerships between software vendors and ISVs.
• Enterprises forming cohorts with startups to solve business challenges.
• Software supply chain transparency increasingly important.
• Government sector slower to adopt cloud and AI technologies.
• Change resistance remains significant challenge for adoption.
• 69% prioritize improving innovation capability over next year.

Participants:

• Linda Ivy-Rosser - Vice President, Enterprise Software, IT services and Digital Transformation Executive Portfolio, Forrester

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

New Relic's Chief Customer Officer Arnaldo (Arnie) Lopez details how their observability platform helps 70,000+ customers monitor cloud performance through AWS infrastructure while introducing AI capabilities that simplify operations.

Topics Include:

• Arnie Lopez is SVP, Chief Customer Officer at New Relic.
• Oversees pre-sales, post-sales, technical support, and enablement teams.
• New Relic University offers customer certifications.
• Founded in 2008, pioneered application performance monitoring (APM).
• Now offers "Observability 3.0" for full-stack visibility.
• Prevents interruptions during cloud migration and operations.
• Serves 70,000+ customers across various industries.
• 16,000 enterprise-level paying customers.
• Platform consolidates multiple monitoring tools into one solution.
• Helps detect issues before customers experience performance problems.
• Market challenge: customers using disparate observability solutions.
• Reduces TCO by eliminating multiple monitoring tools.
• Targets VPs, CTOs, CIOs, and sometimes CEOs.
• Decade-long partnership with AWS.
• Platform built on largest unified telemetry data cloud.
• Uses AWS Graviton instances and Amazon EKS.
• AWS partnership enables innovation and customer trust.
• Three AI approaches: user assistance, LLM monitoring, faster insights.
• New Relic AI helps write query language (NURCLs).
• Monitors LLMs in customer environments.
• Uses AI to accelerate incident resolution.
• Lesson learned: should have started AI implementation sooner.
• Many customers still cautiously adopting AI technologies.
• Goal: continue growth with AWS partnership.
• Offers compute-based pricing model.
• Customers only pay for what they use.
• Announced one-step AWS monitoring for enterprise scale.
• Amazon Q Business and New Relic AI integration.
• Agent-to-agent AI eliminates data silos.
• Embeds performance insights into business application workflows.

Participants:

• Arnie Lopez – SVP Chief Customer Officer, New Relic

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

PDI Technologies’ Steve Antonakakis shares how his company is implementing generative AI across their fuel and retail technology ecosystem through a practical, customer-focused approach using Amazon Bedrock.

Topics Include:

• PDI's COO/CTO discussing generative AI implementation
• Practical step-by-step approach to AI integration
• Testing in real-world settings with customer feedback
• AWS Bedrock and Nova models exceeded expectations
• Early adoption phase with huge potential
• Fuel/retail industry processes many in-person transactions
• PDI began in 1983 as ERP provider
• Grew through 33+ acquisitions
• Provides end-to-end fuel industry solutions
• Owns GasBuddy and Shell Fuel Rewards
• Processes millions of transactions daily
• Generative AI fits into their intelligence plane architecture
• AWS Bedrock integrates well with existing infrastructure
• Focus on trusted, controlled, accountable AI
• Productizing AI features harder than traditional features
• Created entrepreneurial structure alongside regular product teams
• Team designed to fail fast but stay customer-focused
• AI features can access databases without disrupting applications
• Customers want summarization across different business areas
• AI provides insights and actionable recommendations
• Conversational AI replaces traditional reporting limitations
• Working closely with customers to solve problems together
• Beyond prototyping phase, now in implementation
• AWS Nova provides excellent cost-to-value ratio
• Focus on measuring customer value over immediate profitability
• RFP use case saved half a million dollars
• Early prompts were massive, now more structured
• Setting realistic customer expectations is important
• Data security approach same as other applications
• Treating AI outputs with same data classification standards

Participants:

• Steve Antonakakis – COO & CTO, Retail & Energy, PDI Technologies

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