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/

From 3am war rooms to self-healing infrastructure, LogicMonitor's GM of AI shares a compelling vision for how observability and agentic AI are transforming IT organizations worldwide.

Topics Include:

• LogicMonitor is a 15-year-old AI-powered hybrid observability company.
• Their AI product, Edwin AI, targets IT alert fatigue and noise.
• Enterprise IT teams are drowning in signals from dozens of monitoring tools.
• Generative AI evolved from machine learning — agents are the next frontier.
• LogicMonitor's first Edwin use case: help teams know what to focus on.
• Key lesson learned: stop chasing perfection and start experimenting faster.
• AI adoption requires serious change management, not just technical deployment.
• Success metrics should be process efficiency, not vanity adoption numbers.
• LogicMonitor accelerated software releases from monthly to weekly to daily.
• AWS Bedrock powers Edwin AI; Agent Core reduces infrastructure complexity.
• Agentic AI will run long, complex workflows without human intervention.
• The future is self-healing infrastructure — systems that sense, fix, and notify.

Participants:

• Karthik Sj – General Manager of AI, LogicMonitor

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

Cohesity CPO Vasu Murthy breaks down how enterprise data protection has evolved into a 24/7 cyber recovery operation — and why the battle against ransomware is now being fought with AI on both sides.

Topics Include:

• Cohesity protects, secures, and provides insights into enterprise data globally.
• 70% of Fortune 500 companies trust Cohesity with their critical data.
• Cyber attacks are now the dominant threat to enterprise data resilience.
• Cohesity recently merged with Veritas, dramatically expanding its customer base.
• Real-world rescue: a cyber-hit company ran payroll on time anyway.
• Recovery operations run 24/7, with dozens of active rescues at any time.
• The threat landscape is now AI versus AI — and escalating fast.
• Cohesity enables customers to practice cyber recovery drills through automation.
• AI is accelerating product cycles — planning that took months now takes weeks.
• More than a third of Cohesity's latest release was AI-assisted code.
• Flatter teams and less hierarchy are defining the new CPO playbook.
• AWS partnership innovations like Glacier Instant Retrieval delivered 30% cost savings.

Participants:

• Vasu Murthy – Chief Product Officer, Cohesity

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

CTO Sam Pierson explains how Qlik’s associative engine and agentic AI are transforming the way businesses uncover insights and what’s next on the data frontier.

Topics Include:

• Qlik is a 30-year-old data analytics and AI company with global customers.
• Qlik's associative engine surfaces insights from data you aren't even examining.
• A paper manufacturer optimized supply chain routing and navigated tariff complexity.
• Generative AI can't easily query databases — Qlik's engine bridges that gap.
• Qlik built an agentic layer enabling natural language conversations with your data.
• MCP integration lets users access Qlik insights directly from tools like Claude Desktop.
• Qlik runs entirely on AWS, with global regions built around local compliance requirements.
• The AWS partnership prioritizes mutual success over transactional service relationships.
• Agents will mature in 2026; some agentic bets will succeed, others will be refactored.
• Fine-tuned, smaller language models will grow in importance alongside larger ones.
• AI adoption requires restructuring workflows end-to-end, from product spec to go-to-market.
• Qlik is hiring for curiosity and agency — people who experiment without waiting for permission.

Participants:

• Sam Pierson – Chief Technology Officer, Qlik

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

Sumo Logic's VP of Security Strategy reveals how a ground-up agentic framework transformed their platform, and why clean data and autonomous agents are rewriting the rules of cloud security.

Topics Include:

• Sumo Logic is a cloud analytics platform ingesting data from complex IT stacks.
• Built on AWS from the start, leveraging microservices for scalable solutions.
• Early AI efforts produced a natural language query co-pilot for security data.
• Bolting AI onto existing platforms proved brittle and one-dimensional.
• Customer feedback drove a decision to redesign AI from the ground up.
• The Dojo AI framework unifies purpose-built agents across the entire platform.
• New agents include a SOC analyst agent, knowledge agent, and MCP server.
• New frontier models on Bedrock give the whole platform an instant brain transplant.
• Autonomous agents require rethinking security controls beyond traditional programmatic guardrails.
• Federal and global customers demand rigorous, levelled-up security across all regions.
• Clean, normalized data proved the biggest unlock for reliable AI query results.
• Agent-to-agent communication and MCP will define the next era of AI platforms.

Participants:

• Chas Clawson – Vice President, Security Strategy, Sumo Logic

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

Avalara's Chief Architect Tim Diekmann reveals how AI and agentic technology are transforming tax compliance and accuracy across 40,000 jurisdictions leveraging AWS.

Topics Include:

• Avalara provides tax compliance software across North America, Europe, and beyond.
• They operate between commerce and government, covering 40,000+ jurisdictions.
• Services span registration, sales tax calculation, and certificate management.
• Avalara was the only company keeping pace with rapid tariff changes.
• AI is used to parse unstructured documents like tax notices and publications.
• Intelligent mapping automates ERP integration across vastly different system configurations.
• GenAI lets customers query billions of transactions using plain conversational language.
• Avalara and AWS are now engaged in a promising co-selling motion.
• Time-to-go-live and transaction accuracy are the key success metrics tracked.
• Amazon Q was rolled out company-wide, achieving 95% developer adoption.
• AI literacy is now prioritized across legal, HR, and engineering teams alike.
• Agentic AI will embed Avalara directly inside customer ERP systems going forward.

Participants:

• Tim Diekmann – SVP of Engineering, Chief Architect, Avalara

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

Honeycomb Co-founder and CTO Charity Majors explains why measuring the right engineering metrics in the age of AI matters more than chasing numbers.

Topics Include:

• Charity Majors introduces Honeycomb as the original observability company for complex systems
• Honeycomb solves high cardinality problems across millions of individual customer experiences
• Their MCP tool ranked top five in Stack Overflow's most-used list
• Canva lets developers interact with production software directly from their IDE
• AI acts as an amplifier requiring strong reliability and observability foundations
• Measuring success requires multiple metrics to avoid gaming single numbers
• Honeycomb adopted Intercom's 2X productivity challenge enlisting employees to identify gains
• Writing code was never the hard part even before generative AI arrived
• Honeycomb created AI values prioritizing transparency and emotional safety for employees
• Staff tested boundaries on resources and environmental impact prompting honest discussions
• Honeycomb acquired Grok and shipped Query Assistant Canvas and MCP products
• Future concerns include AI economics shifting and AI-native developers lacking foundational expertise

Participants:

• Charity Majors – Co-Founder/CTO, Honeycomb.io

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

Astronomer's Steven Hillion reveals how OpenAI, Anthropic, Uber, and Lyft use Apache Airflow to orchestrate AI and machine learning pipelines at scale on AWS.

Topics Include:

• Steven Hillion leads data and AI at Astronomer
• Apache Airflow surpassed Spark and Kafka in community metrics
• Astronomer coordinates data flow like conductor orchestrating instrumental platforms
• Organizations with data engineering teams use Airflow at scale
• Customers already used Airflow for ML before official promotion
• Uber and Lyft orchestrate pricing models using Airflow
• Astronomer runs on AWS with close integration partnerships
• OpenAI Anthropic and GitHub Copilot use Airflow for operations
• Internal data team uses Airflow creating feedback loops
• Evolved from constrained AI reports to agentic workflows
• Platform monitors generative AI output quality at user interactions
• Metadata and context increasingly critical for AI applications
• Learn more at Astronomer’s Data FlowCast podcast

Participants:

• Steven Hillion – SVP, Data and AI, Astronomer

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