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/