If you're betting on agentic AI, hear directly from the builders navigating the challenges, innovating pricing models, and creating the coming reality where every employee manages thousands of agents.

Topics Include:

• Four panelists represent the full AI stack: build, run, secure, monitor.
• Agentic AI moved faster than anyone predicted just 18 months ago.
• Writer AI's no-code agent builder missed both its target personas entirely.
• Non-technical users now just prompt agents instead of building workflows.
• Fireworks AI processes over ten trillion tokens daily across open models.
• DeepSeek's Christmas release tripled Fireworks' capacity needs almost overnight.
• Okta identified agent identity as a security problem from day one.
• 91% of organizations are already using AI agents in some capacity.
• Datadog evolved naturally from dashboards to autonomous investigative agents.
• Bits.ai agents now diagnose production incidents before engineers wake up.
• Trust requires explainability — black-box agents stall enterprise adoption cold.
• Human-in-the-loop remains essential; risk tolerance varies wildly by organization.
• Writer AI compressed a four-month retail workflow down to one week.
• Multi-provider inference consistency is one of the hardest unsolved infrastructure problems.
• Agentic pricing models are fundamentally broken for enterprise budget planning today.
• Agents managing agents means every employee becomes a manager of thousands.
• POC data gaps are the most underrated blocker to production deployment.
• Security must be designed in from the start — retrofitting is painful.
• Build evaluations first so you know if you're actually improving anything.
• Find your uniquely differentiated data and build your agentic bet there.

Participants:

• Yannick Guillerm – Regional Manager, Sales Engineering, Datadog
• Ray Thai – Director of Product Management, Fireworks AI
• Andrew Yu – Vice President of Engineering, Okta
• Matan-Paul Shetrit – Director of Product Management, Writer AI
• Moderator: Carol Potts – General Manager, North America ISV 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/

Asana CPO Arnab Bose breaks down how AI agents are transforming collaborative work management with multiplayer AI teammates that any team member can coach and correct.

Topics Include:

• Asana is a collaborative work management platform used by 170,000+ companies worldwide.
• The "Pyramid of Clarity" connects individual tasks all the way up to company strategy.
• Asana's "work graph" maps tasks, teams, projects, and portfolios in one connected system.
• Generative AI now converts unstructured data like emails into structured project plans.
• Asana integrates directly with AWS, Gemini, and Claude to automate that conversion.
• AI Teammates are first-party agents that take on and complete tasks inside Asana.
• These agents work in multiplayer mode — visible, collaborative, and team-correctable.
• A third AI unlock is coming: letting any external agent builder plug into Asana's interface.
• Asana runs entirely on AWS, including a new FedRAMP moderate GovCloud deployment.
• AWS Marketplace listings help customers transact faster using existing AWS credits.
• Arnab advises startups to bet on AWS long-term rather than chasing short-term LLM trends.
• His 2026 prediction: multi-agent orchestration standards will be the enterprise AI battleground.

Participants:

• Arnab Bose – Chief Product Officer, Asana

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

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/

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/