In this interview from AWS Summit Washington, D.C. 2026, Logan Sammons, strategic architect at Palantir Technologies, joins theCUBE + NYSE Wired's Gemma Allen to discuss how Palantir and AWS are helping government agencies move from AI experimentation to mission-ready execution. Sammons explains how Palantir's tier-two service provider authorization pulls directly from AWS's tier-one DOD provisional authorization, giving customers seamless security integration and the ability to operationalize data on day one. He breaks down how AIP, Palantir's model-agnostic AI platform, moves agencies beyond sandbox experimentation by allowing them to select accredited language models — from FedRAMP to DOD IL6 to ICD 503 — best suited to each specific mission outcome.

The conversation also explores Palantir's Ontology layer, which sits above individual AI services and language models to map an enterprise's data and architecture into a common machine-readable structure, enabling agentic AI to pull decision-making forward rather than produce more data for humans to synthesize. Sammons addresses vendor lock concerns directly, arguing that Palantir's approach builds an architecturally sound enterprise foundation that remains independent of any single model, subscription or infrastructure provider — so customers in government, healthcare and financial services retain the flexibility to match the right model to each project. Looking ahead, he outlines how the Palantir-AWS partnership is focused on pre-authorization, multi-region capacity planning and transparent security reviews to compress government authorization timelines and give agencies the ability to deploy AI at mission speed from day one.

In this interview from AWS Summit Washington, D.C. 2026, Steve Schmidt, chief security officer of Amazon, joins theCUBE + NYSE Wired's Gemma Allen to discuss how AI is shrinking the window from threat detection to active defense as cyber adversaries accelerate their attacks. Schmidt introduces MadPot, Amazon's global honeypot network that monitors over one billion adverse threat signals daily, noting that adversaries discover new sensors in under 90 seconds and attempt exploitation within three minutes. He underscores how Amazon's visibility across satellites, robotics and cloud workloads gives it a uniquely broad view of adversary behavior — enabling analysis of not just what attackers are doing, but why. He explains how AI has compressed defensive signature generation from several hours down to under 15 minutes, enabling near-real-time protection through services like GuardDuty.

The conversation also explores how Amazon governs agentic AI in high-stakes security decisions, including Schmidt's framework of "one-way doors" versus "two-way doors" to determine when human sign-off is required versus when agents can act autonomously. Schmidt addresses the Mythos model and the growing capability of AI to not just find vulnerabilities but chain and build exploits automatically, arguing that patch deployment cycles of 30 to 90 days are no longer viable and must shrink to hours. He details Amazon's partnership with CrowdStrike to track agent identities on edge devices and fuse that data with cloud-level telemetry for a complete defensive picture. From governing autonomous agents to preserving human judgment as the irreducible safeguard, Schmidt outlines how organizations can stay ahead in an era where adversaries are not acquiring better tools — they are simply moving much faster.

In this interview from AWS Summit Washington, D.C. 2026, Francessca Vasquez, vice president of frontier AI engineering and services at Amazon Web Services, joins theCUBE + NYSE Wired's Gemma Allen to discuss how AWS's newly launched Forward Deploy Engineering initiative is redefining what it means to take enterprise AI from experimentation to production. Vasquez traces the path from AWS's Machine Learning Solutions Lab in 2017 through its Generative AI Innovation Center to the current FDE model, built for the agentic era. She explains how embedded agile pods of five to six engineers operate inside customer environments, applying an AI-native development lifecycle to deliver working production deployments — not traditional consulting artifacts.

The conversation also explores the "Live in 45" framework — a sprint model that moves customers from ideation in 45 minutes to a validated proof point in 45 hours to a production deployment in 45 days. Vasquez highlights how FDE's model-agnostic approach, spanning Amazon Bedrock, AgentCore and Kiro, ensures organizations avoid lock-in while accessing AWS's full frontier AI capabilities. She identifies the strongest FDE candidates as data-rich industries — financial services, government and healthcare — where leadership conviction and existing data foundations accelerate time to value. From enabling customers to become self-sufficient through active skills transfer to scaling a partner ecosystem that extends FDE reach, Vasquez outlines how AWS is positioning FDE to deliver measurable, mission-ready outcomes across the enterprise.

At the Amazon Web Services Summit DC 2026, theCUBE Research presents a conversation on public sector artificial intelligence, citizen engagement and partnership-led digital transformation. Gemma Allen of theCUBE moderates the session with Angy Peterson of Granicus, senior vice president of experience services, and Alec Chalmers of Amazon Web Services, hereafter AWS, director of edtech and govtech. Peterson and Chalmers discuss AI-driven government services and the role of cloud-native agents, context-aware AI, content governance, accessibility and multilingual support in modernizing citizen interactions.

Peterson outlines Granicus's civic engagement platform and multilingual deployments. They report measurable operational gains in customer environments, noting that Granicus reduces call-center wait times by about 30% and saves approximately 600 staff hours annually in Wyandotte County, with similar volume relief in Jackson County. Chalmers explains AWS support for agentic flows and describes how AWS Bedrock and AgentCore provide guardrails and model flexibility, enabling context-aware, auditable agents and a path to integrated workflow agents for broader AI adoption.

The discussion highlights practical factors to consider when deploying AI in the public sector, such as content governance, auditability, accessibility, multilingual support and scalable cloud architectures. Speakers emphasize partnership-led approaches that combine platform capabilities with cloud service flexibility to deliver trusted, efficient and accessible citizen services.

In this interview from AWS Summit Washington, D.C. 2026, Faisal Sublaban, executive vice president of AskMD at Sharecare, joins theCUBE + NYSE Wired's Gemma Allen to discuss how a 50-year clinical reasoning engine is being reimagined as an agentic AI health navigation platform built on Amazon Bedrock. Sublaban frames the core challenge not as a shortage of health data but as fragmentation — over 30 billion health-related searches occur on Google each month, yet users receive generic responses regardless of their insurance coverage, medical history or individual circumstances. AskMD addresses this through three capabilities: insurance awareness, permissioned access to medical records and actionable guidance on next steps. He is clear that the platform is not telehealth — it is a navigation layer — and argues that Sharecare's governed orchestration layer is the product, not the underlying model.

The conversation also explores Sharecare's multimodal model strategy on Amazon Bedrock, where Anthropic leads in healthcare workflows but Sublaban explains the flexibility to route traffic to smaller distillation models or Sharecare's own on-prem clinical reasoning model hosted within AWS infrastructure. He addresses the competitive pressure from general-purpose LLMs like ChatGPT by introducing the "commitment curve" concept — that users who experience contextualized health intelligence are unlikely to return to generic responses. Trust anchors the entire architecture: AskMD requires biometric identity proofing at IAL2 certification through partnerships with CLEAR and ID.me, and users retain full permissioned control over what data they share at any given time. From eliminating health data fragmentation to building a clinically grounded AI layer that serves both consumers and providers, Sublaban provides a roadmap for how healthcare can meet the moment without compromising accuracy or trust.

In this interview from AWS Summit Washington, D.C. 2026, Faisal Hanafi, director of worldwide public sector at Amazon Web Services, joins Taylor Johnston, president and chief executive officer of University of South Florida Institute for Applied Engineering, to talk with theCUBE + NYSE Wired's Gemma Allen about how academia and cloud infrastructure are converging to accelerate defense-ready research and mission-critical innovation. The discussion centers on a newly signed memorandum of understanding between AWS and USF — grounded in Tampa's unique position as home to both Special Operations Command and Central Command. Hanafi explains how the Secure Research Environment (SRE) being established at USF compresses research timelines from years to days, enabling classified work at FedRAMP High, IL6 and TS/SCI levels. Johnston details how students gain security clearances and hands-on experience with Bedrock and Kiro during their undergraduate careers, graduating ready to contribute to DoD missions from day one.

The conversation also explores how the SRE addresses two pressing challenges for universities: protecting sensitive research from exfiltration to countries of concern and diversifying revenue from grants toward DoD applied research contracts. Johnston notes that while foundational research funding faces headwinds in the next federal budget cycle, applied and component research is expanding — and the SRE creates the secure, collaborative infrastructure needed to deliver on those contracts. Looking ahead, the partnership targets military medical innovation through USF's relationship with Tampa General Hospital, spanning traumatic brain injury treatment and radiology, alongside advanced capabilities in electronic warfare and computer vision for targeting. From enabling students to graduate clearance-ready to delivering research at what Johnston calls "the speed of need," the discussion frames the AWS-USF model as a blueprint for industry-academic collaboration that others can emulate.

In this interview from AWS Summit Washington, D.C. 2026, Angela Shippy, director and senior physician executive at Amazon Web Services, joins theCUBE + NYSE Wired's Gemma Allen to discuss how AI is accelerating healthcare innovation, from patient access and operational efficiency to drug discovery and global disease surveillance. Shippy, whose clinical career included leading pandemic incident response before joining AWS in 2021, explains why healthcare is no longer a slow adopter — 19 of the top 20 pharmaceutical companies and 80% of healthcare and life sciences unicorns are already running AI on AWS infrastructure. She highlights how agentic AI is compressing deployment timelines from weeks to hours, giving non-developer clinical staff the ability to build and iterate on applications faster than ever.

The conversation explores specific use cases where that speed is translating into measurable outcomes. At UC San Diego, Amazon Connect Health enabled 3.2 million patient interactions while cutting agent hours by 33,000 and reducing call abandonment by up to 60%. Jupiter Medical used the same platform to shrink a diagnostic backlog from a two-week wait to 24 hours. Shippy also details Amazon Bio Discovery, which is helping institutions like Memorial Sloan Kettering accelerate drug discovery from months to days, and the Fleming Initiative — a global effort spanning 150 communities to combat antimicrobial resistance, a crisis claiming a life every 15 seconds. From reducing operational friction for rural and underserved hospital networks to positioning AI agents as discovery partners in oncology and beyond, Shippy outlines how cloud infrastructure and AI are moving healthcare from reactive care to proactive, mission-driven innovation.

In this interview from AWS Summit Washington, D.C. 2026, Dave Levy, vice president of worldwide public sector at Amazon Web Services, joins theCUBE + NYSE Wired's Gemma Allen to discuss how governments and public sector organizations are moving from cloud migration to mission-ready AI execution. Levy outlines two landmark billion-dollar commitments announced at the summit: a forward deployed engineering program that embeds AWS engineers directly inside agencies for real-time, hands-on problem-solving — distinct from traditional consulting engagements — and an initiative designed to free "trapped" on-premises workloads by offsetting the double-bubble costs of migration. He explains how a proven delivery framework underpins a 45-day sprint model, giving agencies both the speed and confidence to modernize critical systems without compromising compliance or operational resilience.

The conversation also explores the growing global appetite for agentic AI in government, as Levy details how agencies are applying it to combat fraud, waste and abuse, strengthen national security and deliver faster citizen services. He shares standout real-world examples — a UK council deploying AI to help residents navigate lease agreements, sensor-enabled monitoring in elderly homes to accelerate social service response and healthcare systems using AI to speed diagnosis, improve discharge rates and reduce unnecessary emergency department visits. Levy also addresses long-standing public sector challenges around talent and fiscal responsibility, arguing that modern technology is itself a competitive attractor for mission-driven engineers. From embedding AWS engineers inside federal agencies to giving a single researcher access to the same high-performance computing resources once reserved for entire organizations, he outlines why cloud and AI have become the foundation of national infrastructure — not just an IT decision.