Generative AI & Foundation Models

Key concepts

1. 1
   Foundation models vs. fine-tuned models vs. distilled models
2. 2
   Prompt engineering — system prompts, few-shot, chain-of-thought
3. 3
   Context windows, tokens, and inference cost optimization
4. 4
   Guardrails — content filtering, PII redaction, topic blocking
5. 5
   Model evaluation — automatic and human-in-the-loop
6. 6
   Provisioned throughput vs. on-demand inference

Key AWS services

• Amazon Bedrock
• Amazon Nova
• Amazon Titan
• SageMaker JumpStart
• Bedrock Guardrails

Learn more — curated resources

Hand-picked official docs, foundational papers, and the best community guides for going deeper on this topic.

• Amazon Bedrock — Official AWS page
• Amazon Nova foundation models
• Anthropic Claude on Bedrock
• Generative AI on AWS — Learning Path
• Prompt Engineering Guide
• Bedrock Workshop — hands-on labs

Sessions on this topic

50 sessions from the Summit covered this topic. Each is a self-contained mini-lesson.

1. PRT104-SFoundational

   Building Resilience for AI Data Foundations and Cloud-Native Apps 5 Steps to Enterprise-Grade AI Security for Amazon Bedrock Projects

   AI innovation depends on consistent, trusted data. When disrupted, AI systems and the business decisions they support are at risk. In this session, learn how cloudnative protection models support AI pipelines, reduce recovery time after disruptions, and minimise operational overhead. Discover best practices to protect AI and cloudnative applications in AWS while innovating with confidence.

2. PRT202-SIntermediate

   5 Steps to Enterprise-Grade AI Security for Amazon Bedrock Projects

   This session demonstrates how quickly and easily enterprise-grade AI security can be applied to your Amazon Bedrock projects. See the new Prisma AIRS AI-security platform in action on AWS: We explore Model Scanning and AI Posture Management; then dive into Runtime Security; and finally examine automated AI Red Teaming and AI Agent Security. Unlock your AI-led innovation - securely.

3. PRT204-SIntermediate

   Optimising GenAI at Runtime with Experimentation and Guardrails 5 Steps to Enterprise-Grade AI Security for Amazon Bedrock Projects

   Generative AI systems evolve constantly, and the impact of prompt or model changes often isnt clear until real users interact with them in production. In this session, learn how teams using Amazon Bedrock safely experiment with AI at runtime, testing models and prompts with targeted rollouts, evaluating system outputs online, and optimising against real business result

4. AIM401Expert

   Beyond API Dependency: Fine-tuning Cost-Effective Models on AWS

   As API costs for general-purpose LLMs rise, relying solely on off-the-shelf models can quickly undermine both cost control and system reliability. In this session, we share how Nearmap moved beyond API dependency by fine-tuning and distilling domain-specific models on AWS to analyze 300 million building permits for roof modifications. Well discuss our approach to generating and structuring training data, distilling large models into smaller, production-ready alternatives, evaluating trade-offs across model architectures, and making data-driven accuracy-versus-cost decisions before deployment. Attendees will leave with concrete patterns for shipping efficient, specialized models into production.

5. ANT301Advanced

   A practitioners guide to data for agentic AI

   In this session, gain the skills needed to deploy end-to-end agentic AI applications using your most valuable data. This session focuses on data management using processes like Model Context Protocol (MCP) and Retrieval Augmented Generation (RAG), and provides concepts that apply to other methods of customizing agentic AI applications. Discover best practice architectures using AWS database services like Amazon Aurora and OpenSearch Service, along with analytical, data processing and streaming experiences found in SageMaker Unified Studio. Learn data lake, governance, and data quality concepts and how Amazon Bedrock AgentCore and Bedrock Knowledge Bases, and other features tie solution components together.

6. ARC301Advanced

   Build an AI-ready data foundation

   An unparalleled level of interest in generative AI and agentic AI is driving organizations to rethink their data strategy. While there is a need for data foundation constructs such as data pipelines, data architectures, data stores and data governance to evolve, there are business elements that need to stay constant like cost-efficiency and effectively collaborating across data estates. In this session we will cover how building your data foundation on AWS provides the tools and the building blocks to balance both needs, and empower organizations to grow their data strategy for building AI-ready applications.

7. MAM306Advanced

   Adding Agentic AI to legacy apps with Amazon Bedrock AgentCore

   In this code-first session, we demonstrate how to add agentic AI capabilities and augment a legacy application using Amazon Bedrock AgentCore and the Amazon Strands Agents SDK. We will explore how to build AI-powered features for a legacy application without modifying the existing backend code. We will showcase how to leverage existing APIs and Lambda functions as the backbone for your agentic AI experience. You'll learn how to execute code in isolated sandbox environments, ensuring security while accessing internal data sources with Amazon Bedrock AgentCore Code Interpreter.

8. ISV302Advanced

   Architecting Scalable AI Agents using Amazon Bedrock AgentCore

   Discover how to build powerful AI agents using Amazon Bedrock's suite of tools, with a focus on Amazon Bedrock AgentCore. This session explores how Parrot Analytics leveraged the modular components of Amazon Bedrock AgentCore and Amazon Nova foundational models to achieve 10x the processing speed of manual classification across 2M+ entities. We will dive into prompt and context engineering, knowledge bases, and observability for production agentic workloads.

9. DEV205Intermediate

   Securing Amazon Bedrock AgentCore: A Practical Framework

   Explore a practical framework to think about and build secure AI agents on Amazon Bedrock AgentCore. This session covers threat modeling specific to agentic workloads, including how agents interact with tools, memory, and external systems, and what you need to watch out for. You'll learn how to apply AWS security best practices across AgentCore services, and walk away with actionable patterns. Suitable for developers and architects building AI agents who want to move from prototype to production with confidence.

10. DEV313Advanced

    From Timeout to Throughput: Scaling Resilient Agentic Systems

    Moving an AI agent from prototype to production requires more than optimism. This session tackles the "Day 2" engineering challenges of scaling resilient agentic architectures on AWS. Learn practical patterns for handling traffic spikes, optimizing throughput, and controlling costs using Amazon Bedrock models and AgentCore Runtime. We'll cover tool filtering strategies, when multi-agent architectures make sense, how to apply evaluations effectively, and how to harden your APIs against real-world load. Leave with concrete techniques to transform brittle GenAI prototypes into production-grade systems that survive viral launches and demanding enterprise workloads.

11. PRT103-SFoundational

    Cloud Anywhere: Architectural Freedom for Unified Data and AI 5 Steps to Enterprise-Grade AI Security for Amazon Bedrock Projects

    Need flexibility across cloud and on-premises This session reveals how delivering cloud anywhere gives you the architectural freedom to run data and AI across AWS, clouds and hybrid environments. Discover how a unified data fabric simplifies governance and security, accelerating AI-driven innovation. Achieve unified control and compliance for highly regulated environments.

12. DEV202Intermediate

    AI Native Development: Strategies and Impact across Amazon and AWS

    AI Native Development: Strategies and Impact across Amazon and AWSAmazon and AWS have evolved beyond AI-assisted development to embrace AI Native practices, integrating AI as a partner throughout the software development lifecycle. Learn how their teams leverage AWS foundational tools including Kiro, and Amazon Bedrock. Discover effective Prompt Driven Development methodologies and grassroots adoption strategies from early champions. See how Amazon enables teams to provide AI with right context through strategic use of MCP, RAG and custom models trained on Amazon technical knowledge. Understand the culture transformation required across multi-thousand person organizations, where every role must evolve. Gain actionable insights to accelerate your AI Native journey.

13. DEV314Advanced

    AI Native Development: Strategies and Impact across Amazon and AWS

    Amazon and AWS have evolved beyond AI-assisted development to embrace AI Native practices, integrating AI as a partner throughout the software development lifecycle. Learn how their teams leverage AWS foundational tools including Kiro, and Amazon Bedrock. Discover effective Prompt Driven Development methodologies and grassroots adoption strategies from early champions. See how Amazon enables teams to provide AI with right context through strategic use of MCP, RAG and custom models trained on Amazon technical knowledge. Understand the culture transformation required across multi-thousand person organizations, where every role must evolve. Gain actionable insights to accelerate your AI Native journey.

14. MAM307Advanced

    Modernise legacy code using fine-tuned Gen AI models

    Rio Tintos data science team saw an opportunity to preserve institutional knowledge and improve developer productivity by modernizing a legacy codebase. Rather than attempting a full system overhaul, the team focused first on adding generative AI capabilities to their critical legacy application. By using the proven, open, and trusted data foundation of AWS, the company laid the groundwork for incremental modernization without disrupting core operations. Learn about model fine tuning against legacy codebases, Amazon Nova, SageMaker Jumpstart and AgentCore in this deep dive with AWS & Rio Tinto

15. PRT101-SFoundational

    Accelerating Innovation with GitLab DAP Powered by Amazon Bedrock

    Learn how GitLab Duo Agent Platform (DAP) powered by Amazon Bedrock brings agentic AI into every stage of the software development lifecycle while keeping data, logs, and inference traffic inside your AWS environment. We'll show how teams can orchestrate AI-assisted workflows for planning, coding, security, and compliance using Amazon Bedrock foundation models behind GitLab's AI Gateway.

16. PRT203-SIntermediate

    Design, Deploy, and Govern AI Agents with Boomis Agentstudio 5 Steps to Enterprise-Grade AI Security for Amazon Bedrock Projects

    Transform enterprise automation with Boomi's AI agent ecosystem. Learn to use Agent Designer to visually build agents that connect across systems, and Agent Control Tower for centralised governance, compliance, and performance monitoring. Securely orchestrate your AI lifecycle at scale with Amazon Bedrock.

17. COP302Advanced

    Applying AI for FinOps and FinOps for AI

    Explore the intersection of AI and FinOps in this advanced session. First, discover how Kiro CLI can simplify AWS cost management by analyzing trends, explaining spend, and recommending optimizations like rightsizing and Savings Plans. Then, dive into FinOps for AI- learn how to track and control generative AI costs across Amazon EC2, Amazon SageMaker, Amazon Bedrock, and more. We'll share architecture patterns, cost-saving strategies, and real-world examples to help you build scalable, production-ready AI solutions while staying on budget. Whether you're optimizing existing workloads or launching new AI initiatives, you'll leave with practical tools to maximize value.

18. DEV305Advanced

    Agents in the enterprise: Best practices with Amazon Bedrock AgentCore

    As organizations scale AI agent development, robust enterprise architecture patterns become essential. In this advanced session, we'll explore how Amazon Bedrock AgentCore enables teams to build modular systems using their preferred frameworks while sharing tools through MCP gateways. Learn about A2A collaboration, shared memory, identity-based access controls, and integrated observability. Discover practical strategies for secure runtime deployment, standardized tool integration, evaluation frameworks, and end-to-end monitoring. Leave with actionable insights to build secure, scalable agent infrastructures that balance centralized governance with team autonomy.

19. DEV401Expert

    Build Intelligent Memory Systems for AI Agents

    Explore how to build production-grade AI agents with persistent, context-aware memory using Amazon Bedrock AgentCore. This expert session covers architectural patterns for implementing four memory typesepisodic, semantic, preference, and summaryenabling agents that recall past interactions, recognize cross-session patterns, and maintain conversation context. You'll examine real implementation techniques for long-term memory management, workflow orchestration, and retrieval strategies using Amazon Bedrock. Leave with practical skills to design intelligent agents that deliver faster, more accurate responses in high-stakes applications. Ideal for architects and engineers ready to move beyond stateless AI toward genuinely intelligent, memory-enabled systems.

20. STP208Intermediate

    NextAI's LegalScout: A Data Foundation for Private Legal AI

    LegalScout helps Australian SME law firms turn Generative AI into a competitive advantage by securely leveraging their own client data and confidential matters to work smarter, not harder. Built with Australian lawyers on AWS using Amazon Bedrock for inference and Amazon S3Vectors for secure document searches, it automates repetitive work, streamlines workflows, and improves drafting, contract review, and research to boost productivity, reduce costs, and lift accuracy while maintaining strict privacy and compliance.

21. TNC201Intermediate

    Explore the Agentic Capabilities of Amazon Quick Suite

    Discover the latest features of Amazon Quick Suite, a generative AI-powered business intelligence platform transforming organizational data workflows. Explore the newest capabilities including Quick Sight for interactive visualizations, Quick Flows for workflow creation, Quick Automate for intelligent automation, and Quick Research for comprehensive analysis. Learn how custom chat agents, knowledge spaces, and workplace extensions integrate seamlessly to enhance productivity through natural language interactions across your organization.

22. INO201Intermediate

    Build and scale AI: from reliable agents to transformative systems

    Many teams move fast with agentic AI prototypes that impress in demos but stall in productionblocked by gaps in reliability, accuracy, and safety. In this session, AWS agentic AI technical leaders will help builders rethink how to build and scale production-grade, trustworthy agentic AI. Learn proven patterns to build and deploy agents that earn trust in the real world. See AWS agentic AI platform Amazon Bedrock AgentCore in action. Discover how AWS customers move fast from sparks of experiment to scaled AI-driven innovation with trust at the core, transforming industries.

23. ARC303Advanced

    Unlock GenAI inference anywhere with Amazon EKS Hybrid Nodes

    Join this session to explore how Amazon EKS Hybrid Nodes enables GenAI inference anywhere. We'll discuss reference architectures for adding on-prem GPUs to your EKS hybrid cluster, and for running real-time data capture and processing at the edge. You'll learn how EKS Hybrid Nodes enables seamless integration between the cloud and your on-prem or edge environments. Well also walk through a real-world example, showcasing how to accelerate GenAI inference at the edge using Amazon EKS Hybrid Nodes with NVIDIA DGX platform.

24. DAT301Advanced

    Powering your Agentic AI experience with AWS Streaming and Messaging

    Powering your Agentic AI experience with AWS Streaming and MessagingOrganizations are accelerating innovation with generative AI and agentic AI use cases. This session explores how AWS streaming and messaging services such as Amazon Managed Streaming for Apache Kafka, Kinesis Data Streams, Amazon Managed Service for Apache Flink, and Amazon SQS build intelligent, responsive applications. Discover how streaming supports real-time data ingestion and processing, while messaging ensures reliable coordination between AI agents, orchestrates workflows, and delivers critical information at scale. Learn architectural patterns that highlight how a unified approach acts on data as fast as needed, providing the reliability and scale to grow for your next generation of AI.

25. DEV311Advanced

    Serverless Developer Experience: Day in a life of builder

    What does it mean to be a serverless developer in the era of GenAI What disciplines do you need to master to build cloud-native, serverless solutions today In this session, we'll walk through a day in the life of a serverless developer and explore the core principles, architecture patterns, frameworks, and how to leverage GenAI tools to build your next-generation serverless application.

26. ARC307Advanced

    AI Powered Resilience Lifecycle

    Not all disaster recovery strategies can address the complex, dynamic nature of modern cloud infrastructures, leading to gaps in system resilience and compliance adherence. Discover how to enhance resilience and disaster recovery on AWS empowered by AI. This approach bridges infrastructure insights and application-level testing, enabling more effective disaster recovery preparation. You will learn how to leverage Large Language Models (LLMs) with AWS Resilience Hub and AWS Systems Manager to modernize testing, analyze infrastructure, and generate targeted AWS Fault Injection Service experiments and recovery runbooks. Walk away with practical examples of automated test generation with templates and learn to design prompts.

27. AIM101Foundational

    AI League Championship | 14-May | 08:00 - 16:00

    Experience the ultimate AI showdown from your theater seat as finalists from the AWS AI League: Agentic AI challenge battle head-to-head in real-time. Watch top performers compete in a live, tournament-style competition where their AI agents navigate complex challenges, demonstrating the power of intelligent automation and decision-making under pressure. This electrifying viewing experience offers AI practitioners and enthusiasts unique insights into orchestrating intelligent agents using Amazon Bedrock AgentCore. See firsthand how agents handle real-world scenarios including code execution, web browsing, content moderation, and multi-step problem solvingall while competing for championship glory. The 1st place winner will represent Australia at the 2026 AWS AI League Championship at re:Invent 2026.

28. AIM403Expert

    AI League

    Building intelligent AI Agents with Amazon Bedrock AgentCore Dive into the future of Al in this competitive workshop where you'll create intelligent agents using Amazon Bedrock AgentCore. Using our no-code Ul interface and generative AI you will develop agents and agentic tools that tackle real-world technical challenges. Experience hands-on learning through dynamic gameplay with live leaderboards while mastering prompt engineering, safety guardrails, tool creation, and performance optimization. Whether you are an avid Al developer or an architect eager to gain practical experience with production-grade agentic Al, this session will give you a new hands-on experience.

29. IDE301Advanced

    Diversity In Tech - AI Literacy Skills - Rapid prototyping with Kiro

    In this workshop you will be shown how to build functional prototypes using our proven techniques. Learn how to leverage Kiro to go beyond "vibe-coding", and transform ideas into fully functional prototypes while validating technical approaches. Discover effective spec-driven development and prompt engineering techniques combining generative AI capabilities with AWS services for rapid iteration and refinement. If participants would like to follow along please bring your own laptop.

30. STP204Intermediate

    How Heidi Health Fine-Tunes Speech-to-Text Models on AWS

    Join Heidi Health and AWS's Generative AI Innovation Center (GenAIIC) for a behind-the-scenes look at building and deploying custom speech-to-text AI for healthcare. Learn hard-won lessons and a practical blueprint: curating domain-specific training data, fine-tuning open-weight models, validating non-deterministic outputs at scale, and shipping to production with optimized inference. Both teams share how AWS services reduced infrastructure complexity, accelerated iteration cycles, and scaled custom models across diverse real-world use cases — all while maintaining security and cost efficiency. Ideal for ML engineers, data scientists, and technical leaders exploring fine-tuning and production ML on AWS.

31. ISV209Intermediate

    From dev tools to customer value: BGL's agentic AI journey

    Australian fintech leader BGL demonstrates their systematic approach to scaling agentic AI. Starting with Claude Code on Amazon Bedrock for developer productivity, BGL built OpsGorilla, a Slack-integrated agent serving 200+ employees. BGL extended AI agents to customer-facing innovation. BGL's Roni AI autonomously drafts annual compliance work for Self-Managed Superannuation Funds, reducing accountants' workload from days to hours. Built on Claude Agent SDK and Amazon Bedrock AgentCore, BGL's implementation showcases practical architectural patterns for organizations scaling AI agents from developer tools through enterprise operations to customer solutions.

32. IND202Intermediate

    How Zuru Uses AI to Analyze TikTok Trends for Rapid Content Creation

    For modern consumer brands, winning means moving at the speed of culture. Zuru uses Amazon Bedrock and Twelve Labs to analyze up to 10,000 TikTok videos a day, rapidly identifying viral trends, emotional cues, and content patterns to create creator briefs in hours instead of weeks. Join this session to see how AWS gives Zuru a measurable edge, from 30 million organic views in seven days to 50x faster content creation, with industry peers now looking to replicate its speed-to-market advantage.

33. TNC301Advanced

    Using Tools and Agents in Generative AI applications

    Join us for an engaging session on AI Agents and Tools in AWS, where well explore how to build intelligent, autonomous systems using Amazon Bedrock and open-source frameworks. Learn about function calling, ReAct patterns, and AWSs comprehensive agent platforms. Well dive into practical demonstrations using Strands and CrewAI, and discover how to leverage protocols like MCP and A2A for seamless tool integration and agent collaboration. Perfect for developers looking to create production-ready AI solutions.

34. STP301Advanced

    AI-Native Remediation with Pleri: Your Security Engineer That Ships

    Most security tools find the problem and hand it to a human. Plerion closes the loop. In this talk, we'll show how Pleri, our AI security engineer powered by Amazon Bedrock, takes a critical cloud risk from detection to remediation without the alert-ticket-backlog cycle. Watch a top risk get prioritized, a ticket filed, a PR opened, and code-level remediation land in your environment. Re-define what it means to have an AI teammate that does the work, not just alerts and reporting.

35. DEV308Advanced

    AI Blast-Radius Reviews for AWS Changes Using Amazon Bedrock

    Cloud infrastructure changes carry hidden risks that manual reviews often miss. This session demonstrates how to build a pre-deployment blast-radius reviewer using Amazon Bedrock that analyzes infrastructure-as-code diffs, IAM policy changes, and deployment metadata to produce structured risk assessments in seconds. Attendees will learn how to design grounded AI workflows that identify affected services, security gaps, cost implications, and rollback considerations, and how to apply Bedrock guardrails for consistent, safe outputs. The session includes a live demonstration and covers practical patterns for integrating AI-generated assessments into existing engineering approval and governance processes without sacrificing speed or reliability.

36. ISV102Foundational

    From documents to voice - building AI products on AWS

    How Affinda leverages Amazon Bedrock (Claude), SageMaker, EKS & CloudFormation to deliver intelligent document processing at enterprise scale, cutting setup time and costs by 90% with 95%+ accuracy. This session will demonstrate how Affinda powers real-world AI product development from Affinda's Intelligfent Document Processing platform to Pathfindr's (acquired by Affinda) custom AI agents. The session will showcase the complete journey of building Honey Insurance's voice agent - Australia's first voice agent in financial services, and how the Affinda-AWS partnership enables rapid AI product development for Enterprises.

37. STP212Intermediate

    How Apate AI uses Amazon Bedrock and voice AI to catch scammers

    Scams are a global epidemic costing businesses and consumers trillions. Apate AI turns the tables on fraudsters by deploying lifelike conversational AI agents, powered by Amazon Bedrock and speech models on Amazon SageMaker bidirectional streaming, that engage scammers in real time to detect, divert, disrupt, and decode their tactics. In this session, learn how Apate AI converts every scam interaction into actionable intelligence and how to build your own voice AI agents on AWS.

38. IND301Advanced

    Stockland Empowers People with a GenAI Assistant Built on AWS

    Discover how Stockland, one of Australia's largest diversified property groups, built an intelligent AI assistant on AWS that puts enterprise knowledge at everyone's fingertips. This session explores a multi-agent system powered by Amazon Bedrock & Strands SDK and embedded in Microsoft Teams, that enables teams to streamline vendor management, automate routine tasks and accelerate decision-making. Learn how Stockland built intelligent workflows that transform procurement data into actionable insights, reducing manual effort while improving accuracy and compliance.

39. INO203Intermediate

    Behind the curtain: How Amazons AI innovations are powered by AWS

    Discover how Amazon leaders across Zoox, Prime Video, and Amazon Stores are leveraging AI to power their next-generation innovations with AWS and create better experiences for customers. Through three key stories discover how customer needs sparked transformative experiences: fan feedback revolutionising sports broadcasting with AI-powered highlights, shopping patterns evolving Amazons mobile commerce platform, and robotics and automation delivering advances in supply chain optimisation and fulfillment. Learn the best practices Amazon has applied using AWS that can help scale innovation in your organisation.

40. MAE205Intermediate

    AI at Speed of News: Unlocking Value from Media with Generative AI

    For media and communications organizations, the ability to rapidly discover, repurpose, and distribute content across platforms directly impacts revenue and audience engagement. This session examines how Generative AI is transforming content operations through intelligent metadata extraction, semantic search, and automated workflow orchestration. Using a case study from a global media organization managing 13 petabytes of content growing at 3,000 hours daily, we'll explore practical implementations using Amazon OpenSearch for multimodal retrieval, Amazon Neptune for knowledge graphs, and agentic AI for content assembly. Learn how organizations are achieving faster time-to-market, improved content monetization, and enhanced audience experiences through AI-powered content discovery and recommendation systems

41. STP101Foundational

    Driving Profitable Growth with Generative AI: From Prompt to Product

    Generative AI is the largest disruption to software company business models since the emergence of SaaS. In this workshop we'll cover best practices software companies use to take AI-native products from pilot to production, including identifying use cases that drive business value, features that accelerate adoption and pricing strategies that result in profitable growth. This will include an interactive session - so bring your ideas and collaborate with other startups to help find generative AI features that add value to your product

42. ISV101Foundational

    How AI is Transforming Pharmacy Care with Amazon Nova:MedAdvisor Story

    MedAdvisor, Australia's leading medication management platform connecting over 90% of community pharmacies, faced a critical challenge: pharmacists were losing hours daily to manual documentation, diverting time from patient care. To solve this, MedAdvisor built an AI-powered Scribe using Amazon Nova on Amazon Bedrock. The tool listens to pharmacy consultations in real time, transcribes conversations, and automatically generates structured clinical notes. Through iterative prompt engineering, output quality improved from 3.5 to nearly 4.5 out of 5, surpassing market alternatives. Now in beta across Australia, the solution went from concept to production-grade clinical documentation in under six months.

43. DEV309Advanced

    AI Outputs: Amazon Bedrock Structured Output in Production

    Parsing LLM responses as JSON worksuntil truncation, missing fields, or malformed output breaks your pipeline. This session examines Amazon Bedrock Structured Output, which enforces schema compliance at the model level rather than relying on prompt instructions. You'll learn how to define response contracts using JSON Schema, understand where native structured output differs from prompt-based approaches, and see practical patterns for integrating reliable model responses into production systems. Attendees will leave with concrete techniques for eliminating output validation failures, designing more resilient AI workflows, and understanding the architectural implications of treating model responses as typed, validated data rather than freeform text.

44. ISV104Foundational

    hipages Journey Towards an Agentic Engineering Organisation

    Discover how hipages, ANZ's leading online construction marketplace, redefined their software development lifecycle by embedding Claude Code on Amazon Bedrock into daily engineering workflows. Join this session to get practical insights into maximizing Claude Code on Bedrock, understanding the decision process behind selecting this solution, and learning how hipages is pioneering an AI-first strategy that's transforming operations across their entire business.

45. STP216Intermediate

    Building AI Agents: From Open-Source Frameworks to Production-Grade

    AI agents are moving from demo to deployment. Startups across ANZ are building production-grade assistants using open-source orchestration frameworks, fine-tuned foundation models, and GPU-accelerated inference on AWS and NVIDIA infrastructure. This panel explores what it actually takes to ship agentic use casesfrom choosing the right models and frameworks to managing latency, cost, and reliability at scale. We'll hear from AirTree VC on where the investment thesis is heading, from NVIDIA on how accelerated compute is shaping the agent stack, and from Heidi Health building and scaling these systems in production. Whether it's vertical agents for healthcare, customer support, or code generation, we'll focus on what's working, what's hype, and where the real startup opportunities lie in the agent ecosystem.

46. ISV213Intermediate

    From GRC Platform to AI-Native Risk Intelligence on AWS:Protecht Story

    Protecht, a global leader in enterprise risk management software, partnered with AWS and Caylent to build Cognita AI, an embedded AI assistant purpose-built for governance, risk, and compliance (GRC). Backed by a $280M PSG investment, Protecht built Cognita on a production-grade Amazon EKS foundation, integrating Amazon Bedrock and Anthropic's Claude models with a RAG architecture grounded in Protecht's proprietary GRC content. The result is a contextual, explainable, and auditable AI assistant that guides risk professionals through complex workflows, earning high accolades at the Gartner Enterprise Risk, Audit & Compliance Conference and setting a new benchmark for investor-grade, regulator-trusted AI in months.

47. INO202Intermediate

    Build and scale AI: from reliable agents to transformative systems

    Many teams move fast with agentic AI prototypes that impress in demos but stall in productionblocked by gaps in reliability, accuracy, and safety. In this session, AWS agentic AI technical leaders will help builders rethink how to build and scale production-grade, trustworthy agentic AI. Learn proven patterns to build and deploy agents that earn trust in the real world. See AWS agentic AI platform Amazon Bedrock AgentCore in action. Discover how AWS customers move fast from sparks of experiment to scaled AI-driven innovation with trust at the core, transforming industries.

48. MAE204Intermediate

    How Amazon Ads Creative Agent uses AWS to democratize ad creation

    Media advertisers see up to 25% higher engagement when delivering custom creative to relevant audiences, yet producing quality video ads traditionally requires weeks of expensive and specialized expertise. Discover the inner workings of Amazon Ads new AI Creative Agent, and how it's transforming the creative process by automating and enhancing the generation of multi-format ads to businesses regardless of their size or creative expertise. Explore how Amazon Bedrock, custom-built ML models, GPUs, and model evaluations are used to orchestrate and generate compelling ad creatives into full video productions with professional voiceovers from conversational natural language, while reducing creative development time.

49. SMB203Intermediate

    From Vision AI to Agentic AI: Real-Time Ops & Compliance in QSR

    Fingermark's Eyecue platform turns drive-thru video feeds into real-time operational intelligence for some of the world's largest QSR brands. Using hybrid edge-cloud architecture on AWS, they track every customer journeycapturing precise timing at order points, windows, and bayswhile keeping sensitive data at the edge. Now they're taking the next leap: agentic AI powered by Amazon Bedrock AgentCore. Autonomous agents automatically answer compliance questions"Are there spills Are staff following food handling protocols"replacing manual audits with continuous monitoring. See how a Kiwi company scaled from local innovation to global impact, and from computer vision to autonomous agents.

50. STP401Expert

    How WhiteHorse AI Deploys Openclaw Agents on AWS with Amazon Bedrock

    What if every small business could afford a chief of staff that never sleeps In this session, WhiteHorse AI shares how they build autonomous AI agents — "AI employees — that handle invoicing, email triage, lead follow-up, and customer inquiries 24/7.

One sharp, contrarian insight per session — the things teams don't think of unprompted.

Related topics