Opening remarks from James Bunting, CEO at Leighton
Microservices architecture is evolving. AI agents are reshaping how backend systems are built and consumed. Discover Agentic Microservices, a new evolution of microservices architecture, along with emerging patterns such as Microservices as Tools (MAT) and Agentic Monoliths. We also explore why serverless is a natural fit for agentic architectures and watch an agentic microservice in action.
The era when organizations relied solely on skilled programmers to write countless lines of code is fading. Developers who once enjoyed crafting well-structured and well-documented code in their preferred programming languages are now openly turning to their Generative AI coding partners to generate code. Here, language is no longer a barrier.
A practical guide to building secure, scalable, and high-performance multi-tenant APIs using AWS serverless architecture, covering tenant routing, authentication, data isolation, quotas, and observability.
Exploring how IAG Loyalty separates an AI control plane from an agent harness to enable governed, scalable, and observable GenAI adoption across the enterprise.
An insight into G-P’s AI Development Life Cycle, showing how a people-first operating model combined with multi-agent workflows can help teams adopt AI at scale while maintaining engineering rigour and quality.
Learn how to build and operate event-driven architectures, covering observability, testing, schema evolution, error handling, integration, idempotency, documentation, and governance.
An AWS enterprise customer’s journey to securely scaling Agentic AI on AWS, covering enablement, adoption patterns, guardrails, reporting, and logging using Amazon Bedrock and Bedrock AgentCore.
A real-world look at orchestrating multi-agent AI workflows with AWS Lambda Durable Functions, showing how to build resilient, long-running chat experiences with Amazon Bedrock agents and asynchronous human interactions.
Closing remarks from James Bunting, CEO at Leighton
Discover how to use autonomous AI pentesters to test infrastructure security at scale, covering safe deployment, security controls, agent limitations, stopping conditions, and the operational challenges of AI-driven security testing.
An overview of how AWS data services can provide AI agents with trusted, company-specific knowledge from databases and data lakes, while keeping data quality high and controlling token costs.
How the AI-Driven Development Lifecycle can help teams build production-ready software faster without compromising quality, using structured AI workflows and a real-world case study.
A hands-on demonstration of building an MCP server with Spring Boot and Spring AI, showing how to securely connect AI models to local tools, databases, APIs, and backend infrastructure.
A real-world case study of building a production-ready dog training platform in just five weeks using AWS serverless, infrastructure as code, and AI, exploring rapid delivery, architectural trade-offs, and scalability.
A practical look at using AWS S3 Vectors, Annotations, and Metadata to help AI agents turn unstructured files into searchable compliance data and answer audit questions accurately.
This session explores how teams can modernise legacy applications faster using AWS Kiro and AI-powered agentic engineering. By combining specification-driven development with AI engineering agents, the talk will demonstrate how organisations can accelerate delivery, improve software quality and reduce the risks associated with complex transformation programmes.
A guide to securely running autonomous AI agents using isolation, secrets management, egress controls, and lifecycle management to prevent threats such as prompt injection, data exfiltration, and lateral movement.
How Pulumi brings infrastructure as code into familiar programming languages, making it easier to define and manage AWS infrastructure.
Learn how Chaos Engineering and Amazon Fault Injection Service can help enterprises test, strengthen, and demonstrate the resilience of their infrastructure, applications, and systems.
Learn how to build a serverless system that automatically handles out-of-hours customer Slack messages, reducing unnecessary on-call alerts while maintaining reliable monitoring, security, and incident visibility.
Insights to using Strands SDK and OpenTelemetry to monitor AI agents, providing visibility into agent loops, tool calls, latency, token costs, and hallucinations in serverless environments.
Exploring how CDL’s journey from AI coding assistants to an AI-Driven Development Lifecycle, exploring how context, knowledge retrieval, governance, and quality can enable AI-native software development at scale.
A look at PwC’s Orchestrated Agentic Operating Model (OAOM) and how it helps organisations redesign work, decision-making, governance, and accountability around human and AI collaboration.
A leadership perspective on moving beyond cloud migration to building adaptable organisations, covering strategy, team design, platform thinking, transformation, and the changing role of technology leaders in an AI-driven world.
A closer look at how AI agents are transforming commerce through autonomous, intent-driven purchasing, exploring the emerging agentic commerce landscape and what it means for organisations.
This talk explores the rise of open-weight AI models, why they’re challenging proprietary models, and the practical considerations for enterprises looking to deploy them in production.
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