Architecting for the Unknown
In an environment of constant change and ongoing disruption, building systems that can adapt and endure is essential. This keynote explores the principles of ad...
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The Goal: Flow Architecture
When Eliyahu Goldratt wrote The Goal, he revealed how local optimizations, such as adding automation to one part of a process, can harm overall performance. Tod...
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Every Event, Everywhere, All at Once
Domain events, integration events, boundary events, event-driven systems, event sourcing, and event streaming—these concepts are central to modern software desi...
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A Practical Introduction to LangChain4j
Interested in adding AI capabilities to your Java applications? LangChain4j makes it simple to integrate large language models (LLMs) directly into your existin...
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Enterprise Architecture 2026–2028: AI-Native, Agentic, and Governed
Enterprise architecture is entering a new era defined by agentic AI, AI governance, confidential computing, and post-quantum cryptography (PQC), while sustainab...
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The AI-Native Codebase
AI coding assistants are transforming how software is written, but scaling their use across teams introduces new challenges in reliability, maintainability, and...
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Refactoring to Modernize Java Applications
Refactoring is essential for maintaining and modernizing Java applications, yet it often feels slow, risky, and time-consuming. While IDEs offer powerful refact...
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Goodbye Microservices, Hello Self-Contained Systems
Microservices promised scalability and agility, but for many teams, they have introduced operational overhead, complex debugging, and fragmented ownership. What...
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Computer Programming is Dead; Long Live AI-First Programming
The job market for computer science graduates is shifting rapidly, revealing a growing gap between academic training and industry expectations. Traditional prog...
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3rd Generation Agentic AI
AI models are advancing rapidly, yet the systems around them remain fragile. Each backend change risks breaking an AI client, while on the web, servers evolve s...
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From Noise to Signal: Using MCP Servers for AI-Driven Alerting and Monitoring
Traditional monitoring and alerting systems generate too much noise and too little insight. They detect issues but often miss the context that matters most. The...
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Beyond Transformers: State Space Models as the Next Paradigm in AI
State space models (SSMs) are emerging as a compelling alternative to transformer-based architectures, providing a mathematically grounded and computationally e...
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Simpler Java Build Tools with Object-Oriented Programming
Java as a language is fast, expressive, and well-supported by IDEs, but the same cannot always be said of its build tools. Why is build tooling such a challengi...
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The Architect’s Dilemma: Control vs Convenience
Few decisions challenge software architects more than choosing between control and convenience. Should you host PostgreSQL on EC2 for full control, use Amazon R...
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Tuning the JVM for Performance: 10 Optimizations Every Developer Should Know
Significant performance gains, often 10 to 40 percent, can be unlocked in Java workloads without touching a single line of source code. The JVM comes packed wit...
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Power and Perils of Vibe Coding
Vibe coding uses intuition, AI assistance, or rapid iteration to build software without traditional design formality. It can feel liberating and fast, but it co...
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Keep It Dull, Keep It Running: Runbooks and the Religion of Boring Platforms
Nobody dreams of a platform that is exciting at 2 a.m. In incident management, boring is beautiful. When the pager goes off, what matters most is not innovation...
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Developers: Contribute to Java Now!
The Java ecosystem thrives because of a global community built on collaboration, mentorship, and contribution. With over 30 years of continuous innovation and m...
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A Tale of Two Systems: Design and Reality
Every architect knows the feeling: the system you designed and the one that was actually built rarely look the same. In fast-moving environments, where speed of...
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Creating Architectures with the Aid of AI
The excitement around AI continues to grow, but can AI actually help us create software architectures? This session explores the opportunities and risks of usin...
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Design Patterns for Software Diagramming
Clear communication is essential to successful software development, and effective diagrams play a major role in sharing understanding within teams. Yet diagram...
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Data Architecture for AI
AI conversations often focus on models, yet the real foundation of intelligence lies in data architecture. Modern AI systems remain fragile because they lack co...
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AI Inference at Scale: Reliability, Observability, Cost, and Sustainability
AI inference has become the new production workload: always on, cost-intensive, and increasingly complex. Teams face unpredictable latency spikes, runaway GPU c...
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AI-First Software Delivery: Superpowers, Adoption Challenges, and the Path to Software 3.0
AI is reshaping the entire software delivery value chain, from market research and ideation to coding, deployment, and operations. This session explores what it...
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The Past, Present, and Future of Null-Safety in Java
NullPointerExceptions have long been a source of frustration for Java developers, turning minor oversights into production issues. Null-safety in Java, however,...
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Intelligent Java Apps: Agent Patterns, MCP, and the Future of AI-Native Design
As AI moves from experimentation to production, Java developers face a new paradigm: building intelligent, context-aware systems that can reason, interact, and ...
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Agents in Action: Building Autonomous Java Systems That Don’t Break in Production
Agent frameworks promise reasoning and autonomy, but enterprise environments demand more than impressive demos, they require reliability, observability, and con...
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Who Owns the Code That AI Writes
With more than 80 AI coding tools available today, and projections exceeding 270 by 2027, product managers, designers, and other “citizen engineers” can now gen...
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Context Engineering for Everyday Software Development
AI coding assistants are now a standard part of modern software development, yet their conversational interfaces introduce a subtle but serious problem: they en...
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Architectural Decision Records: The Why and How
Software development is filled with decisions, and over time, it is easy to forget why those decisions were made. Architectural Decision Records (ADRs) provide ...
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Human-AI Collaboration: Making Prudent Use of AI in Development
AI offers tremendous potential, but using it wisely is essential for both developers and organizations. This workshop begins with a brief discussion on the ethi...
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Responsible GenAI for Java Developers: Fast Doesn’t Mean Reckless
As generative AI capabilities accelerate, the real challenge for enterprise teams isn’t building faster, it’s building responsibly. This session focuses on how ...
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Rethinking Software: The AI-Native, Event-Driven, Multi-Agent Paradigm
Software is undergoing a foundational shift, from deterministic systems built through static pipelines to adaptive, event-driven networks orchestrated by intell...
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Modern Java Patterns in Practice: Records, Pattern Matching, and Switch (with Real Refactors)
Modern Java has evolved into a powerful language for expressive, concise, and safe code, thanks to Records, Pattern Matching, and the new Switch patterns. But u...
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Asynchronous Programming in Spring: Past to Present
Building scalable Spring applications often depends on choosing the right approach to asynchronous programming. In the past, developers relied heavily on Reacti...
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Hands-on Unit Testing with JUnit 5/6
Unit testing remains one of the most effective ways to ensure code quality and maintainability, and JUnit continues to be Java’s most trusted framework for it. ...
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Innovation: Why the Majority Is Always Wrong
If everyone agrees with you, you are probably not innovating, you are conforming faster. History’s real breakthroughs did not come from consensus but from heret...
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Prototype to Production: Building Enterprise MCP and AI Agents with Templates
More than 95 percent of GenAI pilots fail to reach production not because of capability, but because of missing engineering discipline. This session presents a ...
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The Intersection of Architecture and AI
Will Generative AI replace software architects? The short answer is no. The longer answer is that it depends on how architects use it. This keynote examines the...
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Gearing Up to Java 25: Key Language Features
Once known for its slow evolution, Java has transformed into a fast-moving, forward-looking language. With frequent, incremental releases, it continues to deliv...
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Architecture in the Age of AI
As code generation becomes increasingly automated, the role of developers and architects is changing. The challenge is no longer about making AI write more code...
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Building LLM-Powered Agents with Real-Time Reasoning Loops
Generative AI systems are evolving beyond single-shot prompts toward closed-loop reasoning, a structured process of planning, acting, observing, reflecting, and...
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Building AI Agents with Spring and MCP
Integrating AI into enterprise systems has traditionally been complex and specialized, but new tools are changing that. Spring AI and the Model Context Protocol...
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Putting the Human in the Center of Your AI Efforts
AI technologies are advancing rapidly, yet many organizations still struggle to turn them into meaningful value. At the same time, people remain uncertain and w...
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Finding and Fixing Issues with Legacy Code using AI
Every developer eventually faces the challenge of maintaining legacy code: systems written by others, often under time pressure, and difficult to understand or ...
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Surviving Complexity Through Software Design
Modern software teams face unprecedented complexity: multiple tech stacks, DevOps pipelines, observability systems, and constant delivery pressures. The result ...
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GraphRAG and Explainable AI: Building Trustworthy LLM Outputs
Most enterprise LLM failures are not technical, they are trust failures. Models hallucinate, lose alignment with source truth, or generate answers with no trace...
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7 Technology Trends That You Need to Know
AI is transforming software and systems at every layer, but real mastery lies in understanding the deeper shifts shaping this new stack. This talk explores seve...
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From Props to Prompts – Bridging React and AI Workflows
React has long been built on the idea of props, static inputs passed at build time to define component behavior. But in a world of adaptive, AI-driven applicati...
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Granularity and Communication in Microservices Architectures
Many teams understand how to structure microservices but struggle with how those services should communicate. The result is often a distributed “Big Ball of Mud...
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Creating Evolutionary Architecture
How should architecture evolve as requirements change? A good architecture must stay relevant to the application it serves, but knowing when and what to adapt i...
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How Google Built a Consistent, Global Authorization System, and You Can Too!
Google Zanzibar is the global authorization service that powers access control across products like Google Docs, YouTube, and Cloud IAM. Designed to handle more...
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The Digital Workflow is Obsolete: How to Survive the End of the Canvas
The way digital products are designed and delivered is changing fast. The traditional canvas-to-code model, where visual mockups are handed off to engineers, is...
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Practical Python AI in Java with GraalPy
AI innovation in the Java ecosystem is accelerating through projects like LangChain4j, Spring AI, and llama3.java, yet Python remains the powerhouse for AI, mac...
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Lost Developer Wisdom
In our rush toward the future, the software industry often forgets its past, and the lessons that came with it. In this live storytelling session, Michael Cardu...
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Harnessing Event-Driven and Multi-Agentic Approaches for Efficient AI Data Flows
Generative AI applications excel at isolated tasks like zero-shot and one-shot problem solving, but struggle with the complexity of real-world business workflow...
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Shaping Intelligent APIs: Scaling LLMs, Open Ecosystems, Enterprise AI
As Large Language Models (LLMs) become core to enterprise transformation, the ability to design and scale AI-powered APIs has never been more crucial. In this s...
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Lessons from Building Deep Research Agents in Production
Deep research is complex. Data is scattered across systems, insights are buried in text and tables, and most LLM demos stop at shallow Q&A. In production enviro...
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AI-First Repositories: Architecting Your Codebase for AI Collaboration
AI code assistants often fall short not because the technology is weak, but because they lack access to the context developers rely on. This session introduces ...
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How to Be Indispensable in a Post-AI World
AI will not take all developer jobs, but it will transform them. Generative AI is already reshaping software development by automating the easiest part of the w...
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Spring into AI
If you are building applications with Spring and want to integrate AI capabilities, this session offers a practical, example-driven introduction to Spring AI. Y...
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AI Communication Patterns: Communicate 10x Faster?
We often hear about the “10x developer,” but can AI help you become a 10x communicator? In this session, Jacqui Read explores the patterns and antipatterns of u...
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How Generative Tools Are Re-Architecting the Software Engineer’s Role
Large language models now write boilerplate, propose tests, and even suggest architectures, but these gains introduce new risks, governance challenges, and skil...
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Context Engineering: Connecting the Dots with Graphs
AI systems require more than intelligence; they require context. Without it, even advanced models can misinterpret data, lose important details, or reach conclu...
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Architecture as Code
Even the most well-designed architecture can fail when critical changes go unnoticed during implementation. The result is software that does not scale, is diffi...
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Rethinking React Architecture - From Hooks to Remote Contexts
React’s context API, hooks, and Suspense work well for small to medium applications, but as systems grow across multiple micro-frontends, deployment cycles, and...
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Develop Through Dialogue: Keeping Humans in the Loop
As AI becomes integral to software development, keeping humans actively involved is essential for ensuring ethical, accurate, and context-aware systems. This se...
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The Winning Formula: Human Ingenuity Meets Software Development
From pioneering “Moneyball” sports analytics to uncovering the stories of forgotten heroes through AI, Ari Kaplan has spent his career at the intersection of da...
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From Black Box to Blueprint: AI-Assisted Legacy Reverse Engineering
Every enterprise has mission-critical legacy systems that no one fully understands anymore. Documentation is missing, experts have moved on, and every change fe...
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Extending Functional Pipelines with Gatherers
The Java Stream API offers a rich set of operations, filter, map, takeWhile, limit, and many others, to create expressive functional pipelines. However, not eve...
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Your API Is Not Ready for AI (Lifecycle Readiness Guide)
APIs built for humans often break when consumed by AI agents. Documentation meant for developers does not help large language models (LLMs) or autonomous system...
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How to Prevent AI Agents from Accessing Unauthorized Data
As AI systems move into production, data security and access control become critical. In the era of AI agents, enterprises must move beyond experimentation to D...
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Taming Chaos: Deterministic Simulation Testing for Distributed Systems
Testing distributed systems is notoriously difficult. Concurrency bugs, network partitions, and clock skew often lead to flaky tests and elusive failures that a...
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Beyond Local Tools: Deep Dive into the Model Context Protocol (MCP)
The Model Context Protocol (MCP) is redefining how AI systems connect to external data, APIs, and tools, moving beyond local integrations toward secure, scalabl...
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Distributed vs. Universal Data Model: Essentials for Distributed Architectures
When transitioning from a monolith to a modular monolith or microservices architecture, breaking apart the codebase is challenging, but handling data is even ha...
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The Art of Being an Architect
The hardest part of software architecture is not the technology, it is the people. Every architecture succeeds or fails based on its ability to influence behavi...
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Securing LLMs in Production: From OWASP Top-10 to Guardrails that Work
Large Language Models have expanded what’s possible, and what’s vulnerable. New risks like prompt injection, data exfiltration, insecure plugin calls, and model...
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Spring AI + MCP: Building the Missing Bridge Between Java Apps and AI Agents
The Model Context Protocol (MCP) is rapidly becoming the standard for connecting AI agents to external tools, APIs, and data sources. For Java developers, this ...
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Rethinking Engineering Roles As We Welcome Our Machine Overlords
AI is reshaping how software gets built. Designers, product managers, and even non-technical teams can now prototype, build, and ship without writing a single l...
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