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This talk will explore the main architectural blueprints for Java GenAI Applications, offering insights on addressing the most typical requirements for such applications, approaching recurrent problems, and breaking them into manageable components to unlock the potential of LLMs. The talk comprises the most common design patterns for building GenAI solutions, and some examples with Java and Kubeflow for MLOps will be presented as well.
We make decisions all the time in software - our architectures are the sum of them; both conscious and unconscious. In this talk I’ll describe what architectural decisions are, and the different ways that we approach them (individually and collectively) making clear the pros and cons of each. I’ll then compare them all, concluding by describing the ideal characteristics of a decision-process for modern software development.
Software architects will not be replaced by Generative AI or LLMs. They will be replaced by software architects that know how to leverage Generative AI and LLMs. For the last two years, Avraham has been on a journey using generative AI to augment the way he does architecture and makes architecture decisions. Along the way, Avraham has learned so much both about generative AI and about himself as an architect and as a person. In the talk, Avraham invites you to join him on his journey. This talk will equip you with the knowledge and tools to start on your own adventure to leverage the power of GAI, elevate your architectural practice, and hopefully stay ahead of the curve.
Micro-Frontends are the distributed architecture for the user interfaces that are solving not only technical but also organizational challenges. In this session, you will learn the most common anti-patterns I've seen in the past 9 years of implementing and consulting worldwide companies in their journey into the micro-frontends architecture. Whether you are an expert or a newbie, in this talk, you will learn how to properly structure your micro-frontends architecture and how to avoid common mistakes while building micro-frontends.
Software engineering challenges stem from two constraints: humans' limited cognitive capacities and the necessity for human effort in modifying software. Innovations like OOP, Agile, DDD, and Team Topologies serve to thrive within these constraints. As AI evolves to regenerate and redeploy entire systems, it promises a profound paradigm shift in software engineering, altering our work and software's role in the business ecosystem. This talk delves into AI's potential to revolutionize software engineering and offers insights into the future of AI-driven software development.
Every software engineer and architect strives to design modular software systems and avoid complexity. Yet, frequently, the outcome is the opposite: what promised to be an elegant, well-thought architecture results in another big ball of mud. Why does this pattern persist and how do we learn not to repeat it? In this talk, we will explore the nature of modularity and complexity, including their surprising similarities.You will learn what forces drive software design towards modularity or complexity, and the effects these forces have on your organizational design. Understanding the relationship between social and technical design principles will make you more effective in architecting systems that thrive over time.