Alexander Lehmann
Software Architect @ One.O (OTTO Group)
Dresden, Germany
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Alexander studied Information Systems Technology in Dresden and has worked in the local software industry for over ten years. In his current position, he works on customer benefits for the OTTO marketplace, using the latest technology to compete with Amazon's overwhelming eCommerce market share.
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Serverless - A big failure?
In 2023, an Amazon Prime Video team published a blog post about how they saved costs and increased scalability by migrating away from a serverless architecture. Does this mean serverless is a failure if even Amazon is moving away from it? To address this question, we will explore how a serverless architecture is effectively used at OTTO's marketplace to select customers for discounts and benefits. We'll also discuss why the Amazon Prime Video team made the right decision by migrating away from serverless, highlighting the different needs and contexts of each use case. By the end, you'll be able to decide for yourself when a serverless architecture is the right choice and when it's better to opt for more traditional technologies.
Software 3.0: Generating High-Quality Business Applications from Natural Language
The future of software development is here. Imagine generating entire, high-quality business applications from simple natural language requirements, bypassing the traditional complexities of manual coding. This session unveils "Software 3.0," a groundbreaking approach leveraging advanced AI to redefine how we build enterprise solutions.
We'll dive into a live project that demonstrates the power of AI in adhering to fundamental architectural principles like Onion Architecture and Domain-Driven Design (DDD), ensuring the generated code is not just functional, but maintainable, scalable, robust and secure. Discover how a prototype of an AI agent framework is already capable of fully generating itself from its own requirements – a testament to its self-sustaining potential.
This session will explore:
The paradigm shift from manual coding to AI-driven software generation.
How AI can be engineered to consistently produce high-quality code adhering to best practices (Onion Architecture, DDD) and security constraints.
A practical look at a self-generating prototype.
Our vision for the future, including automated, zero-operational-effort deployment to serverless cloud environments and the exciting prospect of generating graphical user interfaces directly from natural language.
Join us to explore how "Software 3.0" promises to dramatically reduce development cycles, enhance code quality, and free up developers to focus on higher-level problem-solving, paving the way for a truly intelligent software factory. This isn't just about writing code faster; it's about building better software, more intelligently.
How to make your Business Processes AI-ready? A Tale of digital Transformation
In the rush to embrace Artificial Intelligence, many organizations overlook a crucial reality: their existing business processes are far from ready for AI integration. When core operations still rely on emailed Excel sheets, manual data compilation, and disconnected systems, even the most sophisticated AI solutions cannot deliver their promised value.
This presentation takes you on a journey through the essential stages of digital transformation that must precede successful AI adoption. Through practical examples, we'll explore the path from manual, unstructured processes to AI-ready operations, highlighting both the pitfalls to avoid and the milestones to achieve.
A significant portion of our journey focuses on the critical role of development teams in this transformation. We'll examine how to build the right foundations: maintaining clean software architecture, integrating technical expertise early in requirements gathering, and striking the delicate balance between business demands and technical sustainability. The narrative extends to organizational aspects, demonstrating how domain-driven team structures and business-aligned decision-making (rather than politically motivated choices) create the fertile ground needed for AI readiness.
This session is designed for executives and project leaders navigating the complex landscape of business modernization. It provides particular value for decision-makers seeking to understand how to prepare their organizations and development teams for the meaningful integration of AI technologies, moving beyond the hype to create genuine business value.
GenAI 101
If you want to understand the current state of the art in generative AI technology, this session is for you.
We will start with LLM Basics: How do Large Language Models (LLMs) work internally (at a high level of abstraction)? How does the API of an LLM look like, and what are its limitations? How do "reasoning models" work?
Then we'll visit the peripherals of a LLM: What is Retrieval Augmented Generation (RAG)? What is "tool calling"?
Before coming to AI Agents answering the questions: What defines an AI Agent? How do current state-of-the-art AI agents function? What's the Model Context Protocol (MCP)?
We will conclude the session with a practical example of how an internal AI agent for a software development team could look like. We will also give away some lessons learned about AI use cases and their pitfalls.
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