![[VDBUH2026] Alexander Chatzizacharias: How to build your own fun and absurd pair programmer @DevoxxForever](https://i.ytimg.com/vi/jnPtYh-n0LM/maxresdefault.jpg)
Uploaded May 2026 | Updated September 2026, 3 weeks ago
Tired of AI assistants that are always so boring and soulless? Alexander was. So, he decided to build his own. An AI assistant with personality, flair, and a healthy dose of sarcasm. Imagine a pair programmer that offers sarcastic feedback, makes absurd suggestions, and threatens to blow up your code when it disagrees with your changes. And when things get too quiet, it might even challenge you to a game of tic-tac-toe.
This session is for anyone who believes the best way to learn new technologies is by playfully breaking them. If you’re curious about LLMs and agents beyond the typical use cases, this talk is for you. You’ll leave with practical insights into building your own agentic LLM workflows using Spring Boot, vector databases, and locally running models. Alexander will talk about Retrieval-Augmented Generation (RAG) flows that feed LLMs the right context, multi-vector search for fast context retrieval, and Model Context Protocol (MCP) integrations that let the assistant directly meddle with your file system.
Come to learn, chuckle, and get inspired to create your own dysfunctional digital sidekick.
Tired of AI assistants that are always so boring and soulless? Alexander was. So, he decided to build his own. An AI assistant with personality, flair, and a healthy dose of sarcasm. Imagine a pair programmer that offers sarcastic feedback, makes absurd suggestions, and threatens to blow up your code when it disagrees with your changes. And when things get too quiet, it might even challenge you to a game of tic-tac-toe.
This session is for anyone who believes the best way to learn new technologies is by playfully breaking them. If you’re curious about LLMs and agents beyond the typical use cases, this talk is for you. You’ll leave with practical insights into building your own agentic LLM workflows using Spring Boot, vector databases, and locally running models. Alexander will talk about Retrieval-Augmented Generation (RAG) flows that feed LLMs the right context, multi-vector search for fast context retrieval, and Model Context Protocol (MCP) integrations that let the assistant directly meddle with your file system.
Come to learn, chuckle, and get inspired to create your own dysfunctional digital sidekick.
![[VDBUH2026] Alexander Chatzizacharias: How to build your own fun and absurd pair programmer](https://i.ytimg.com/vi/jnPtYh-n0LM/mqdefault.jpg "[VDBUH2026] Alexander Chatzizacharias: How to build your own fun and absurd pair programmer
Tired of AI assistants that are always so boring and soulless? Alexander was. So, he decided to build his own. An AI assistant with personality, flair, and a healthy dose of sarcasm. Imagine a pair programmer that offers sarcastic feedback, makes absurd suggestions, and threatens to blow up your code when it disagrees with your changes. And when things get too quiet, it might even challenge you to a game of tic-tac-toe.
This session is for anyone who believes the best way to learn new technologies is by playfully breaking them. If you’re curious about LLMs and agents beyond the typical use cases, this talk is for you. You’ll leave with practical insights into building your own agentic LLM workflows using Spring Boot, vector databases, and locally running models. Alexander will talk about Retrieval-Augmented Generation (RAG) flows that feed LLMs the right context, multi-vector search for fast context retrieval, and Model Context Protocol (MCP) integrations that let the assistant directly meddle with your file system.
Come to learn, chuckle, and get inspired to create your own dysfunctional digital sidekick.")
![[VDBUH2026] Victor Botan - Scaling the Future: Lakehouse Architecture and OpenSource Collaboration](https://i.ytimg.com/vi/lW6VqE3HMvQ/mqdefault.jpg "[VDBUH2026] Victor Botan - Scaling the Future: Lakehouse Architecture and OpenSource Collaboration
Modern data platforms demand scalability, flexibility, and interoperability—capabilities that traditional architectures often fail to deliver. The lakehouse paradigm bridges this gap by combining the strengths of data lakes and data warehouses into a unified, performant system.
This talk explores how open source technologies like Apache Spark, Delta Lake, and Apache Iceberg enable scalable lakehouse architectures. It also highlights the strategic value of contributing back to these ecosystems—driving innovation, improving reliability, and shaping the future of data engineering. Attendees will leave with practical insights on building resilient data platforms and leveraging open source as a force multiplier.")
