GDG on Campus Texas Tech University - Lubbock, United States
DevCon 3.0 is the annual developers conference organized by the Google Developers Student Club at Texas Tech University ...
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DevCon 3.0 is the annual developers conference organized by the Google Developers Student Club at Texas Tech University and is one of the largest student-led technology conferences in West Texas. The event brings together students, developers, and technology enthusiasts for a day focused on learning, innovation, and career development in the tech industry.
DevCon provides a platform for students to explore emerging technologies, discover new areas within computing, and gain valuable insights into navigating careers in technology. Through engaging talks and discussions, attendees will learn about current trends in software development, artificial intelligence, machine learning, and other rapidly evolving areas of technology.
The conference aims to inspire curiosity, encourage collaboration, and connect students with professionals who are actively shaping the future of technology. DevCon also serves as an opportunity for attendees to build meaningful connections, exchange ideas, and become part of a growing developer community.
Students from all majors and experience levels are welcome to attend. Whether you are just beginning your journey in technology or looking to deepen your knowledge and expand your network, DevCon offers an inclusive environment where everyone can learn, grow, and connect!
In this session, we’ll build a distributed pipeline that reviews videos at scale. The system breaks the problem into stages—audio transcription, on-screen text extraction, and visual analysis—and combines the results to make approval decisions based on rules for things like toxic language, hate speech, and personally identifiable information (PII).
We’ll walk through how the pipeline is structured, how stages communicate, and how results are aggregated into a final decision. The focus is on orchestration, consistency, and handling conflicting signals across steps.
You’ll see practical patterns for designing distributed systems that scale with demand, remain predictable, and support evolving moderation rules over time.
Generative AI has evolved at an incredible pace: from chatbots that surprised the world to intelligent systems that can reason, use tools, and interact with the digital world. In this talk, I will tell that story through the major milestones of the last few years, including ChatGPT, GPT-4, open models, reasoning models, agents, and MCP. We will also look at how these breakthroughs changed the industry, influenced what companies are building, and reshaped the skills that matter for the next generation of engineers.
For students, this is not just a story about AI’s past; it is a guide to understanding the future they are stepping into and the roles the industry increasingly demands.
In this session, Sachin will share how his approach to building and understanding systems has evolved since graduating from college and working on real-world production systems.
In school, the focus is often on writing correct code, optimizing algorithms, and solving well-defined problems. In industry, however, engineering is often about making good decisions under constraints, working with ambiguity, handling failures, and understanding how different parts of a system interact over time.
Through concrete examples, Sachin will walk through how he breaks down systems today, reasons about trade-offs like latency and reliability, and approaches situations where there isn’t a single “right” answer. He’ll also highlight key mindset shifts that weren’t obvious as a student.
This session aims to give students a realistic picture of how engineers think in industry and provide a mental framework they can start building even before they graduate.
The demo session will guide you from an introduction to the Google Antigravity IDE to developing a custom application. The initial application can be further enhanced to add more features later. The IDE not only builds but also auto tests in the agent-controlled browser. Documentation: Yes, it generates a complete plan and artifacts including test screenshots. That’s a mind-shift in how applications will be built, with multiple agents working on separate tasks simultaneously, playing different job roles and you the builder, are in charge of all.
Have you ever wondered how massive distributed systems handle millions of events in real-time? For years, traditional message queues handled this by passing transient messages between services. But as data scale exploded, the industry had to evolve from simple queuing to persistent message streaming giving rise to append-only log architectures like Apache Kafka. In this session, we'll break down this critical shift, starting from the ground up to explain why modern microservices desperately rely on high-throughput streaming infrastructure to survive. But what happens when the industry standard becomes the bottleneck? Enter Apache Iggy. Drawing on my experience as a core contributor, I'll take you under the hood of this next-generation, ultra-low latency streaming engine. We'll explore the mechanics of high-performance infrastructure and see exactly why Iggy is fundamentally faster: leveraging Rust, thread-per-core architectures, and lock-free processing to easily handle over a million messages per second without the heavy JVM overhead or garbage collection pauses of older systems. Finally, we'll transition from raw performance to practical deployment by introducing LaserData, a fully managed, cloud-native implementation of Apache Iggy. We'll discuss how LaserData strips away infrastructure complexity so developers can harness next-generation streaming speed without the operational headaches. Whether you are a student or an entry-level engineer, you will leave this talk with a solid understanding of modern event streaming and the tools powering the fastest systems in the world.
April 8 – 9, 2026
10:30 PM – 1:00 AM (UTC)
