Artificial neural networks over the course of the last 5 to 6 years have grown so large and complex that humans are losing the ability to understand and interpret this artificial brain. If this continues, our society can face disastrous consequences. This talk sheds light on how these networks work and, drawing from Shayan's personal research, how we can develop that understanding for the future ahead.
Architecture diagrams can explain what a system looks like, but they rarely explain how teams should evolve it safely. Python systems often grow through rapid iteration, integration needs, and team-specific decisions, and over time the challenge becomes less about drawing the right diagram and more about creating governance that helps people make better changes. This talk reframes software architecture as a living decision system, built around decision records, ownership boundaries, integration contracts, stakeholder alignment, and change readiness.
Keeping with tradition, we hosted our 3rd July Lightning Talks meetup. We had five speakers present on a wide range of topics.
In the past 10 years, I've mentored several really amazing young humans. I'm also a product of a lot of informal mentoring. Let me opine on what I've learned being on both sides of the desk and my general advice to anyone, regardless of your goals. We'll talk about:
This talk is the story of how a small idea grew into a real, working social platform built around tiny 300-character posts. We built it mostly out of curiosity- using Python, a bit of GenAI, and a lot of trial and error. Along the way, we learned what actually matters when you're building something for real people, not just for yourself.
In October 2025, Python 3.14 was released and with it a cool new way to create t-strings, which promise to help python developers write better, and safer python code. While on the surface, they share a similar name to f-strings, the way we use them is quite different. This talk explores what they are, how they work, who they are for and how they will help python developers write safer code.
In an era where enterprises generate massive, complex streams of unstructured data from documents and logs to images, audio, and video, traditional search and analytics fall short. This session explores a transformative, production-ready framework for Multimodal Retrieval-Augmented Generation (RAG), designed to redefine how organizations unlock insights from every data modality. Discover how an intelligent agent, built using cutting-edge encoders and composable AI models, empowers organizations to understand, retrieve, and reason over diverse information in real time.
Merge Conflicts in software programming occur in 20% of all merges in open-source projects, incurring a median resolution time of ~6 minutes for a single conflict at best, or multiple days at worst. This talk will touch upon LLM Evaluations, Azure OpenAI Fine-Tuning, AI-generated resolution explanations, and usage of multiple Python SDKs to craft a scalable LLM-powered Merge Conflict Resolver. Our results indicate up to 125% performance improvement over vanilla LLM resolution accuracy.
Learn how to maintain code quality without sacrificing performance. This presentation explores SAST, SCAT, and SCA concepts, then introduces modern tools like Ruff and Pyright that make formatting, linting, and type checking simple and almost instantaneous.
Python Decorators are a cool, pythonic way to inject context into your Python code. In this talk we'll walk through some interesting ways to leverage them and a couple places where you're better off not using them.