The QCon San Francisco 2025 conference, set to take place from November 17-21, is rapidly approaching and generating considerable excitement in the tech community. As a member of the program committee, I’ve had the privilege of participating in the meticulous process of curating tracks, selecting expert hosts, and designing a cohesive schedule for the event. This year, we’re focusing on the real-world challenges faced by software leaders and practitioners, making it a must-attend for anyone involved in tech.
With the pervasive influence of AI across various sectors, it’s no surprise that many of the 15 curated tracks revolve around AI-related topics. For those of us entrenched in machine learning infrastructure and passionate about artificial intelligence, the lineup includes some particularly compelling sessions. Here’s a curated list of my top picks, presented in no particular order:
- “Accelerating LLM-Driven Developer Productivity at Zoox” by Amit Navindgi at Zoox. This session offers a practical blueprint filled with tangible ideas and organizational strategies for scaling an organization’s AI capabilities.
- “Engineering at AI Speed: Lessons from the First Agentically Accelerated Software Project” by Adam Wolff at Anthropic. An exploration of the architectural decisions made in Claude Code that prioritize speed over complexity, providing invaluable insights into effective engineering practices in the age of AI.
- “Deep Research for Enterprise: Unlocking Actionable Intelligence from Complex Enterprise Data with Agentic AI” by Vinaya Polamreddi at Glean. This case study discusses the development of an agentic AI system designed to extract actionable intelligence from vast enterprise data, showcasing advanced training methods and scalable design.
- “The Future of Engineering: Mindsets That Matter When Code Isn’t Enough” by Ben Greene at Tessi. This talks about the evolving role of engineers and the necessity of rethinking engineering mindsets beyond coding expertise to remain relevant.
- “Dynamic Moments: Weaving LLMs into Deep Personalization at DoorDash” by Sudeep Das and Pradeep Muthukrishnan at DoorDash. A deep dive into how DoorDash is transforming personalization through a seamless integration of large language models (LLMs).
- “Designing Fast, Delightful UX with LLMs in Mobile Frontends” by Bala Ramdoss at Amazon. This session provides insights into creating fast and engaging user experiences in mobile applications by intelligently combining frontend architecture with smart UX design.
- “One Platform to Serve Them All: Autoscaling Multi-Model LLM Serving” by Meryem Arik at Doubleword. A technical breakdown of how a single platform can autoscale multi-model serving with shared base weights, hot-swapped adapters, dynamic loading, and smart eviction.
- “From Content to Agents: Scaling LLM Post-Training Through Real-World Applications and Simulation” by Faye Zhang at Pinterest and Andi Partov at Veris AI. This session explores effective LLM post-training techniques, highlighting real-world applications from Pinterest’s content generation to simulation-based agent training.
- “Powering the Future: Building Your GenAI Infrastructure Stack” by Maggie Hu and Merrin Kurian at Intuit. An inside look at how Intuit’s GenOS team integrates vector stores, prompt management, RAG pipelines, and agent orchestration to serve approximately 100 million users.
- “AI-Driven Productivity: From Idea to Impact” by Jyothi Nookula at a Stealth Startup. A pragmatic framework designed to transform GenAI enthusiasm into an enterprise-ready blueprint for achieving significant productivity gains.
Mark your calendars for QCon San Francisco 2025, where tech leaders and practitioners will converge to share insights, strategies, and lessons learned from navigating the complexities of software development. This conference is an excellent opportunity to network, learn, and grow. For more details about the event and to view the full schedule, check out the QCon San Francisco website.
Inspired by: Source
