The full program for QCon.ai New York 2025 is officially released! Scheduled for December 16–17, 2025, this conference is a must-attend for senior software engineers, architects, and technology leaders. This year’s theme revolves around a pressing challenge in modern software development: turning AI prototypes into reliable, production-grade systems that scale.
Crafted by a dedicated Program Committee of senior practitioners, QCon.ai New York offers a rich array of experience-driven sessions. These sessions tackle the practicalities of building, deploying, and maintaining enterprise AI systems, focusing on the realities faced in the field.
Wes Reisz, the Conference Chair and Technical Principal at Thoughtworks, emphasizes, “QCon.ai New York is focused on helping you build and scale AI reliably.” Every presentation is delivered by practitioners who share their real-world insights and experiences—flaws and successes alike.
AI’s Impact on the Software Development Lifecycle
The integration of AI is fundamentally reshaping the software development lifecycle (SDLC). Various sessions will explore new challenges and opportunities for engineering teams that arise from this integration.
- AI Works, Pull Requests Don’t: How AI Is Breaking the SDLC and What To Do About It: In this talk, Michael Webster, a Principal Engineer at CircleCI, will dive into the emerging friction between AI-generated code and traditional quality gates like pull requests and CI pipelines. Attendees will learn about innovative processes necessary to maintain velocity without compromising code quality.
- Platform Teams Enabling AI – MCP/Multi-Agentic Tools Across LinkedIn: This session features LinkedIn’s Principal Engineers, Karthik Ramgopal and Prince Valluri. They will discuss the intricate challenge of developing centralized platform infrastructure to support diverse AI-driven developer tools utilized by decentralized teams across the organization.
Building and Scaling Reliable AI Systems
Transitioning from theory to production is not easy. It requires a dedicated focus on architecture, data governance, and system reliability. The following talks provide practical insights from leaders in the industry.
- Designing AI Platforms for Reliability: Tools for Certainty, Agents for Discovery: Aaron Erickson, Founder of the DGX Cloud Applied AI Lab at NVIDIA, will present a dual-layer architectural approach for AI systems. His session will explore how to meld deterministic tools essential for reliable operations with probabilistic agents designed for discovery and problem-solving.
- Graph RAG: Building Smarter Retrieval Workflows with Knowledge Graphs: Cassie Shum, VP of Field Engineering at RelationalAI, will introduce advanced techniques in retrieval-augmented generation (RAG). She will demonstrate how leveraging knowledge graphs, which illuminate the relationships between data points, can enhance the accuracy and context-awareness of large-language model-based systems compared to traditional vector search methods.
Emerging Threats and Trust Frameworks for Enterprise AI
The rise of AI not only empowers developers but also introduces new security threats and challenges. These sessions provide C-level insights into navigating the evolving security landscape.
- Deepfakes, Disinformation, and AI Content Are Taking Over the Internet: Shuman Ghosemajumder, Co-founder & CEO of Reken, will analyze how generative AI technologies are being misused by malicious actors to produce fake content at scale. He will recommend potential technical and strategic countermeasures to mitigate these threats.
- Building Evals for AI Adoption: From Principles to Practice: Mallika Rao, Engineering Leader at Netflix, will address the critical aspect of trust and safety in AI systems. This talk emphasizes the importance of rigorous evaluations to assess behavior and performance, helping teams identify risks, biases, and vulnerabilities before they can be exploited.
QCon.ai New York emphasizes the importance of the real engineering behind AI. Each session is designed to bridge the gap between research and production, focusing on architecture, data systems, observability, and governance.
The full conference schedule is now accessible on the QCon.ai website. Don’t forget that early bird registration ends on October 14!
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