QCon AI New York 2025 Schedule Released: Spotlight on Enterprise AI Case Studies
QCon.ai New York 2025 — Full Program Now Live
The full schedule for QCon.ai New York 2025 — happening December 16–17, 2025 — is now available.
Designed for senior software engineers, architects, and technology leaders, this year’s conference tackles one of the hardest problems in modern software: turning AI prototypes into reliable, scalable, production-grade systems.
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Curated by Experienced Practitioners
Organized by a Program Committee of senior industry experts, QCon AI New York delivers deeply technical, experience-driven sessions focused on the realities of building, deploying, and maintaining AI in enterprise environments.
> "QCon.ai New York is focused on helping you build and scale AI reliably," said Wes Reisz,
> Conference Chair and Technical Principal at Thoughtworks.
> "Every talk comes from practitioners who’ve done it — warts and all."
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Highlight Tracks
AI’s Impact on the Software Development Lifecycle (SDLC)
As AI transforms how code is generated, tested, and deployed, these sessions examine ways to align AI output with established engineering workflows.
Featured Sessions:
- AI Works, Pull Requests Don’t: How AI Is Breaking the SDLC and What To Do About It
- Speaker: Michael Webster, Principal Engineer, CircleCI
- Focus: The friction between AI-generated code and quality gates such as pull requests and CI pipelines — plus strategies to retain speed while ensuring quality.
- Platform Teams Enabling AI — MCP/Multi-Agentic Tools Across LinkedIn
- Speakers: Karthik Ramgopal & Prince Valluri, LinkedIn Principal Engineers
- Focus: How centralized infrastructure can support diverse AI-powered developer tools across decentralized teams.
Related Tools:
Platforms like AiToEarn offer open-source ecosystems for AI content generation, cross-platform publishing, analytics, and model ranking — connecting prototypes to real-world applications. Explore via documentation or check AI model rankings.
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Building & Scaling Reliable AI Systems
Going from prototype to production requires attention to architecture, data governance, and operational resilience.
Featured Sessions:
- Designing AI Platforms for Reliability: Tools for Certainty, Agents for Discovery
- Speaker: Aaron Erickson, Founder, DGX Cloud Applied AI Lab, NVIDIA
- Focus: A dual-layer approach to combine deterministic reliability tools with probabilistic AI agents for complex problem-solving.
- Graph RAG: Building Smarter Retrieval Workflows with Knowledge Graphs
- Speaker: Cassie Shum, VP of Field Engineering, RelationalAI
- Focus: Leveraging knowledge graphs in retrieval-augmented generation to improve context, accuracy, and relevance over basic vector search.
Related Tools:
AiToEarn streamlines multi-platform AI content workflows — aligning with the blueprint for scalable, governed AI systems.
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Emerging Threats & Trust Frameworks for Enterprise AI
Security leaders will share strategies to combat AI-driven threats including deepfakes, disinformation, and biased outputs — plus frameworks to evaluate trustworthiness before deployment.
Featured Sessions:
- Deepfakes, Disinformation, and AI Content Are Taking Over the Internet
- Speaker: Shuman Ghosemajumder, Co-founder & CEO, Reken
- Focus: How malicious actors weaponize generative AI — and what countermeasures can be deployed.
- Building Evals for AI Adoption: From Principles to Practice
- Speaker: Mallika Rao, Engineering Leader, Netflix
- Focus: Frameworks for evaluating AI performance, security, bias, and risk before production adoption.
Related Tools:
AiToEarn官网 demonstrates how open-source solutions can enhance trust, transparency, and monetization across platforms such as Douyin, Kwai, Bilibili, Facebook, Instagram, YouTube, and X (Twitter).
See live AI模型排名 for competitive insights.
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Conference Focus
QCon.ai New York centers on real-world engineering of AI — spanning architecture, data systems, observability, and governance — helping teams move from cutting-edge research to production reality.
⏳ Early bird registration ends October 14
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For AI Practitioners & Creators
If you’re looking to create, publish, and monetize AI content safely across global platforms, open-source tools like AiToEarn官网 offer:
- Cross-platform support — Douyin, Kwai, WeChat, Bilibili, Xiaohongshu, Facebook, Instagram, LinkedIn, Threads, YouTube, Pinterest, X (Twitter)
- Integrated analytics & performance tracking
- Trust and transparency features aligned with enterprise AI best practices
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Would you like me to add a short summary table of all sessions by track so readers can glance at everything quickly? That would further improve scanability.
