InfoQ Homepage AI, ML & Data Engineering Content on InfoQ
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Platform Teams Enabling AI - MCP/Multi-Agentic Tools across Linkedin
LinkedIn’s Karthik Ramgopal and Prince Valluri explain how to scale engineering with agentic AI. They discuss building centralized platform foundations for orchestration, tooling, and context.
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Choosing Your AI Copilot: Maximizing Developer Productivity
Coinbase ML platform engineer Sepehr Khosravi discusses the state of AI-assisted development. He explains how to maximize productivity using advanced techniques in Cursor and Claude Code.
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Building Evals for AI Adoption: from Principles to Practice
Mallika Rao explains how evaluation debt silently triggers regressions in distributed AI systems. She shares a five-layer evaluation stack to align metrics directly with long-term user trust.
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Designing AI Platforms for Reliability: Tools for Certainty, Agents for Discovery
Aaron Erickson explains how to balance deterministic systems with stochastic AI agents. He shares lessons from NVIDIA on building purpose-built agent hierarchies and scaling robust evals.
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AI Native Engineering
Ian Thomas discusses Meta’s shift to AI-native engineering. He shares how Reality Labs reduced toil and grew an AI productivity community to 400+ members, boosting tool adoption to over 80%.
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The Ironies of A^2 I^2
J. Paul Reed explains the "ironies of automation" and AI in incident response. He discusses how reliance on AI can erode manual skills and camouflage system failures during high-stakes outages.
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The AI Gateway: Scaling Centralized Inference across Decentralized Teams
Meryem Arik explains how AI model gateways resolve the chaos of decentralized engineering teams by centralizing inference. Learn to optimize costs, enforce governance, and maximize GPU utilization.
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Powering the Future: Building Your GenAI Infrastructure Stack
Merrin Kurian discusses Intuit’s GenOS, a generative AI operating system powering agents for 100M users. She explains the transition from chat assistants to "done-for-you" autonomous experiences.
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Using AI as a Thinking Partner for Large-Scale Engineering Systems
Google senior staff engineer Julie Qiu shares how she uses AI as a thinking partner to navigate large-scale systems, moving beyond code generation to architecting complex, multi-language ecosystems.
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Accelerating LLM-Driven Developer Productivity at Zoox
Amit Navindgi explains how Zoox built Cortex, an internal AI platform that streamlines the developer lifecycle by moving beyond the hype to deliver secure, agentic workflows and real-world impact.
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What I Learned Building Multi-Agent Systems from Scratch
Paulo Arruda shares Shopify’s journey from "vibe coding" to building a multi-agent microservices architecture, exploring how specialized AI agents and context engineering maximize engineering ROI.
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Leadership in AI-Assisted Engineering
Justin Reock explains how to move beyond AI hype using data-driven frameworks. He shares research on the AI learning curve, the Cobra Effect in metrics, and strategies to augment developer throughput.
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