InfoQ Homepage AI, ML & Data Engineering Content on InfoQ
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Moving Mountains: Migrating Legacy Code in Weeks Instead of Years
Principal AI Engineer David Stein explains how ServiceTitan uses AI coding agents to automate large-scale legacy code migrations, compressing quarters of technical debt into weeks.
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Beyond Prompting: Context Engineering and Memory Management for AI Systems at Scale
Adi Polak explains how to scale agentic AI by shifting from stateless prompt engineering to stateful, low-latency context engineering with Apache Kafka and Flink.
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Beyond Speed Limits: Exploring the Performance Power of Valkey
Viktor Vedmich explains how to achieve sub-millisecond application latency using Valkey, an open-source, high-performance in-memory fork of Redis supported by AWS.
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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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