InfoQ Homepage Conferences Content on InfoQ
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Fine Tuning the Enterprise: Reinforcement Learning in Practice
Will Hang and Wenjie Zi explain how OpenAI's Agent RFT (Reinforcement Fine-Tuning) optimizes reasoning models end-to-end, enabling autonomous agents to learn efficient tool use and cut latencies.
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Enhancing Reliability Using Service-Level Prioritized Load Shedding at Netflix
Anirudh Mendiratta and Benjamin Fedorka explain how Netflix handles massive traffic storms using service-level prioritized load shedding and client-side attempt budgets to protect critical path APIs.
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Graph RAG: Building Smarter Retrieval Workflows with Knowledge Graphs
Cassie Shum explains how to move beyond traditional RAG limits using GraphRAG to inject enterprise logic and complex multi-hop reasoning into scalable knowledge graphs within a data warehouse.
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The Infrastructure Challenge Behind Production AI
The panelists share how core data systems and cloud platforms handle machine-driven workloads, exploring infrastructure design patterns and failure points as AI becomes a permanent fixture.
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Trustworthy Productivity: Securing AI-Accelerated Development
Sriram Madapusi Vasudevan explains how to secure autonomous AI agents, sharing enterprise patterns like provenance gates and sandboxed runtimes to defend the ReAct loop against rogue execution.
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Million PDFs: Building a Modern Document Infrastructure with Rust and Typst
Erik Steiger explains how to replace heavy, outdated PDF engines like Crystal Reports and Puppeteer with a high-performance, serverless Rust and Typst pipeline, dropping render times below 2ms.
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AI Works, Pull Requests Don’t: How AI is Breaking the SDLC and What to Do about it
Michael Webster explains how autonomous "headless" AI agents are flooding pipelines with code. He shares how CircleCI addresses the resulting technical debt and bottlenecked PR reviews.
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Rust at the Core - Accelerating Polyglot SDK Development
Spencer Judge explains how Temporal uses a shared Rust core to build multi-language SDKs. He shares practical advice on handling type conversion, async bridging, and memory management.
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Rules for Understanding Language Models
Naomi Saphra explains why language models act like populations rather than individuals. She discusses how data diversity drives generalization, why LLMs mirror users and how tokenizers alter behavior.
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The Time it Wasn't DNS
Sean Klein explains how Azure handles massive outages using modern incident analysis. Moving past the "Five Whys," he shares how systemic factors—not operator error—caused the 2023 global WAN outage.
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Challenging Google Analytics: Building a Scalable, Cost-Effective User Tracking Service
Alina Krasavina discusses how Delivery Hero built an in-house tracking platform to replace Google Analytics. She explains their architecture, load testing, and how they cut storage costs by 75%.
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AI Agents to Make Sense of Data at OpenAI
OpenAI’s Bonnie Xu explains Kepler, their internal AI data analyst agent built on MCP. She shares how they scale data discovery across 600+ PB using automated context, RAG, and AST-based evals.
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