InfoQ Homepage Agents Content on InfoQ
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Architecting the Data Layer for AI Agents: from Transactional Systems to MCP and Semantic Models
Fabiane Nardon explains how to architect enterprise data platforms for AI agents, balancing precision, security, and token costs using MCP, data mesh, and semantic web technologies.
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SafeChat: Building AI-Powered Safety Systems at Scale in a Real-Time Marketplace
Bruna Pereira shares how DoorDash built a scalable AI moderation platform. Learn how combining cheap classifiers with LLM scoring reduced incidents and cut latency in real-time chat.
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From Models to Agents: Building Context-Aware Consumer AI at Scale at DoorDash
Sudeep Das explains how DoorDash transforms e-commerce recommendations using LLM-driven semantic consumer memory, hierarchical semantic IDs, grounded agentic search, and multi-tiered LLM ranking.
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The Right 300 Tokens Beat 100k Noisy Ones: The Architecture of Context Engineering
Baruch Sadogursky and Patrick Debois explain context engineering antipatterns in coding agents, demonstrating how skills, right-tool retrieval, and external memory optimize developer workflows.
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Keeping ChatGPT Fast as AI Development Accelerates
Martin Spier shares how agentic coding accelerates release velocity at OpenAI and explains how always-on AI agents redefine performance engineering to keep ChatGPT fast at massive scale.
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Rewriting All of Spotify's Code Base, All the Time
Aleksandar Mitic and Jo Kelly-Fenton discuss how Spotify uses "Honk," a background AI coding agent, to automate codebase migrations at scale and tackle the ongoing maintenance problem.
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Architecting AI Systems for the Messy Reality of Enterprises: Why Agentic Compute is the Missing Layer
Arun Joseph explains how to successfully build and deploy enterprise-grade agentic platforms by leveraging existing teams, JVM stacks, and a "compute as the agent" architectural paradigm.
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From Copy-Paste to Composition: Building Agents Like Real Software
Jake Mannix explains how to mature AI agents using "virtual tools" for encapsulation, interface abstraction, and deterministic taint tracking to prevent lethal data exfiltration risks.
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Postgres for Production Agents: Your Relational Foundation for Enterprise AI
Gwen Shapira discusses how to power enterprise AI features using Postgres, explaining advanced relational SQL context retrieval, pgvector semantic tuning, and transitioning to agentic workflows.
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The Multi-Agent Approach: Building Reliable and Controllable Software Development Automation
Itamar Friedman explains how to transition from "vibe coding" to reliable software delivery. Learn how to govern agent communication and build a context-driven SDLC that scales.
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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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Automating the Web with MCP: Infra that Doesn’t Break
Paul Klein explains how to automate the web with MCP. He shares architectural strategies for running multi-tenant, cloud-hosted Chromium sandboxes to power AI browsing agents.
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