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Development

Featured in Development

How to Use Apache Spark to Craft a Multi-Year Data Regression Testing and Simulations Framework

Vivek Yadav, an engineering manager from Stripe, shares his experience in building a testing system based on multi-year worth of data. He shares insights into why Apache Spark was the choice for creating such a system and how it fits in the "traditional" engineering practices.

All in development

Architecture & Design

Featured in Architecture & Design

Where Architects Sit in the Era of AI

As AI evolves from tool to collaborator, architects must shift from manual design to meta-design. This article introduces the "Three Loops" framework (In, On, Out) to help navigate this transition. It explores how to balance oversight with delegation, mitigate risks like skill atrophy, and design the governance structures that keep AI-augmented systems safe and aligned with human intent.

All in architecture-design

AI Infrastructure

Featured in AI, ML & Data Engineering

Lessons Learned From Building LinkedIn’s First Agent: Hiring Assistant

Karthik Ramgopal and Daniel Hewlett discuss the evolution of AI at LinkedIn, from simple prompt chains to a sophisticated distributed agent platform. They explain the transition to a supervisor-sub-agent model that enables parallel development and modular quality evaluation. and share a blueprint for building resilient, high-scale agentic systems.

All in ai-ml-data-eng

Culture & Methods

Featured in Culture & Methods

Changing Power Dynamics: What Senior Engineers Can Learn from Junior Engineers

Beth Anderson discusses the "power distance index" and its critical role in communication. Using the Korean Air Flight 801 tragedy as a case study, she explains the dangers of hierarchy-driven silence. She shares actionable frameworks for building the four stages of psychological safety, implementing reverse mentoring, and using PRs as tools for knowledge sharing rather than gatekeeping.

All in culture-methods

DevOps

Featured in DevOps

Fix SLO Breaches before They Repeat: an SRE AI Agent for Application Workloads

Bruno Borges discusses a paradigm shift in performance management: moving from manual tuning to automated SRE agents. He explains how to leverage the USE and jPDM methodologies alongside LLMs to reduce MTTR from hours to seconds. By utilizing MCP tools for real-time diagnostics and memory dump analysis, he shares how engineering leaders can scale systems while meeting strict objectives.

All in devops

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Learn how leading engineering teams run AI in production—reliably, securely, and at scale.

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InfoQ Homepage Interviews Jay Fields and Zak Tamsen on Domain Specific Languages

Jay Fields and Zak Tamsen on Domain Specific Languages

23:45

Bio

Jay Fields and Zak Tamsen are software developers and consultants at ThoughtWorks. They have worked in the Domain Specific Language space where they have delivered applications that empowered subject matter experts to write the business rules of the applications.

About the conference

Oct 22, 2007

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Topics

How to Use Apache Spark to Craft a Multi-Year Data Regression Testing and Simulations Framework

Where Architects Sit in the Era of AI

Lessons Learned From Building LinkedIn’s First Agent: Hiring Assistant

Changing Power Dynamics: What Senior Engineers Can Learn from Junior Engineers

Fix SLO Breaches before They Repeat: an SRE AI Agent for Application Workloads

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Choose your language

Jay Fields and Zak Tamsen on Domain Specific Languages

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This content is in the Adaptive Leadership topic

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Java News Roundup: Spring Vault, LangChain4j, Seed4J, Infinispan, Gradle

Effective Mentorship and Remote Team Culture with Gilad Shoham

QCon AI New York

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InfoQ Software Architects' Newsletter

Jay Fields and Zak Tamsen on Domain Specific Languages

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