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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

Ecologies and Economics of Language AI in Practice

Jade Abbott discusses the shift from massive, resource-heavy models to "Little LMs" that prioritize efficiency and cultural sustainability. She explains how techniques like LoRA, quantization, and GRPO allow for high performance with less compute. By sharing the "Ubuntu Punk" philosophy, she shares how to move beyond extractive data practices toward human-centric, sustainable AI systems.

All in ai-ml-data-eng

Culture & Methods

Featured in Culture & Methods

Empowering Teams: Decentralizing Architectural Decision-Making

Peter Hunter & Elena Stojmilova share Open GI's journey from a slow, legacy monolith to a cloud-native SaaS platform. They detail how adopting Team Topologies and a decentralized architectural approach empowered teams. Key practices discussed include utilizing Domain-Driven Design to create a Context Map, implementing the Advice Process with Architectural Principles, and more.

All in culture-methods

DevOps

Featured in DevOps

DevOps Is for Product Engineers, Too

Lesley Cordero discusses platform engineering as a sociotechnical solution for scaling organizations. She explains the CALMS framework, the "pendulum of tension" between reliability and velocity, and how to transition from reactive to proactive leadership. By focusing on communal learning and distributed power, she shares how to build resilient systems without sacrificing human well-being.

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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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

Ecologies and Economics of Language AI in Practice

Empowering Teams: Decentralizing Architectural Decision-Making

DevOps Is for Product Engineers, Too

Helpful links

Choose your language

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Magika 1.0: Smarter, Faster File Detection with Rust and AI

HL is a Fast, Rust-Based JSON Log Viewer Offering up to 2GiB/s Parsing Speed

Lessons Learned in Migrating to Micro-Frontends by Luca Mezzalira at QCon SF

Target Improves Add to Cart Interactions by 11 Percent with Generative AI Recommendations

AWS Expands Well-Architected Framework with Responsible AI and Updated ML and Generative AI Lenses

Where Architects Sit in the Era of AI

Lessons Learned from Migrating a Legacy Test Suite to Gauge with Kotlin

Empowering Teams: Decentralizing Architectural Decision-Making

Leading from Any Position: Richard Bown on Humane Engineering Organizations

Ecologies and Economics of Language AI in Practice

OpenAI and Anthropic Donate AGENTS.md and Model Context Protocol to New Agentic AI Foundation

Toad: A Unified CLI Tool for All Your LLMs That Promises Improved UX From Existing Ones

Pinecone Introduces Dedicated Read Nodes in Public Preview for Predictable Vector Workloads

DevOps Is for Product Engineers, Too

AWS Launches ECS Express Mode to Simplify Containerised Application Deployment

QCon AI New York

QCon London

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