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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 Shipping AI-Powered Healthcare Products

Clara Matos discusses the journey of shipping AI-powered healthcare products at Sword Health. She explains how to implement input/output guardrails for regulated industries and shares a framework for robust evaluations using human and LLM-based ratings. From prompt engineering to RAG and user feedback loops, she shares a data-driven roadmap for building reliable AI care agents at scale.

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

Overload Protection: the Missing Pillar of Platform Engineering

Overload protection is often overlooked in platform engineering, leaving teams to create inconsistent, fragile fixes. Centralized rate limits, quotas, adaptive controls, and clear visibility give services predictable ways to handle traffic spikes, reduce reliability debt, and prevent cascading failures across systems.

All in devops

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Podcasts

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Intended for architects and senior developers.

About this Podcast

Intended for architects and senior developers.

AI, ML & Data Engineering

Platform Engineering for AI: Scaling Agents and MCP at LinkedIn

QCon AI New York Chair Wes Reisz talks with LinkedIn’s Karthik Ramgopal and Prince Valluri about enabling AI agents at enterprise scale. They discuss how platform teams orchestrate secure, multi-agentic systems, the role of MCP, the use of foreground and background agents, improving developer experience, and reducing toil.

Karthik Ramgopal Prince Valluri
on Dec 10, 2025

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32:50
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Intended for architects and senior developers.

About this Podcast

Discussions on intentional corporate culture and software management approaches.

Culture & Methods

GitHub Next: how their research and prototyping team operates

In this podcast, Shane Hastie, Lead Editor for Culture & Methods spoke to Idan Gazit and Eddie Aftandilian from GitHub Next how their research and prototyping team operates as a "department of fool around and find out", exploring AI-powered developer tools through rapid experimentation and user feedback.

Idan Gazit Eddie Aftandilian
on Jul 11, 2025

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30:04
Culture & Methods

Using AI Code Generation to Migrate 20000 Tests

In this podcast, Shane Hastie, Lead Editor for Culture & Methods spoke to Sergii Gorbachov, a staff engineer at Slack, about how they successfully used AI combined with traditional coding approaches to migrate 20,000 tests in 10 months, discovering that AI alone was insufficient and required human oversight and conventional tools to work effectively.

Sergii Gorbachov
on Jun 06, 2025

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23:03
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