Facilitating the Spread of Knowledge and Innovation in Professional Software Development

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Development

Featured in Development

Expanding Swift from Apps to Services

Cory Benfield discusses the evolution of Swift from an app language to a critical tool for secure, high-scale services. He explains how Swift’s lack of a garbage collector eliminates tail latency and shares how its "zero-cost abstractions" rival C performance. He shares Apple’s roadmap for incremental adoption and demonstrates groundbreaking new interoperability for C++ and Java ecosystems.

All in development

Architecture & Design

Featured in Architecture & Design

[Video Podcast] Improving Valkey with Madelyn Olson

In this episode, Thomas Betts chats with Madelyn Olson, a maintainer of the Valkey project and a Principal Software Development Engineer at Amazon ElastiCache and Amazon MemoryDB. The conversation covers how Valkey started as an open source fork of Redis and how the maintainers optimized the memory usage and improved throughput.

All in architecture-design

AI Infrastructure

Featured in AI, ML & Data Engineering

From Prompts to Production: A Playbook for Agentic Development

In this article, author Abhishek Goswami shares a practitioner's playbook with development practices, that describes building agentic AI applications and scaling them in production. He also presents core architecture patterns for agentic application development.

All in ai-ml-data-eng

Culture & Methods

Featured in Culture & Methods

Scaling to 100+ as a Director: Lessons from Growing Engineering Organizations

Thiago Ghisi discusses the strategic evolution required to lead 100+ engineers without breaking the organization. He explains his "Three Levels of Impact" framework and shares practical lessons on speeding up decision-making, cultivating leadership teams, and building organizational resilience. Learn why he views reorgs as a continuous deployment feature rather than a one-time traumatic event.

All in culture-methods

DevOps

Featured in DevOps

From Alert Fatigue to Agent-Assisted Intelligent Observability

As systems grow, observability becomes harder to maintain and incidents harder to diagnose. Agentic observability layers AI on existing tools, starting in read-only mode to detect anomalies and summarize issues. Over time, agents add context, correlate signals, and automate low-risk tasks. This approach frees engineers to focus on analysis and judgment.