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Topics

Development

Featured in Development

Python, Numba, and Algorithm Design: Building Efficient Models in Financial Services

Chad Schuster discusses bridging Python's developer velocity with C-like performance using Numba JIT and GPUs. Drawing from large-scale actuarial modeling, he explains LLVM pipeline architecture, performance gains up to 750x, and essential trade-offs like OOP limits, type inference errors, and compile-time overhead for engineering leaders scaling compute-heavy enterprise systems.

All in development

Architecture & Design

Featured in Architecture & Design

Architecture as a Socio-Technical Craft

Architecture is not a fixed choice made once; fitness is a moving target driven by changing regulations, tech, and markets. Even a sound design can silently stop fitting over time without bad calls. Spanning seven articles on context stores, gateways, and topologies, this collection treats architecture as an evolving sociotechnical craft where teams deliberately shape friction, fitness, and flow.

All in architecture-design

AI Infrastructure

Featured in AI, ML & Data Engineering

Beyond Offset Lag: Computing Time in Queue for Apache Hudi Data Lake Pipelines at Petabyte Scale

In this article, author Srikanth Mamidala discusses the data lake architecture used for analytics, reporting, and machine learning and shows how to manage the consumer lag metrics when using Kafka and Apache Hudi.

All in ai-ml-data-eng

Culture & Methods

Featured in Culture & Methods

Rightsizing Platform Engineering: Building the Platform Your Organization Actually Needs

Shift-left and DevOps have impacted how we flow changes from inception to production, but at the cost of increased cognitive load and duplication of effort across testing, security, and maintenance. This article explores the real-world challenges of rightsizing developer platforms and finding a cultural match for engineering teams who use them to reduce cognitive load and deliver change faster.

All in culture-methods

DevOps

Featured in DevOps

Can Claude Fix Itself? Using LLMs for Incident Response

Anthropic reliability engineer Alex Palcuie shares practical lessons on using LLMs for real-world incident response. He explains where AI acts as a superhuman for observing logs and traces, why it still struggles with causation versus correlation during root-cause analysis, and how engineering leaders can integrate AI into on-call workflows without eroding human expertise.

All in devops

Events

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AI Security & Privacy Engineering Certification

Secure and govern production AI systems, from sensitive data to guardrails, evals, and audits.
Online. Register now.

Architect Certification

Distributed systems, decentralized decisions, platform engineering, and AI architecture.
Online. Register Now.

Engineering Leadership Certification

Work through leadership decisions with senior peers facing similar technical trade-offs.
Online. Register Now.

AI-Assisted Engineering Certification

Your coding agent moves fast. Who checks whether it's making the codebase better?
Online. Register Now.

QCon San Francisco

What's working across AI, architecture, and leadership, from the teams doing it.
Register. Early bird ends August 11.

QCon AI New York

Production AI across agents, context, evals, security, and infrastructure, from the senior engineers building it.
Registration open.

QCon London

What early-adopter teams have proven in production, across 15 engineering tracks.
Register. Early bird ends August 11.

InfoQ Homepage Interviews Sylvan Clebsch on the Actor-Model Language Pony, Garbage Collection, Capabilities, Concurrency

Sylvan Clebsch on the Actor-Model Language Pony, Garbage Collection, Capabilities, Concurrency

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30:10

Bio

Sylvan Clebsch was kicked out of a lot of schools before becoming a serial entrepeneur in the 90s, working on embedded OSes, secure systems, VOIP, physical simulation, and graphics engines, before accidentally becoming an Executive Director in IT at a major investment bank - which he has now left. He now works at Causality, developing Pony, and is a part-time PhD student at Imperial College.

About the conference

Code Mesh, the Alternative Programming Conference, focuses on promoting useful non-mainstream technologies to the software industry. The underlying theme is "the right tool for the job", as opposed to automatically choosing the tool at hand.

Dec 24, 2015

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