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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

From DVDs to Global Streaming: How Netflix’s Commerce Architecture Actually Evolved

Kasia Trapszo discusses how Netflix evolved its commerce platform from a U.S. DVD service into global infrastructure. She explains navigating international payment realities, adapting to strict regulatory mandates, decomposing monolithic architectures along domain boundaries, and re-architecting systems for massive live-event demand - proving great systems survive by continually evolving.

All in architecture-design

AI Infrastructure

Featured in AI, ML & Data Engineering

Architecting the Data Layer for AI Agents: from Transactional Systems to MCP and Semantic Models

Fabiane Nardon shares how TOTVS prepares enterprise data for token-hungry AI agents. She discusses balancing deterministic logic and non-deterministic LLMs across precision, security, and cost. Nardon details using data mesh, low-latency database architectures, semantic ontologies, and dynamic MCP tool selection to optimize context windows and reduce token overhead in transactional systems.

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 Brian Beckman and Erik Meijer on Tesla

Brian Beckman and Erik Meijer on Tesla

15:10

Bio

Dr. Brian Beckman and Dr. Erik Meijer are both architects in the SQL Server at Microsoft where amongst many other things, they works with the C# and VB.NET teams on the design of data integration in programming languages. Both are accomplished writers in computer science and academia currently working as a team in in Microsoft Research and Development.

About the conference

Sep 05, 2007

Interview with

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