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Development

Featured in Development

Accelerating Performance by Incrementally Integrating Rust into Existing Codebase

Lily Mara explains how to avoid high-risk software rewrites through incremental FFI refactoring. She shares how engineering teams can replace Python bottlenecks with Rust via PyO3, demonstrating how to achieve dramatic function-level speedups, seamless integration testing, and meaningful infrastructure cost savings without microservice overhead.

All in development

Architecture & Design

Featured in Architecture & Design

Agentic AI Architecture: Current Challenges and Future Opportunities

Agentic AI architecture extends microservices and cloud-native architectures with AI agents that work with context, memory, and protocols such as MCP and A2A. The article covers bounded-context integration, task-dependent coordination strategies, new security risks, and observability needs. It expects gradual adoption alongside existing architectures, with platforms absorbing common components.

All in architecture-design

AI Infrastructure

Featured in AI, ML & Data Engineering

Distributed LLM Inference on Kubernetes with llm-d, Wasm, & TornadoVM

In this episode, Edoardo Vacchi discusses the evolving landscape of WebAssembly on the backend, running Java workloads on GPUs using TornadoVM, and optimizing distributed AI inference using llm-d and vLLM on Kubernetes. Edoardo explains how llm-d manages cache locality (KV and prefix caches), request routing, and batch inference across Kubernetes clusters to maximize expensive GPU utilization.

All in ai-ml-data-eng

Culture & Methods

Featured in Culture & Methods

The Socio-Technical Staff+ Engineer: Architecture, Culture and Organisational Change

Vanessa Formicola shares how technical leaders can move beyond "wishful architecture" by practicing holistic socio-technical engineering. She discusses why engineering leaders must account for organizational maturity, reward structures, geopolitical climate, and team dynamics, framing the staff-plus role as designing the conditions for technology to thrive rather than just picking tools.

All in culture-methods

DevOps

Featured in DevOps

Wrangling Telemetry at Scale: a Guide to Self-Hosted Observability

Colin Douch shares battle-tested strategies for building and scaling self-hosted observability stacks. He explains how to effectively correlate metrics, structured logs, and distributed traces using open-source tooling like Prometheus, VictoriaMetrics, and Jaeger, while navigating the engineering trade-offs of avoiding SaaS vendor lock-in.

All in devops

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AI Engineering Certification

Work through your production AI decisions with senior engineers from other companies. Apply their perspectives to challenges from your own work.
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AI Engineering Certification

Building RAG pipelines or AI agents? Work through retrieval, context, evals, and reliability decisions with experienced practitioners.
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High-Performing Teams Certification

Compare team design, delivery flow, AI roles, and metrics with experienced practitioners.
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Architect Certification

Distributed systems, decentralized decisions, platform engineering, and AI architecture.
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QCon San Francisco

What's working across AI, architecture, and leadership, from the teams doing it.
Register. Early bird ends Nov 10.

QCon AI New York

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

What early-adopter teams have proven in production, across 15 engineering tracks.
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QCon AI Boston

Learn from the decisions and trade-offs behind AI systems already running in production.
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Five Static Code Audits Every Developer Should Know and Use

Mike Rozlog discusses the need for software audits, proposing five code reviews that every developer should use: Numerical Literal, String Literal, god Method, Shotgun Surgery and Duplicate Code.

Mike Rozlog
on May 17, 2011

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55:12
Scrub & Spin: Stealth Use of Formal Methods in Software Development

Gerard Holzmann discusses Spin, a design analyzer tool, and Scrub, a code review tool, used by Jet Propulsion Laboratory to analyze and fix the software used for solar system exploration missions.

Gerard Holzmann
on Jun 02, 2010

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01:23:00
Controlling Your Architecture

Magnus Robertsson shows how to control the code architecture to avoid an architectural drift leading to a big-ball-of-mud: peer review, code analysis, and zero tolerance to warnings and errors.

Magnus Robertsson
on Oct 22, 2009

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40:37
Testing is Overrated

In this talk from RubyFringe, Luke Francl asks: is developer-driven testing really the best way to find software defects? Or is the emphasis on testing and test coverage barking up the wrong tree?

Luke Francl
on Jan 02, 2009

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22:25
Secure Programming with Static Analysis

Creating secure code requires more than just good intentions. Static source code analysis can be used to uncover the kinds of errors that lead directly to vulnerabilities. Brian Chess shows you how.

Brian Chess
on Aug 06, 2008

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55:40

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