Engineering Leadership

Senior engineering interviews still revolve around whiteboard puzzles that the job never asks for, and AI has now made the puzzle worthless as a signal. A hiring manager who also builds recruiting software and recently sat on the candidate side lays out the case for work-sample loops that mirror the actual role, and a concrete protocol for running them.

AI coding assistants are fundamentally breaking traditional engineering productivity metrics. Individual output measurements become meaningless when AI can generate thousands of lines per hour. Explore why the 10x engineer concept is dying, what replaces it, and how engineering culture must adapt to survive the transition to AI-augmented development teams.

From scaling AI teams across three continents, I've learned that building ML organizations isn't about hiring data scientists—it's about architecting talent systems that scale with ambition.

Wells' Eloi-Morlock dynamic eerily parallels our AI dependency trajectory. Engineering leaders must recognize cognitive atrophy patterns and implement strategic frameworks that preserve human agency while embracing technological advancement.

Master platform engineering maturity with this comprehensive assessment framework combining CNCF standards, real-world implementation experience, and practical evaluation tools.

A comprehensive analysis of code ownership patterns in polyrepo vs monorepo architectures, examining team autonomy, coordination challenges, and scaling strategies for engineering organizations.

Meta's $65 billion superintelligence initiative restructures AI development with unprecedented talent acquisition, infrastructure investment, and technical architecture patterns that engineering leaders must understand and adapt.

A deep dive into the new wave of advanced nuclear energy technologies—from small modular reactors to fusion—reshaping the global energy landscape.

A comprehensive guide to platform engineering in 2026 covering internal developer platforms, Backstage ecosystem maturity, infrastructure abstraction with Crossplane and Humanitec, developer experience metrics, AI-assisted workflows, security guardrails, FinOps integration, and the organizational patterns that separate successful platform teams from expensive failures.

Remote DevOps has evolved from pandemic workaround to permanent operating model. Five years of distributed infrastructure management has produced clear patterns for what works — async incident response, AI-augmented operations, infrastructure-as-code everything, and team topologies designed for timezone-distributed collaboration.

Technical debt costs the average enterprise $3.61 per dollar of development spending. Yet most organizations have no systematic approach to measuring, prioritizing, or remediating it. A strategic guide covering debt taxonomies, quantification frameworks, the 20% sprint allocation model, and how AI tools are changing the debt remediation calculus in 2026.