Career Development
The long arc of a senior engineering career — transitions, leveling up, and picking projects that compound.
Articles
Plan: 90-Day AI Ramp for Backend Engineers
A 90-day plan for backend engineers who need to be AI-competent at work — not transitioning roles, just keeping up and contributing.
Guide: Surviving a Full Interview Loop with ADHD
Concrete structures for getting through a 5-6 round interview loop when your executive function doesn't cooperate — prep systems, day-of tactics, and recovery.
Guide: Using AI Coding Tools Without Getting Worse
A practical guide for senior engineers using AI coding tools — how to get the speed gains without losing the judgment and debugging skills that make you senior.
Guide: Finding Projects That Enrich Your Resume
How to identify and volunteer for the projects at your current job that actually move your career forward — the tactics for sourcing signal-rich work.
Framework: Aligning Projects With Your Next-Level Goal
A framework for choosing projects that build the exact signals your next promotion requires — not just projects that keep you busy.
List: Papers Backend Engineers Should Read
A curated list of the 20 papers that shaped how backend systems actually work — annotated with why each one matters and what to skip.
Guide: Building a Real LLM Project for Your Resume
How to build an LLM project that demonstrates real engineering judgment — not a wrapper around an API call, but something that survives scrutiny in an interview.
Framework: Scope, Impact, Visibility — The Three-Axis Promotion Model
A framework for diagnosing why your promotion isn't moving — separating the three axes that drive senior-level promotion and which to fix first.
Plan: Transitioning to Machine Learning Engineer
A phase-based roadmap for backend engineers moving into ML engineering — what transfers, what to build, and what to skip entirely.
Plan: Transitioning to AI Infrastructure Engineer
A phase-based roadmap for backend engineers moving into AI infrastructure — GPU serving, training platforms, and the systems layer beneath ML.
Framework: The AI/ML System Design Interview — What's Different
A framework for backend engineers preparing for AI/ML system design rounds — what's the same, what's different, and where strong backend candidates fail.
Framework: What's Durable vs What's Hype — A Backend Engineer's AI Investment Guide
A decision framework for backend engineers picking which AI skills to invest in — separating durable knowledge from churn that won't matter in 18 months.