Most career ladders define a single, uniform set of expectations for Staff engineers operating within the company. Everyone benefits from clear role expectations, but career ladders are a tool that applies better against populations than people. This is particularly true for Staff-plus engineers, whose career ladders often paper over several distinct roles hidden behind a single moniker. The more folks I spoke with about the role of Staff-plus engineers at their company, the better their experiences began to cluster into four distinct patterns. Most companies emphasized one or two of the patterns, and one pattern only existed in companies with many hundreds or thousands of engineers. A few companies didn’t feature any technical leadership pattern and pushed all their experienced engineers towards engineering management. In literature, recurring character patterns are called archetypes, such as the “hero” or the “trickster,” and the archetype term is helpful for labeling these frequent variants of Staff-plus engineers.
Engineering Career Paths at Big Tech and High-Growth Startups
Levels at big tech, the most common career paths, and what comes after making it to Staff
Hiring (and Retaining) a Diverse Engineering Team
Stories from six engineering leaders who succeeded in building and growing diverse teams. Hiring approaches, retention tactics and strategies.
Engineering Leadership Skill Set Overlaps
How Staff Engineer, Engineering Manager (EM), Product Manager (PM), Tech Lead Manager (TLM) and Technical Program Manager (TPM) positions overlap in Big Tech and at high-growth startups – and their di
Engineering managers have a new job description
Why engineering managers are expected to be hands-on again and how AI tools are making it possible to stay technically sharp while still leading.
Staff Engineer and Public Speaker | Szymon Chudy
Staff engineer who cares about the why, not just the how. Writing about frontend, productivity, and growing in tech.
Why I Ignore The Spotlight as a Staff Engineer
An alternate path for Staff+ engineers that optimizes for systems over spotlights and stewardship over fungibility.
Intentions have a surprising amount of detail
Auteur managerialism, the myth of one-shotting, and the chindogufication of engineering
The Engineering Leadership Report 2026
Our survey of 600 engineering leaders exploring how the role is evolving, where the challenges lie, and what the future holds for the job.
5 Engineering Manager Archetypes
“There are only two hard things in Computer Science: cache invalidation and naming things.” — Phil Karlton Introduction In today’s tech organisations, you find 2 ... Read more
Scaling Engineering Teams: Lessons from Google, Facebook, and Netflix
After spending over a decade in engineering leadership roles at some of the world’s most chaotic innovation factories—Google, Facebook, and Netflix—I’ve learned one universal truth: scaling e…
The 2e Advantage: A Systemic Guide for Understanding & Unlocking Twice-Exceptional Talent in the Modern Workplace
In today's competitive landscape, overlooking talent is a critical error. Twice-exceptional (2e) and neurodivergent individuals represent a significant pool of often untapped potential, possessing unique strengths alongside specific challenges.
The engineering manager's attention budget
Every Engineering Manager has 5 jobs - most distribute their 100 'attention points' across only 2-3 of them
Tracking employee voice: developing the concept of voice pathways
Different disciplines have studied employee voice as a key component of workplaces. However, they have not tended to look at voice as a journey en route to enhanced (or diminished) employee voice with a start, diversion, delay and combining twists and turns during processes leading to outcomes. In this article, we build on existing theory and phenomena to develop the concept of ‘employee voice pathways’. We use this concept to provide a framework for analysing the processes underpinning employee voice as a potential desirable form of employee voice as well as outlining areas for a future research agenda.
What do professional software developers need to know to succeed in an age of Artificial Intelligence?
Generative AI is showing early evidence of productivity gains for software developers, but concerns persist regarding workforce disruption and deskilling. We describe our research with 21 developers at the cutting edge of using AI, summarizing 12 of their work goals we uncovered, together with 75 associated tasks and the skills & knowledge for each, illustrating how developers use AI at work. From all of these, we distilled our findings in the form of 5 insights. We found that the skills & knowledge to be a successful AI-enhanced developer are organized into four domains (using Generative AI effectively, core software engineering, adjacent engineering, and adjacent non-engineering) deployed at critical junctures throughout a 6-step task workflow. In order to "future proof" developers for this age of AI, on-the-job learning initiatives and computer science degree programs will need to target both "soft" skills and the technical skills & knowledge in all four domains to reskill, upskill and safeguard against deskilling.
one of the only people i've ever worked with who consistently and intentionally hired junior / early career people, and prioritized their mentorship.
Jimmy Lee
One of the highlights of my life is finding incredible webmaster youths to transfer all my remaining skill and resource to ✌️🙌⚔️ Thanks for everything
