Professional growth in tech, skill development strategies, and industry career guidance
Comprehensive guide to creating an optimal home office environment for software developers, covering ergonomics, equipment, lighting, and productivity optimization.
The move from senior to staff is not about technical depth — it's about ambiguity tolerance and system-level thinking. What I observed coaching a dozen engineers through this transition.
DORA metrics are useful proxies. They become harmful when teams optimize the proxy rather than the outcome it was supposed to represent. What I watch instead.
Framing tech debt as a deferred maintenance cost — with an interest rate — resonates with finance-minded executives in ways that 'we need to refactor' does not.
Non-technical executives make decisions about engineering resources. The language and cadence that give them accurate understanding without requiring a CS degree.
The inflection point where IC and management tracks offer similar compensation but different leverage. What I observed in engineers who made each choice — and who was happier two years later.
Not all open source contributions are equal on a resume. Code review quality, documentation improvements, and sustained maintenance signal different things than a single feature PR.
Reorganizations are information events. The engineers who thrive are the ones who treat them that way rather than as purely political events.
We adapted the Dropbox engineering ladder for a 40-person team. Three levels collapsed to two, staff split from senior for legitimate reasons, and the calibration process took six months to stabilize.
The right answer changes with team size, product phase, and how much technical debt is actively slowing delivery. A framework I've iterated on across three companies.
Band compression, competing offer leverage, and the difference between base and total comp. A candid account of compensation negotiation across four role changes.
Hardware startup interviews lean heavily on take-home designs and breadth questions. Big tech interviews optimize for algorithmic depth. Preparing for both simultaneously is inefficient.