#Engineering
10 notas · última:
Notes on Distributed Systems for Young Bloods
A set of practical lessons for new distributed systems engineers, emphasizing failure, coordination costs, backpressure, metrics, percentiles, capacity, feature flags, and service extraction.
How Top Engineers Structure Their Day to Maximize Their Productivity Without Burnout
The page argues that engineers can ship more by managing energy instead of time, matching deep work to peak hours, batching shallow tasks, and using location and automation to protect focus and reduce burnout.
Goal setting for productive engineers
The post contrasts top-down goals with tiny experiments for engineers working in unstable environments, using the motivation equation to explain when each approach helps or fails.
Personal Finance for Engineers 🏦
The article argues that personal finance matters for engineers because they often earn well, face career volatility, and can benefit a lot from starting early. It ties money habits to long-term outcomes like savings, retirement, and flexibility in choosing jobs.
Working the Human System Within Companies
00:38:11 — Working the Human System Within Companies
Separating Technical and People Work Causes Crisis
00:14:01 — Separation of Technical and People Work Causes the Crisis
AI as Amplifier: Clarity or Dysfunction
00:10:07 — AI as Amplifier: DORA Report on Clarity vs Dysfunction
Writing an Awesome Resume
The post argues that a strong engineering resume should be concise, specific, and tuned to hiring pipelines, with clear sections, honest skills, and careful wording.
Don't Call Yourself A Programmer, And Other Career Advice
The post argues that engineers are hired to create business value, not to code for its own sake, and advises readers to focus on revenue, cost reduction, communication, networking, and negotiation rather than title, stack, or academic status.
Providence: Failure Is Always an Option
Jason Punyon revisits Providence’s year-long build and argues that the project failed slowly because it was too large, relied on speculative technology choices, and spent too long on incidental work instead of validating the models in production.