The First 90 Days as a Junior Engineer
What to focus on, what to let go of, and how to build credibility in a new engineering role without burning out trying to prove yourself.
What to focus on, what to let go of, and how to build credibility in a new engineering role without burning out trying to prove yourself.
How Apache Kafka works under the hood - what makes it different from a traditional message queue, and how producers, consumers, and partitions fit together.
The difference between ETL and ELT, how modern data pipelines are built, and how to choose the right approach based on your actual constraints.
How to integrate AI coding tools effectively, where they genuinely help, where they mislead you, and what you still need to understand yourself.
What is actually happening inside a large language model - tokens, attention, context windows, and why these systems behave the way they do.
What separates a unit test that catches real regressions from one that only verifies your test setup - and how to write tests that stay useful as code changes.
What unit, integration, and end-to-end tests are actually good for, and how to find the right mix so your test suite catches real bugs without being a maintenance burden.
Why guessing at performance bottlenecks wastes time, and how to use profiling tools to find what actually needs fixing before you touch the code.
A practical look at the most common web application vulnerabilities, what actually causes them, and the patterns that consistently prevent them.
How to pick the right metrics for your service, understand the different metric types, and avoid the trap of measuring everything.
What Docker actually is under the hood - from a Dockerfile to a running container, and where registries fit in.
Caches speed things up until they serve stale data. Understanding the tradeoffs at each caching layer - and how invalidation actually works - is what keeps them from becoming bugs.