Data Engineering
Kafka Fundamentals: Topics, Partitions, and Consumer Groups
How Apache Kafka works under the hood - what makes it different from a traditional message queue, and how producers, consumers, and partitions fit together.
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Data Engineering
Data Pipelines: ETL, ELT, and When Each Makes Sense
The difference between ETL and ELT, how modern data pipelines are built, and how to choose the right approach based on your actual constraints.
AI & Machine Learning
AI-Assisted Coding: How to Use It Without Losing Your Skills
How to integrate AI coding tools effectively, where they genuinely help, where they mislead you, and what you still need to understand yourself.
AI & Machine Learning
How LLMs Work: A Mental Model for Engineers
What is actually happening inside a large language model - tokens, attention, context windows, and why these systems behave the way they do.
Testing
Writing Unit Tests That Actually Catch Bugs
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.
Testing
The Testing Pyramid: Why Balance Matters More Than Coverage
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.
Performance
Profile First, Optimize Second
Why guessing at performance bottlenecks wastes time, and how to use profiling tools to find what actually needs fixing before you touch the code.
Security
OWASP Top 10: The Vulnerabilities That Keep Coming Back
A practical look at the most common web application vulnerabilities, what actually causes them, and the patterns that consistently prevent them.
Observability
Metrics: What to Measure and What to Ignore
How to pick the right metrics for your service, understand the different metric types, and avoid the trap of measuring everything.
Infrastructure
Docker from Scratch: Images, Containers, and Registries
What Docker actually is under the hood - from a Dockerfile to a running container, and where registries fit in.
Performance
Caching Strategies: Where to Cache and What to Invalidate
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.
Databases
Indexes: How They Work, When They Help, When They Hurt
An index is a tradeoff - faster reads at the cost of slower writes and more storage. Knowing how B-trees work and how the planner uses them tells you when that tradeoff is worth making.