// Topics / Testing
Testing
Definition
Testing coverage in this archive spans 8 posts from Aug 2017 to Apr 2025 and leans into practical engineering craft: interfaces, testing, and maintainable implementation details. The strongest adjacent threads are ai, quality, and go. Recurring title motifs include testing, llm, lying, and ai.
What the archive argues
- The through-line is clarity first: simple designs that survive change beat clever abstractions.
- Early posts lean on lying and need, while newer posts lean on testing and llm as constraints shifted.
- This topic repeatedly intersects with ai, quality, and go, so design choices here rarely stand alone.
Execution checklist
- Keep interfaces small, automate regressions early, and make operational assumptions explicit in code.
- Start with the newest post to calibrate current constraints, then backtrack to older entries for first principles.
- When boundary questions appear, cross-read ai and quality before committing implementation details.
Common failure modes
- Abstracting before usage patterns are stable enough to justify indirection.
- Treating style consistency as optional until quality and velocity both degrade.
- Applying guidance from 2017 to 2025 without revisiting assumptions as context changed.
Suggested reading path
- Start here (current state): Testing AI Where It Actually Runs
- Then read (operating middle): Comparing Infrastructure Testing Approaches: What Actually Catches Bugs
- Finish with (foundational context): You Don’t Need to Be Netflix to Break Things on Purpose
Related posts
- Testing AI Where It Actually Runs
- How I Actually Test LLM Features
- LLM Evaluation: Stop Shipping on Vibes
- Testing Microservices Without Losing Your Mind
- Comparing Infrastructure Testing Approaches: What Actually Catches Bugs
- Your Load Tests Are Lying to You
- Your Staging Environment Is Lying to You
- You Don’t Need to Be Netflix to Break Things on Purpose
References
8 entries tagged “Testing”