Articles.
Notes from the work: product thinking, engineering quality, and what AI tools do well and what they leave to you.
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Metrics and code health
DORA Metrics Are Not Vanity Metrics: How Elite Teams Use Them as a Compass
Most teams treat DORA metrics like a dashboard decoration — check them quarterly, nod at the numbers, change nothing. Elite teams use them as a compass that connects delivery performance to engineering decisions. Here's the difference between observing DORA and using DORA.
Devraj Rajput12 min read
Metrics and code health
Your Dashboards Show Symptoms. Detection Shows the Cause.
DORA metrics tell you delivery is slow. Code coverage says tests are fine. But neither tells you why features take 3x longer than they should. Detection connects the dots — correlating process symptoms to code causes — so you fix what actually matters.
Chirag10 min read
Engineering practices
88% of Your Tests Are Decorative: The Mutation Testing Wake-Up Call
Most test suites look healthy — high coverage, all green. But run mutation testing and you'll discover that 80-90% of tests would still pass even if you deleted the code they claim to test. Here's what decorative tests are, why they're dangerous, and how to fix them.
Chirag8 min read
AI engineering
AI Agents Are Pattern Amplifiers: Why Your Codebase Determines Whether AI Helps or Hurts
AI coding agents don't create quality — they amplify whatever's already there. The 2025 DORA Report confirms it: AI adoption correlates with higher instability. Here's why your codebase determines whether AI accelerates delivery or accelerates chaos.
Chirag7 min read
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