Loop Engineering's Missing Half
The article argues that engineering education and practice overemphasize analytical problem-solving while neglecting the equally important "loop" of problem formulation, experimentation, and learning from failure. It calls for a more balanced approach that integrates design thinking, iteration, and reflective practice into engineering work.
Background
- This is a post (likely on X/Twitter) by @nsankar (Nikhil Sankar) critiquing loop engineering in software and systems design.
- "Loop engineering" refers to designing feedback loops — the mechanism by which a system senses its environment, compares it to a desired state, and adjusts its behavior (e.g., thermostats, autopilots, algorithmic recommendation systems).
- The "missing half" argument claims that most engineers focus only on the *control* side (tuning parameters, optimizing setpoints) while neglecting the *observation* side (sensor quality, data integrity, latency, and what signals are even worth measuring).
- This mirrors debates in fields like machine learning operations (MLOps), where data quality and monitoring often get less attention than model architecture, or in DevOps, where observability (logs/metrics/traces) is a distinct discipline from deployment automation.
- The core insight: a perfectly tuned controller is useless if its sensors are broken, biased, or measuring the wrong thing — the loop is only as strong as its weakest link.