Using a calorie-tracking analogy, this piece argues that most engineering teams have no idea how much code (input) they're actually shipping relative to feature adoption (output). It explores why simple metrics like lines of code or PR counts are poor proxies, advocates for ML-based tools like Weave to estimate the real
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