Posts tagged Data Quality — AI × software engineering, made practical.
You'll learn why LLM consumers stop sending bad input to your dead letter queue, and how a refusal tool, a provenance envelope and abstention monitoring bring it back.
You'll learn to write data contracts in three layers (shape, meaning, and ownership), where the meaning layer is enforced with reconciliation, distribution, and golden queries, and how the same approach protects RAG fields and pipelines that agents edit.
An agent-assisted dbt refactor passed every test, shipped clean, and quietly inflated regional revenue 2.1x — here's the one-line change that caused it and the test nobody had written to catch it.
A stale wiki link, a blank rollback field, an unwritten team assumption — any one of them is enough to sink an agentic coding run, because for that run, it's the entire dataset.