json

Agents and integrations depend on the model returning valid, schema-conforming output. The signal is stacking constrained decoding, schema validation, and retries, rather than trusting a prompt to do the job. Here is the production-reliability answer.

The classic recursive-descent exercise with an applied-AI twist: the JSON your model streams stays truncated mid-token for the whole generation. What matters is a clean strict parser plus a small repair layer, not a second parser. The code follows.

Modern warehouses store JSON natively, and querying it well sets strong data engineers apart from the rest. The signal is path access plus unnesting, and a clear call on when to flatten hot fields versus keep the schema-on-read flexibility.

Pulling a scalar by path is easy; an array of objects three levels deep is where people freeze. The signal is LATERAL FLATTEN / UNNEST to explode arrays into rows plus a clear rule for when to flatten versus query in place.