AI workflows
LLM Feeds API: Build a Source-Grounded Context Pipeline
Turn changing feed items into selected, traceable context using sensible chunking, retrieval tests, freshness rules, and citation checks.
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Data quality
Connected ideas across feed formats, practical engineering, and thoughtful AI workflows.
Read about preserving meaning as information moves between sources, records, and answers. Units, provenance, story revisions, and source citations all influence whether a result is useful for its intended task. Use this collection to define what your project considers incomplete, stale, conflicting, or unverifiable. Avoid reducing quality to a single score before you understand the underlying dimensions. A missing unit and an outdated source need different responses. These articles show how to make those distinctions visible in the record and in the consuming interface.
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News & publishing
News Feeds API Workflows: Deduplication, Corrections, and Attribution
Design a newsroom-friendly feed workflow that preserves publisher identity, handles revised stories, and separates clustering from certainty.
Feed foundations
Data Feeds API Design: Schemas, Provenance, and Change Events
Create a feed contract that explains units, missing values, corrections, and deletions before those details become production surprises.