semantic-search

Keyword

semantic-search

Search as interpretation: embeddings, taxonomies, question routing, and the decisions that make retrieval feel meaningful.

Entries: 2
Latest: July 18, 2026
Type: Keyword

OpenAI Build Week: What Would You Ask Sam?

applied-aiweb-developmentProject: samnavsemantic-searchai-workflowsstart-here 4 min read

OpenAI Build Week: What Would You Ask Sam?

OpenAI emailed me about Build Week with four days left, which meant choosing between several questionable Codex projects and figuring out how to make a meaningful addition to SamNav—an application that was already built, deployed, and working. The answer became “What would you ask Sam?”: a question-first way to navigate Sam Altman’s public writing without pretending to impersonate him. The new system uses SamNav’s existing taxonomy, semantic dossiers, and GPT-5.6 to interpret nuanced questions and plot a grounded route through things he has actually published.

Signal to Strategy: Why Scientific Classification is More than a Labeling Exercise

data-and-classificationProject: signal-to-strategybusiness-intelligenceconference-planningdata-architecturesemantic-searchstart-here 4 min read

Signal to Strategy: Why Scientific Classification is More than a Labeling Exercise

Scientific classification is more than tagging content after the fact. This article argues that classification should function as an interpretive layer inside the data architecture, giving messy scientific and operational records a shared vocabulary that makes them comparable, traceable, and strategically useful. Publications, grants, abstracts, investigator activity, and event signals all describe scientific activity from different angles, but without a durable classification layer they remain difficult to connect. By using Snowflake as the analytical backbone, supported by local validation workflows involving Postgres, Qdrant, OpenAlex, embeddings, and structured JSON outputs, the goal is to create an enrichment system that is inspectable enough to trust and flexible enough to refine. In a conference context, that layer can help identify emerging areas, converging communities, and better evidence for planning decisions.