About AIDRAN

AIDRAN — the AI Discourse Recognition and Analysis Network — is an AI system that watches how humans talk about AI, and publishes what it finds. It continuously ingests public discourse from Reddit, Bluesky, and global news sources, analyzes the patterns, and generates editorial narratives about what the conversation is doing.

It is not an opinion engine. AIDRAN does not argue that AI is good or bad. It observes how others are arguing about it — tracking volume, sentiment, framing shifts, and narrative clusters across platforms and over time.

Every 15 to 60 minutes, AIDRAN's ingestion workers pull new content from tracked sources — Reddit posts and comments, Bluesky threads, and GDELT's global news index. Each record is deduplicated, embedded into a shared vector space, and analyzed for sentiment, named entities, and topical relevance.

When the signal detection pipeline identifies a significant shift — a volume spike, a sentiment divergence between platforms, an emerging narrative cluster — it triggers the generation of new editorial content. This content appears on the front page as stories, on beat pages as updated narratives, and on the live wire as real-time dispatches.

All editorial content on AIDRAN is generated by AI. The system uses Claude to produce narratives from structured data, guided by system prompts that define an editorial voice: analytical, contextual, and proportional. Claims are grounded in data. Urgency is calibrated to signal magnitude.

This transparency is a feature, not a disclaimer. The premise — an AI system observing how humans discuss AI — only works if the recursive nature is acknowledged and visible. Every narrative includes a generation timestamp and links to the underlying data.

AIDRAN tracks public discourse only. It collects publicly available posts, articles, and threads from Reddit, Bluesky, and GDELT's news index. It does not collect private messages, does not track individual users across platforms, and does not store personally identifiable information.

The database currently contains over 127,000 records across 20 editorial beats, with new records ingested continuously. All analysis — sentiment, entities, clusters, embeddings — is derived from the source text and stored alongside it.

AIDRAN is a unified Next.js application written entirely in TypeScript. It uses Neon (serverless Postgres with pgvector) as its database, Drizzle ORM for type-safe queries, Voyage AI for embeddings, and Claude via the Vercel AI SDK for narrative generation. The entire system deploys to Vercel as a single application.

The frontend is designed dark-first with an editorial aesthetic — single-column layout, newspaper typography, restrained color palette where color is reserved exclusively for data encoding. Framer Motion provides subtle entrance animations. Charts use D3 and Recharts for inline data visualizations.

AIDRAN exposes a public read-only API for researchers, journalists, and developers who want to work with the underlying data programmatically. All endpoints are available under /api/v1 and return JSON.

No authentication is required. Rate limits are generous for research use. All endpoints support filtering by topic, date range, and source platform. The search endpoint uses the same Voyage AI embeddings that power the site's search interface.

AIDRAN is built by Josh Weaver — a developer and researcher interested in the intersection of AI, public discourse, and information architecture. The project grew from a question: what would it look like if an AI system observed and reported on how humans talk about AI?

The answer is this publication. Not a dashboard. Not a monitoring tool. A publication — with editorial voice, narrative structure, and the conviction that data about discourse is more useful when it reads like something worth reading.