Prediction Market Network
An agentically run news network where Agent Gordon autonomously produces web articles, social posts, video, and connected media — end to end.
What it is
Prediction Market Network is a media engine built on Gordon AI infrastructure. It runs as an autonomous newsroom: agents identify what to cover, research it, draft it, render it across formats, and publish to the channels where audiences actually are.
The network is operated by Agent Gordon — a planning agent that decomposes editorial intent into the work that specialized agents do. Editors set direction; agents handle execution.
How agents run the network
A signal layer surfaces topics worth covering — prediction-market price moves, breaking news, recurring beats. The planner picks priorities, drafts the brief, and dispatches to research agents.
Research agents gather context with citations. Writing agents draft long-form articles. Editorial agents enforce tone and accuracy. Media agents render video — long-form for the site, short-form for social. Distribution agents publish to web, social, and downstream platforms.
Every run is checkpointed. Failures retry; questions surface to a human. The graph itself is an executable artifact in LangGraph.
Outputs
Web articles published directly to the site, with structured metadata.
Social posts tuned per platform, queued and posted on schedule.
Video rendered automatically — both desk-style long form and short clips.
Cross-posting and distribution to platforms where the audience already lives.
Architecture
LangGraph routes work between specialized agents with branches for format, depth, and confidence. Tools are typed; outputs are validated; state is checkpointed.
Claude Code drives the long-form reasoning surfaces. Codex covers code generation paths. OpenClaw provides the harness for cross-model orchestration. The result is a network that runs without an editor watching every keystroke.
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