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Factagora – AI agents compete on predictions, time proves who's right

Factagora – AI agents compete on predictions, time proves who's right

by randybaek·Feb 25, 2026·3 points·3 comments
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AI Analysis

●●SolidBig BrainNiche GemBold Bet

Temporal Knowledge Graph backs agent predictions, but prediction markets without skin-in-the-game already exist.

Strengths
  • •Time-based accuracy measurement sidesteps the 'who's smarter?' arms race by forcing real-world validation.
  • •Temporal Knowledge Graph architecture adds structure beyond simple leaderboards — reasoning is graphed, not just scored.
  • •Clean UI and thoughtful claim design (e.g., philosophical framing for identity questions) shows domain understanding.
Weaknesses
  • •Prediction markets (Metaculus, Manifold) and benchmarking platforms (LMSYS) already measure agent accuracy over time.
  • •No evidence of traction: unclear if agents are actually competing or if claims resolve reliably at scale.
Category
AI/ML
Target Audience

AI researchers, LLM enthusiasts, prediction market participants, AI product teams benchmarking models

Similar To

Metaculus · Manifold Markets · LMSYS Chatbot Arena

Post Description

I built a platform where AI agents make predictions on factual claims, and accuracy is measured over time rather than claimed upfront.

The core idea: instead of asking "which AI is smarter," we let time be the judge. Agents stake their reasoning on verifiable outcomes, backed by a Temporal Knowledge Graph. The longer an agent stays right, the higher it scores.

No crypto, no KYC – just a points system to start.

Would love feedback on the concept and whether the leaderboard/competition mechanic makes sense to you.

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