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Product Overview

Mission

Deliver a prediction-market experience on Solana where AI agents propose markets, human curators ensure quality, and zkTLS proofs resolve outcomes without trusted third parties.

User Segments

  • Creators: Individuals or communities who want to spin up markets quickly using the AI-assisted studio.
  • Curators: Human reviewers who validate AI proposals before they become immutable on-chain markets.
  • Traders & Liquidity Providers: Participants who browse, evaluate, and trade based on transparent resolution criteria.
  • Proof Submitters: Operators (initially core team) who generate zkTLS attestations and finalize markets.

Experience Pillars

AI-Assisted Market Studio

  • Conversational flow powered by OpenAI/Anthropic models for drafting question, resolution criteria, timelines, and initial liquidity configuration.
  • Guardrails surfaced to creators (template hints, required proof source selection, disallowed categories).
  • Output: structured market spec ready for curator review, including proof expectations and discovery metadata.

Human Curation

  • Queue view showing pending AI proposals with diff view between AI suggestion and last human edit.
  • Accept/Request changes/Reject actions; accepted markets trigger contract deployment.
  • Feedback loop into the AI agent to improve future drafts (prompt tuning, heuristics).

Market Discovery Hub

  • Pump.fun inspired landing page with live leaderboard (volume, open interest, time since creation) dressed in Arrakis lore.
  • Filters for topic tags, confidence rating, resolution window, and source category (API, news, social).
  • Market detail card: question statement, resolution criteria, Mentat rationale, proof status, key timestamps, and liquidity snapshot.

zkTLS Resolution Lifecycle

  1. Expectation: Market spec records target sources and acceptable timestamp windows.
  2. Proof preparation: Off-chain service generates zkTLS proof(s) once the outcome data is published.
  3. Submission: Proof hash and metadata stored on-chain; complete proof either verified on-chain or referenced for later verification.
  4. Settlement: Smart contract executes payout logic; disputes route through separate governance if implemented later.

High-Level System Components

  • Front-end Web App (Vue 3 + Vite): Creator studio, curator console, discovery feed, market detail pages, proof submission panel.
  • Agent Orchestrator (Python + DSPy): Manages OpenAI/Anthropic interactions, enforces templates, and stores drafts in Postgres/Redis.
  • Curator API (FastAPI): Persists human edits, logs decision trail, and triggers Solana contract calls after approval.
  • Solana Programs:
  • MarketFactory for instantiating markets with metadata, staking, and proof configuration.
  • MarketSettlement for accepting proof artifacts, verifying them (or storing references), and distributing payouts.
  • Proof Service: Integrates with zkTLS stack (e.g., TLSNotary), publishes proof artifacts, and submits results to Solana.
  • Data Indexer: Rust service using rkyv + sled to index market events for discovery UI, analytics, and notifications.

Key Flows

  1. Creation: Creator opens studio → AI drafts market → creator tweaks → curator approves → market deployed on Solana.
  2. Discovery & Trading: Traders browse feed → inspect market detail → enter positions → track proof timeline.
  3. Resolution: Outcome occurs → proof service generates zkTLS proof → submission triggers on-chain verification → market settles → discovery feed updates status.

Open Questions

  • Level of on-chain vs. off-chain zkTLS verification in MVP.
  • Incentive design for proof submitters and curators.
  • Scalability limits of AI prompting versus cached templates.
  • Future path to reduce human curation without losing quality.