> For the complete documentation index, see [llms.txt](https://whitepaper.after-bell.uk/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://whitepaper.after-bell.uk/roadmap/phase-2-scale.md). # Phase 2: Scale Defines the roadmap target for expanding AFTERBELL’s markets and operations. ### From MVP to scale Phase 2 covers **Week 7–12**. Its purpose is to scale the product beyond the MVP target and add AI agent integration so bots can trade programmatically. Phase 1 seeks to prove the core product works. Phase 2 seeks a larger footprint: more markets, more stated TVL, and more traders. It also moves beyond exclusively manual interaction by naming programmatic trading as a roadmap capability. These are roadmap targets. They do not describe current adoption, TVL, market count, or deployed agent functionality. ``` Phase 1: prove the product works ↓ Phase 2: expand the product and add programmatic trading ``` ### Quantitative targets | Metric | Phase 1 | Phase 2 | | -------- | -------: | --------: | | Timeline | Week 1–6 | Week 7–12 | | Markets | 10 | 100 | | TVL | $100K | $1M | | Traders | 1,000 | 10,000 | The progression is a simple arithmetic interpretation of the roadmap: ``` 10 → 100 markets = 10× market-count target $100K → $1M TVL = 10× TVL target 1,000 → 10,000 traders = 10× trader target ``` This arithmetic is not a forecast. It does not predict how quickly adoption occurs or establish a guaranteed outcome. It only describes the relative scale of the Phase 2 targets compared with Phase 1. The target of **100 markets** expands the intended market universe from the MVP’s 10 markets. The **$1M TVL** target expands the stated liquidity and capital target. The **10,000 traders** target expands intended participation. The source does not define volume, retention, active-user rates, revenue, or other performance metrics. {% hint style="info" %} The Phase 2 values are goals for Week 7–12. They are not current protocol metrics. {% endhint %} ### AI agent integration The major new capability in Phase 2 is: **AI agent integration so bots can trade programmatically.** At a conceptual level, this means trading interaction is not limited to a person operating the frontend manually. A programmatic agent can create trading intent and use the protocol’s trading path. ``` AI agent → programmatic trading intent → signed order / trading interface → off-chain CLOB → on-chain settlement ``` The agent capability connects to the existing architecture rather than replacing it. The CLOB remains the off-chain matching layer. `CTFExchange` remains the on-chain settlement boundary. Outcome positions continue to be represented through the protocol’s ERC-1155 token architecture. The roadmap does not specify an agent SDK, API, authentication method, endpoint, wallet architecture, strategy framework, autonomous execution engine, AI model, or agent marketplace. This page therefore defines the capability only at the supported level: bots can trade programmatically. ### Why programmatic access matters The architectural difference is between a person interacting manually through the frontend and an agent interacting programmatically with the trading system. Programmatic access can make the existing CLOB architecture accessible to automated participants. That is the roadmap direction. It does not guarantee higher trading volume, better prices, profitable bots, or superior execution. None of those outcomes are defined by the source. The capability also does not eliminate the protocol’s established boundaries. Orders still follow the stated matching and settlement model. Resolution still depends on Chainlink as the primary input, the Robinhood API as the secondary cross-check, and manual handling when the 5% circuit breaker pauses a market. ### Scale dependencies Scaling the roadmap from 10 to 100 markets, from $100K to $1M TVL, and from 1,000 to 10,000 traders increases the scale at which the underlying architecture must operate. The roadmap depends on the existing product loop continuing to function across more market and participant activity. That dependency includes the frontend for normal interaction, the Node.js and WebSocket CLOB for matching, Robinhood Chain and the smart contracts for settlement, USDG as the settlement asset, and the oracle-resolution path for completed markets. The source does not specify particular infrastructure upgrades, database design, cloud services, indexing, or latency solutions. No such implementation should be inferred from the scale targets. ### What success would demonstrate Phase 2 success means pursuing the stated Week 7–12 targets: ``` 100 markets + $1M TVL + 10,000 traders + AI agent integration for programmatic bot trading ``` It would demonstrate expansion beyond the MVP scope and the addition of programmatic trading as a roadmap capability. It would not prove that liquidity is permanent, that revenue projections will materialize, or that agents provide a particular market outcome. AFTERBELL remains under development. Smart contracts are not yet audited, and an audit is planned before mainnet. These limits remain relevant as the roadmap moves toward broader participation. ### Transition to Phase 3 Phase 2 expands participation and market breadth. Phase 3 changes the direction from a standalone prediction-market venue toward composability with additional financial primitives and environments. ``` Phase 1 — MVP → prove the core product Phase 2 — Scale → expand market, user, and liquidity targets; add programmatic trading Phase 3 — Compose → add options hedging, cross-chain markets, and structured products ``` Phase 3 is a future roadmap phase. Its integrations are not current deployed capabilities. ### Current status This roadmap is documented in whitepaper **v0.1, September 2026**. Revenue projections are not proven, organic liquidity is not guaranteed, and AFTERBELL does not currently have a token. It is a product, not a token launch. --- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. 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