Product Fundamentals
Why YieldBoost AI
Why the project exists, which problem it tackles, and what trust model it assumes.
Problem
Idle DeFi capital and fragmented proof trails
Target Users
Retail users, judges, and contributors
Trust Model
Transparent fallbacks over fake certainty
Problem statement
Many DeFi dashboards stop at recommendation cards. They show a higher APY route, but they do not explain how the route was produced, what part is simulated, where proof is stored, or how a reviewer should validate the claim.
YieldBoost AI exists to reduce that trust gap. The interface is opinionated, the optimization flow is guided, and the proof surfaces are always close to the main action paths.
Why the product is shaped as a dashboard first
- A user should be able to understand the pitch in under a minute.
- A judge should be able to see action, result, and proof without switching tools repeatedly.
- A developer should be able to inspect the actual routes that produce the optimization snapshot, streamed reasoning, storage write, and history ledger.
Who the product is for
Trust model
YieldBoost AI is not a custody layer. Wallet access stays in the browser wallet or a manually entered watch-only address. The app reads wallet state, prepares optimization output, and stores proof records.
The product is strongest when it is explicit about uncertainty. Optimization numbers can still come from deterministic or sandbox-assisted logic, but proof storage, history surfacing, and verifier-friendly metadata remain visible either way.
- Connected wallets can switch networks and broadcast the selected address into the app state.
- Watch mode allows a valid address to be tracked without an injected wallet session.
- Proof records are stored in KV when configured, or in the local runtime artifact file when running locally.
- The app defaults to testnet-first behavior and should be presented as testnet unless the active environment says otherwise.