Decision layers on Hokusai

Each layer is a shared model that picks something — which model to call, which tool to use, which context to retrieve. Integrators pay a per-decision fee. Contributors hold a position in that fee stream.

Live

The router

Technical Task Router · HTASK

Picks the right model, prompt, and harness for each coding task, based on a shared learned policy trained on real outcomes. The first decision layer built on Hokusai.

StatusLive
Current benchmark0.4211 cost-adjusted task success
DeltaOne reward250,000 HTASK per percentage-point lift
TokenHTASK — position in the router's fee stream

Decision layers we want built

Each of these is a routing, selection, or retrieval problem currently solved with hardcoded rules or absorbed into lab margin. If you've already built one internally — or have a thesis on how to build one — Hokusai's primitives turn it into a shared model that integrators pay to use and contributors own a piece of.

Open bounty

Tool selection

Coding agents call dozens of tools and MCPs. Which one fits a given task is mostly guesswork or hardcoded rules.

A learned policy could route to the right tool based on outcome data from many harnesses.

Propose this layer
Open bounty

Retrieval policy

Every agent decides what to pull from a user's context, memory store, or codebase. That decision shapes every downstream call.

A shared retrieval policy, trained on what actually got used in successful runs, beats per-harness heuristics.

Propose this layer
Open bounty

Code-review critic selection

Different reviewer models catch different classes of bug. No one's measuring which catches what.

A router that picks the right critic for the diff — trained on real PR outcomes, not synthetic benchmarks.

Propose this layer
Open bounty

Prompt policy

Prompt strategies are tribal knowledge. Engineers swap notes; nobody measures.

A shared model for which prompt strategy fits which task, owned by the engineers who improve it.

Propose this layer

Earlier reference models

These predate the decision-layer focus and demonstrate the protocol's measurement and reward primitives — DeltaOne, bonding curves, on-chain attribution — in non-routing domains. Useful as proof the mechanics work; not the direction Hokusai is going.

Have a decision layer worth building?

If you've identified a routing, selection, or retrieval problem that sits in internal scripts today — or gets absorbed into lab margin — Hokusai gives you DeltaOne measurement, fee-backed tokens, and on-chain attribution from day one.