Hood Language Model

HLM is a concept for a Robinhood-native model and agent layer: an intelligence surface designed to understand ecosystem language, route tasks, maintain context, use tools and prepare permissioned onchain actions.

The interface is a product concept. Animated terminal activity and chat responses are simulated UI behavior, not evidence of a deployed production model.

Robinhood-native

Understands chain vocabulary, projects, wallets, market structure and community workflows.

Agent-first

Designed to plan, route and coordinate specialized workers rather than answer every task with one model.

User-controlled

Research and preparation can be automated; sensitive wallet actions remain explicit and permissioned.

Core objective

Turn a user request into a verifiable output through retrieval, reasoning, routing, tool use and review—while clearly separating known facts, live data, inference and simulated content.

Architecture

HLM is designed as a modular system rather than one monolithic chatbot.

01 / INGESTInterpret intent, entities, constraints and risk.

02 / RETRIEVELoad relevant session, public, onchain and user-provided context.

03 / PLANDecompose the task and choose a verification strategy.

04 / ROUTESelect the smallest capable model, agent or tool.

05 / VERIFYCheck outputs, provenance, permissions and failure states.

Router

The router classifies complexity, latency needs, tool requirements and risk. Simple requests should use a lightweight model; code, market research, multimodal tasks or agent workflows can be routed to specialized components.

Tool ecosystem

Planned adapters include search, chain indexers, wallet readers, contract inspection, analytics, code execution, document retrieval, notifications and automation.

Model family

HLM Base

General conversation, reasoning, summarization and structured generation.

HLM Agent

Multi-step workflows, tool orchestration and long-running tasks.

HLM Code

Smart-contract review, frontend code, scripts and technical explanations.

HLM Markets

Market context, dashboards, alerts and risk-aware synthesis.

HLM Vision

Images, interfaces, charts, screenshots and multimodal documents.

HLM Router

Request classification and model/tool selection.

Future naming

Model releases may use explicit capability and scale labels such as HLM-Base, HLM-Agent and HLM-Code. No parameter counts or benchmarks are claimed at this stage.

Agent runtime

Agents are specialized workers with bounded permissions, clear inputs and auditable outputs.

Scout

Research, source collection and ecosystem monitoring.

Pulse

Market and chain alerts based on user-defined conditions.

Forge

Code generation, testing and deployment preparation.

Ledger

Wallet history, treasury reporting and transaction explanations.

Relay

Automation, notifications and recurring workflows.

Quill

Documentation, articles and structured communication.

Execution boundary

An agent may prepare a transaction, estimate impact and explain risk. It should not silently sign or broadcast sensitive actions without a clear permission and confirmation flow.

Memory

HLM memory is envisioned as layered context with explicit scopes.

Turn memory

The immediate conversation and active task state.

Session memory

Temporary goals, documents, decisions and tool results.

Persistent memory

User-approved preferences, projects and long-term agent state.

Control

Users should be able to inspect, export, edit and delete persistent memory. Sensitive data should not be retained by default merely because it appeared in a conversation.

Retrieval

Relevant memory is retrieved based on task context and confidence. The model should not present uncertain recollections as verified facts.

Onchain layer

The onchain layer connects language understanding to chain data and ecosystem actions.

READBalances, token metadata, contracts, transactions and positions.

INTERPRETExplain activity, risks, permissions and economic mechanics.

PREPAREConstruct a transaction or workflow for user review.

CONFIRMRequire explicit approval before sensitive execution.

Data integrity

HLM should display the network, timestamp, source and contract address for live claims. Contract identity must be verified rather than inferred from a token name or social account.

Token

HLM contract address: TBA. Token mechanics, launch venue and release timing have not been finalized.

Safety and verification

Separate facts, estimates, inferences and simulations.
Never guarantee market outcomes or imply that automated actions are risk-free.
Require explicit confirmation for wallet writes and irreversible actions.
Use allowlists, spend limits, session limits and transaction previews.
Preserve logs for agent steps and tool calls when privacy allows.
Fail visibly when a data source, tool or verification step is unavailable.

The best agent is not the one that acts the fastest. It is the one that knows when it must stop and ask.

Developer surface

The planned developer layer is modular and provider-agnostic.

Chat API

Messages, streaming output, structured schemas and citations.

Agent SDK

Tools, workflows, state, permissions and observability.

Memory adapters

Local, encrypted, database and user-controlled storage backends.

Tool registry

Typed tool contracts, authentication and permission scopes.

Evaluation

Task suites, regression tests, safety checks and cost tracking.

Interfaces

Web, terminal, wallet, bots and embedded application surfaces.

Status

This site presents the intended product direction. Public repositories, APIs, model weights, SDK packages and deployment instructions will be linked only when they exist.