> ## Documentation Index
> Fetch the complete documentation index at: https://dev.haico.gr/docs/llms.txt
> Use this file to discover all available pages before exploring further.

# What is HAI-Co²

> The Human-AI Co-Construction framework: a single shared solution, four co-owned surfaces, and how it differs from RLHF and assistance games.

**Human-AI Co-Construction (HAI-Co²)** frames human-AI collaboration as the *joint construction
of a single shared solution*. Rather than the human prompting and the model replying, both
parties read and write the **same** typed workspace and refine one artifact together until it
meets a goal they co-own.

## The four shared surfaces

Everything the human and the agent collaborate over lives in four surfaces, each a concrete UI
panel backed by concrete state. Both sides can read and edit all of them.

<CardGroup cols={2}>
  <Card title="Objective & constraints: Uᵗ" icon="bullseye">
    The agent's one-line read of the goal (the **Objective**) plus the decoded **preferences**
    (hard / soft constraints). Co-owned: the agent proposes, the user can edit or lock.
  </Card>

  <Card title="The plan: X_j" icon="list-tree">
    A depth-ordered, numbered **plan** of todo steps, the agent's own execution ledger, ticked
    off as it works.
  </Card>

  <Card title="The working artifact: X̂" icon="file-pen">
    The **document** (and typed artifacts such as charts) in the centre panel, the object being
    built together.
  </Card>

  <Card title="The conversation: I" icon="comments">
    The **chat** and its full message history (the informational state), the channel used to
    negotiate everything else.
  </Card>
</CardGroup>

Both parties read and write the one shared workspace, and the agent advances it by running a ReAct turn over those four surfaces:

```mermaid theme={null}
flowchart TD
    Human["Human"]
    Agent["Agent ReAct turn · policy π"]

    subgraph Workspace["Shared workspace"]
        U["Objective and constraints · Uᵗ"]
        X["Plan · X_j"]
        Xhat["Document and artifacts · X̂"]
        I["Conversation · I"]
    end

    Human -->|"read and write"| Workspace
    Agent -->|"read and write"| Workspace
    Workspace -->|"current state"| Agent
    Agent -->|"refines toward the co-owned goal"| Workspace
```

## How the implementation maps to the model

| HAI-Co² object             | Implementation                                                                  |
| -------------------------- | ------------------------------------------------------------------------------- |
| `X̂` (working artifact)    | Document + typed artifact rows                                                  |
| `X_j` (construction space) | Document + the todo plan (a depth-ordered, numbered tree)                       |
| `Uᵗ` (utility / objective) | `objectives` table (the goal) + `preferences` table (hard/soft constraints)     |
| `I` (informational state)  | LangGraph checkpointer (message history) + preference rows + per-turn snapshots |
| `π` (policy)               | The compiled LangGraph ReAct agent                                              |
| Refinement maps `f_j⁻¹`    | LLM calls inside tools                                                          |

See [Architecture](/docs/architecture) for how these pieces connect, and [Agent core logic](/docs/agent-core-logic)
for what the agent sees and does on each turn.

## How it differs from RLHF and assistance games

* **vs. RLHF**: in RLHF humans *rank* finished model outputs to shape a reward; in HAI-Co² the
  human and agent *jointly edit* the artifact and the objective in-flight, so feedback is the
  shared work itself, not an after-the-fact preference label.
* **vs. assistance games**: assistance games have the AI infer a *fixed, hidden* human reward.
  Here the utility `Uᵗ` is **explicit and co-owned**: the Objective and constraints are visible,
  user-editable, and revised as the work evolves rather than guessed at.

A deeper rationale (the defining characteristics, the ethics-by-partnership stance, and the
application domains) is on the **About** page of the [live app](https://haico.gr) and in the
formal paper that accompanies the project.