# PromptDAG Builder

> 🕸️ **Visual Suggestion**: Consider adding a flowchart showing how a multi-node prompt graph connects nodes like summarizer → classifier → action decision prompt.

The ***PromptDAG*** Builder is a visual and programmatic interface for designing and executing multi-prompt workflows using a directed acyclic graph (DAG) abstraction. It enables developers and non-technical users to construct complex semantic flows by chaining prompts into structured logic graphs.

```
┌────────────────────────────────────────────────────────────────────────────────┐
│                          PROMPTDAG EXAMPLE WORKFLOW                            │
│                                                                                │
│   ┌───────────────┐     ┌─────────────────┐     ┌───────────────────┐          │
│   │               │     │                 │     │                   │          │
│   │  Document     │────▶│  Summarizer     │────▶│  Sentiment        │          │
│   │  Extractor    │     │                 │     │  Analyzer         │          │
│   │               │     │                 │     │                   │          │
│   └───────────────┘     └─────────────────┘     └───────┬───────────┘          │
│                                                         │                      │
│                                                         ▼                      │
│                                           ┌─────────────────────────┐          │
│                                           │                         │          │
│                                           │  Conditional Branch     │          │
│                                           │                         │          │
│                                           │                         │          │
│                                           └────────┬────────────────┘          │
│                                                    │                           │
│                          ┌──────────────────────┐  │  ┌────────────────────┐   │
│                          │                      │  │  │                    │   │
│                          │  Negative Feedback   │◀─┴─▶│  Recommendation    │   │
│                          │  Handler            │     │  Generator         │   │
│                          │                      │     │                    │   │
│                          └──────────────────────┘     └────────────────────┘   │
│                                                                                │
└────────────────────────────────────────────────────────────────────────────────┘
```

**1. Conceptual Model**

Each prompt within PromptHub can act as a node within a DAG. These nodes can:

* Accept input from previous nodes
* Transform or reformat data
* Invoke LLMs or agent modules
* Produce intermediate outputs for downstream tasks

DAG edges define data flow, execution order, and conditional branching.

**2. Features**

* **Visual Editor**: Web-based composer to drag-and-drop prompt modules, connect them, and assign parameters
* **Parameter Propagation**: Output of one node can be passed as dynamic input to the next
* **Conditional Execution**: Nodes can execute only if certain outputs match predicates
* **Parallel Execution**: Independent branches can be executed in parallel and merged downstream
* **Reusable Subgraphs**: DAG fragments can be saved, versioned, reused, and shared

**3. On-Chain Representation**

Each ***PromptDAG*** is hashed and stored on-chain as a unique flow asset. This allows:

* Transparent and reproducible agent behavior
* Version tracking and flow auditing
* DAG-specific licensing and monetization

**4. Integration with Agents**

***PromptDAGs*** can be directly consumed by:

* Autonomous agents (e.g. ***AutoGPT***) to replace custom toolchains
* Smart contracts that call semantic AI modules
* DAO workflows for dynamic governance proposals

The DAG builder transforms ***PromptHub*** from a prompt registry into a full-fledged semantic orchestration layer for AI-native computation.