HivePilot

Overview

HivePilot automates product planning. It generates PRDs, creates tickets, and tracks delivery so teams can stay aligned.

Crew Composition

HivePilot uses a 7-agent hierarchical crew for PRD generation:

Agent	Role
Product Strategist	Coordinates overall strategy (Manager)
Market Analyst	Analyzes market opportunity
User Researcher	Defines personas and journeys
Requirements Specialist	Details functional requirements
Technical Architect	Designs system architecture
Risk Assessor	Identifies risks and mitigations
QA Lead	Ensures PRD quality and completeness

Hierarchical Architecture

HivePilot PRD uses hierarchical process with a GPT-4o manager coordinating GPT-4o-mini workers:

                    ┌─────────────────────┐
                    │  Product Strategist │
                    │   (Manager/GPT-4o)  │
                    └──────────┬──────────┘
                               │
        ┌──────────┬───────────┼───────────┬──────────┐
        ▼          ▼           ▼           ▼          ▼
   [Market]   [User Res]  [Requirements] [Tech]    [Risk]

This provides:

• Better synthesis: Manager coordinates and validates all outputs
• Cost efficiency: 60-70% savings on worker LLM costs
• Higher quality: 9/10 average quality scores vs 7.5/10 for sequential

Learn more: Hierarchical Crew Architecture

Additional Agents

• TicketGenerator: creates structured tickets
• DeliveryAgent: tracks execution progress

Supported Outcomes

HivePilot supports:

• detailed PRDs
• issue tickets and checklists
• progress reports

Inputs

It can work with:

• raw text or feature ideas
• uploaded PDFs, DOCX, or TXT files
• prompt enhancements like product area or priority

Output Format

You will receive:

• structured Markdown docs
• Linear-ready tickets or checklists
• Notion exports for sharing

Revisions

• One revision included
• Gather feedback through the async form
• Progress tracked in the outcome dashboard

Agent Behavior

• Gracefully handles missing context by requesting clarifications
• Agents share context via the MCP for autonomous decisions
• End-to-end latency averages a few minutes depending on ticket volume

Integration Capabilities

Optional integrations:

• Slack threads for context
• Notion for publishing or archiving
• Linear for ticket output
• Google Drive for uploading files

Known Limitations

• Context size up to about 10K words
• English language only
• Limited ability to tune style beyond presets

Troubleshooting

• Regenerate if output fails
• Ensure file uploads are within limits
• Contact support if issues persist

Future Roadmap

• Planned agent upgrades
• Slack thread memory
• Automatic cross-crew chaining