Sparks

Sparks are the fundamental building blocks of collaboration in Flowstate. They transform raw thoughts into structured, actionable artifacts that teams can discuss, refine, and execute.

What Are Sparks?

A Spark is a captured moment of inspiration or need. When you share an idea or request in a Room, Flowstate’s AI analyzes your input and creates a Spark — a structured artifact that preserves your intent while making it easy for others to understand and contribute.

Sparks live inside Rooms, positioned on the canvas where you and your team can see them, discuss them, and move them around as your thinking evolves.

Two Types of Sparks

Flowstate recognizes two distinct types of input and creates the appropriate Spark type automatically:

Ideas

Ideas are creative concepts, proposals, or visions for what could be. When you share an idea, Flowstate generates a Blueprint — a structured document that captures:

• The core concept and vision
• Key features or components
• Potential benefits and impact
• Open questions and areas for exploration
• Version history as the idea evolves

Blueprints help teams move from “what if” to “here’s how” by giving ideas a clear structure without locking them down too early.

Requests

Requests are needs, problems, or asks for specific work. When you share a request, Flowstate generates a Scope of Work — a structured document that captures:

• The problem or need being addressed
• Desired outcomes and success criteria
• Constraints and requirements
• Timeline and priority considerations
• Version history as requirements evolve

Scopes of Work help teams move from “we need something” to “here’s what we’re building” by clarifying expectations and boundaries.

How Sparks Are Created

Creating a Spark is conversational. You don’t fill out forms or choose templates. You just describe what you’re thinking:

1. Open a Room where you want to capture the Spark
2. Share your thought in natural language
3. Flowstate’s AI classifies it as an idea or request
4. A structured Spark appears in the Room, positioned on the canvas

The AI does the heavy lifting of extracting structure from your words. You get a well-organized artifact without the friction of manual formatting.

Spark Structure and Versioning

Every Spark is a living document. As conversations unfold and thinking evolves, Sparks can be updated and refined. Each Spark includes:

• Expandable sections: Click to reveal detailed content without cluttering the view
• Version history: Track how the Spark has evolved over time
• Metadata: Creation date, last updated, contributor information
• Position data: X and Y coordinates on the Room canvas for spatial organization

This structure makes it easy to see the current state of an idea or request while preserving the full history of how it got there.

Positioning and Spatial Organization

Sparks aren’t just listed in a feed. They exist at specific positions within a Room’s canvas. This spatial dimension lets teams:

• Group related Sparks together
• Create visual hierarchies and workflows
• Move Sparks as priorities shift
• Use proximity to show relationships

Think of it like arranging sticky notes on a whiteboard, but with the power of structured data and version control.

Content Moderation

Flowstate includes built-in moderation tools to keep Rooms productive and respectful:

Reporting

Any team member can report a Spark if it contains inappropriate content, violates team norms, or doesn’t belong in the Room. Reports are reviewed by administrators.

Admin Actions

Administrators can hide Sparks that violate guidelines. Hidden Sparks are removed from view but not deleted, preserving the audit trail.

Appeals

If a Spark is hidden, the creator can appeal the decision. Appeals are reviewed by administrators, who can restore the Spark if appropriate.

This moderation system balances openness with accountability, ensuring Rooms remain safe and productive spaces.

Working with Sparks

Viewing Sparks

Sparks appear as tiles on the Room canvas. Each tile shows:

• Spark type (Idea or Request)
• Title or summary
• Creation date
• Current status

Click a Spark to expand it and see the full structured content.

Discussing Sparks

Sparks are designed to be discussed. Use the Room’s chat and voice features to:

• Ask clarifying questions
• Suggest refinements
• Debate trade-offs
• Build consensus

The Spark itself remains the source of truth, while conversations flow around it.

Evolving Sparks

As discussions progress, Sparks can be updated to reflect new insights:

• Add details to sections
• Refine the problem statement
• Update success criteria
• Clarify scope

Each update creates a new version, so you can always see how thinking has evolved.

From Sparks to Action

Sparks are the bridge between conversation and execution:

• Ideas become Blueprints that guide design and development
• Requests become Scopes of Work that define deliverables

By capturing and structuring input early, Sparks help teams move faster from “let’s talk about it” to “let’s build it.”

Best Practices

Be Specific

The more detail you provide when creating a Spark, the better the AI can structure it. Instead of “we need a new feature,” try “we need a way for users to export their data as CSV files.”

Use Rooms Intentionally

Create Sparks in the Room where they’ll be most relevant. If you’re brainstorming product ideas, use a product Room. If you’re tracking support requests, use a support Room.

Review and Refine

Don’t treat Sparks as write-once artifacts. Come back to them as you learn more. Update sections, clarify language, and add new insights.

Leverage Positioning

Use the canvas to organize Sparks visually. Group related Sparks, create swim lanes for different stages, or arrange them by priority.

Moderate Thoughtfully

Use moderation tools to maintain quality, but don’t over-moderate. The goal is productive collaboration, not perfect conformity.

Technical Details

Data Model

Each Spark includes:

• Unique identifier
• Type (idea or request)
• Room association
• Position (x, y coordinates)
• Structured content (varies by type)
• Version history
• Moderation status
• Timestamps (created, updated)

AI Classification

Flowstate uses natural language processing to classify input as ideas or requests. The AI analyzes:

• Intent signals (proposing vs. requesting)
• Language patterns (exploratory vs. directive)
• Context from the Room and previous Sparks

Classification happens in real time, typically within seconds.

Storage and Retrieval

Sparks are stored in MongoDB with full version history. Retrieval is optimized for:

• Loading all Sparks in a Room
• Filtering by type or status
• Searching across content
• Tracking changes over time

Future Enhancements

The Sparks system is designed to grow with your team’s needs. Planned enhancements include:

• Custom Spark types beyond ideas and requests
• Automated linking between related Sparks
• AI-suggested refinements based on team patterns
• Export to project management tools
• Advanced search and filtering

Sparks are where collaboration begins. By capturing and structuring your team’s thinking, they make it easier to move from conversation to action.