What is an Implementation?
An Implementation is an actionable breakdown of a Plan containing:- Epics - Logical groupings of related work (e.g., “Backend API”, “Frontend UI”, “Testing”)
- Issues - Individual work items with descriptions, acceptance criteria, and code context
- Code Context - AI-identified files and patterns relevant to each issue
- Export Capability - Bulk export to external project management platforms
Product Planning Hierarchy
Implementations fit into Kasava’s planning hierarchy:Accessing Implementations
You can access Implementations in two ways:From the Implementations Page
Open the Sidebar
Click Implementations in the main sidebar navigation to go to the Implementations list
Browse Your Implementations
View all your implementations displayed as cards in a responsive grid layout
The list view displays:
- Implementation cards - Each showing title, description, status, epic count, and issue count
- Status badges - Draft, In Progress, Completed, or Archived
- Source Plan - Link to the originating Plan
- Creation date - When the Implementation was created
From a Plan
When viewing a Plan, you can quickly access its implementation or create a new one.Creating an Implementation
Implementations are generated from Plans using AI:Click Generate Issues
In the Plan header, click the Generate Issues button. If the Plan already has an implementation, you’ll see a View Issues button instead that takes you directly to the existing implementation.
Select Repository (Optional)
Choose a repository from your organization to enable code context analysis. This helps the AI understand your codebase structure and generate more specific, relevant issues.
Configure Options
Set generation options:
- Include code context - Analyze repository code to generate more relevant issues (requires repository selection)
- Include tests - Generate test-related issues for the implementation
Generation Progress
During generation, you’ll see progress through these stages:- Analyzing Plan requirements - Parsing your Plan content
- Loading repository context - Fetching repository structure
- Searching codebase for relevant files - Semantic code search
- Generating issues with AI - Creating structured issues
- Saving implementation - Persisting the results
What the AI Does
During generation, the AI:- Parses Plan Content - Extracts requirements, user stories, and success criteria from your Plan
- Analyzes Repository - Identifies tech stack, patterns, and directory structure
- Performs Code Search - Finds relevant files for each requirement using semantic search
- Generates Issues - Creates structured issues with code context and implementation hints
- Organizes into Epics - Groups related issues logically by component or feature area
Viewing an Implementation
Click on any Implementation card to view its details.
The detail view shows:
Header Information
- Title and description - Implementation overview
- Status badge - Current state (Draft, In Progress, Completed, Archived)
- Source Plan link - Click to navigate back to the originating Plan
- Creation date - When the Implementation was generated
- Back button - Return to the Implementations list
Statistics Panel
A summary panel shows key metrics at a glance:| Metric | Description |
|---|---|
| Epics | Total number of epic groupings |
| Total Issues | All issues in the Implementation |
| Selected | Issues currently selected for export |
| Estimated | Total estimated hours for all issues |
Epic Sections
Each epic is displayed as a collapsible section showing:- Epic name and color - Visual identifier
- Selection count - How many issues are selected (e.g., “5/8 selected”)
- Issue list - All issues within the epic
Reviewing Issues
After generation, review and edit issues before export:Issue Details
Each generated issue includes:| Field | Description |
|---|---|
| Title | Action-oriented task description |
| Description | Implementation details (collapsible) |
| Priority | Low, Medium, High, or Critical |
| Estimated Hours | Time estimate for completion |
| Status | Draft or Exported |
Issue Row
Each issue row displays:- Checkbox - Toggle selection for export
- Title - Task name (truncated if long)
- Priority badge - Color-coded priority indicator (Low, Medium, High, or Critical)
- Exported badge - Shows “Exported” if the issue has already been sent to a platform
- Description - Truncated preview of the issue description
- Estimated hours - Time estimate displayed on the right (e.g., “4h”)
Managing Selection
Control which issues get exported by using the checkboxes:- Click the checkbox next to any issue to toggle its selection
- The epic header shows the current selection count (e.g., “3/5 selected”)
- Only selected issues will be included when you export to an external platform
Epics
Epics group related issues for better organization:Default Epics
AI typically generates epics based on your codebase structure:- Data Model - Database schema and migrations
- Backend API - API endpoints and services
- Frontend UI - User interface components
- Business Logic - Core application logic
- Testing - Unit, integration, and e2e tests
- Documentation - Technical and user documentation
Epic Display
Each epic section shows:- Collapsible header - Click to expand/collapse
- Color indicator - Visual categorization
- Epic name - Descriptive title
- Selection badge - Count of selected issues
- Description - Epic overview (if provided)
- Issue list - All issues in the epic
Unassigned Issues
Issues without an epic assignment appear in a separate “Unassigned Issues” section at the bottom of the Implementation.Exporting to Platforms
Export selected issues to your project management platform:Select Platform
Choose your target platform:
- GitHub Issues - Export as GitHub issues with milestone grouping
- Linear - Export to Linear with project/cycle organization
- Jira - Export to Jira with epic linking
- Asana - Export to Asana with project/section organization
Platform-Specific Options
GitHub Issues
- Repository - Target repository for issues
- Labels - Apply labels to created issues
- Create Milestones - Map epics to milestones
Linear
- Team - Target Linear team
- Project - Optional project assignment
- Cycle - Optional cycle assignment
Jira
- Project - Target Jira project
- Issue Type - Default issue type for created issues
- Create Epics - Map Implementation epics to Jira epics
Asana
- Workspace - Target Asana workspace
- Project - Target project
- Create Sections - Map epics to project sections
Epic Mapping
Epics are mapped to platform concepts:| Platform | Epic Becomes |
|---|---|
| GitHub | Milestone |
| Linear | Project or Cycle |
| Jira | Epic issue type |
| Asana | Section |
After Export
Exported issues:- Are marked with an Exported badge in Kasava
- Include links back to the platform issue
- Show the platform issue identifier
- Cannot be re-exported (prevents duplicates)
Code Context
When code context is enabled during generation, each issue includes AI-identified relevant information:Affected Files
Files that will likely need modification:Related Patterns
Existing patterns in your codebase to follow:Suggested Approach
AI-generated implementation hints based on your codebase patterns and conventions.Implementation Status
Track progress through these statuses:| Status | Description | Visual |
|---|---|---|
| Draft | Newly created, issues being reviewed | File icon with outline badge |
| In Progress | Actively being worked on | Clock icon with primary badge |
| Completed | All issues exported and resolved | Checkmark icon with success badge |
| Archived | No longer active | Archive icon with muted badge |
Error Handling
If generation fails, you’ll see an error message with:- Error description - What went wrong
- Retry option - For transient errors (network issues, AI service unavailable)
- Suggestions - Tips to resolve the issue (e.g., try without code context)
- Network connectivity issues
- AI service temporarily unavailable
- Rate limiting (too many requests)
- Repository access issues