Platform Workflow

How Feature1 Works

From strategy and PRDs to release-ready work — with product intent preserved through every handoff

The Feature1 Pipeline

Seven stages from repo connection to validated, release-ready work

01

Connect Your Repository

Onboard your GitHub, GitLab, or Bitbucket repository in minutes. Feature1 securely indexes your codebase and establishes a persistent connection to track changes over time.

GitHubGitLabBitbucketOAuth 2.0
02

Build Domain Intelligence

The AI constructs a semantic knowledge graph of your codebase — understanding modules, dependencies, conventions, and architectural patterns. This graph powers every downstream decision.

Knowledge GraphSemantic AnalysisAST ParsingDependency Mapping
03

Plan Features

Turn strategy, PRDs, backlog priorities, and product objectives into sprint-ready scope. Feature1 keeps rationale, risks, dependencies, effort estimates, acceptance criteria, and implementation plans linked for product managers and their collaborators.

PRD to SprintObjective ContextRisk AnalysisHandoff Ready
04

Generate User Stories & ACs

User stories and acceptance criteria are auto-generated from feature analysis, fully aligned with your domain model. Each story is traceable, testable, and ready for implementation.

User StoriesAcceptance CriteriaBDD FormatTraceability
05

Implement with AI

Move approved scope into a controlled engineering handoff. Use Copilot for Driver-Navigator implementation, or choose Autopilot for well-scoped work where AI can implement acceptance criteria between human approval gates.

CopilotAutopilot OptionApproval GatesStyle Consistent
06

Validate with QA Feedback

Acceptance criteria checks, preview validation, bug feedback, and QA notes stay connected to the original objective and PRD. Teams can see what passed, what changed, and what still needs attention before release.

AC ValidationPreview ChecksQA FeedbackIntent Linked
07

Review & Communicate

A pull request is created with a full diff, validation notes, QA feedback, and implementation context. Release notes and stakeholder updates trace shipped work back to objectives, PRDs, validation outcomes, QA feedback, and customer value. Your team manages merge and deployment through its CI/CD pipeline.

PR ReadyValue TraceabilityRelease NotesStakeholder Updates

Choose Your Mode

Two ways to work with Feature1 — pick the level of control that suits your team

Autopilot

HITL Autopilot

Feature1 automates selected implementation work between approval gates. Product and engineering leaders keep control of scope, validation, QA feedback, and release communication while AI helps move well-defined work toward PR review.

  • Automation between human approval gates
  • Implementation option for well-scoped work
  • Validation results and QA feedback captured
  • Objective-linked release notes on every merge
  • Continuous learning from merged code
  • Ideal for repeatable engineering tasks
Best for: Teams who want maximum velocity with minimal overhead
Copilot

Driver-Navigator

The MCP client (Claude Code or Codex CLI) drives the implementation while you navigate — guiding design decisions and architecture choices at each step.

  • Driver-Navigator pair programming pattern
  • MCP client (Claude Code or Codex CLI) drives code
  • You navigate design decisions and architecture
  • Guide each step without writing it yourself
  • Full audit trail of every AI action
Best for: Teams who want AI leverage while keeping architectural ownership

MCP Integration

Connect Claude Code and other AI agents directly to Feature1 via the Model Context Protocol

What is MCP?

The Model Context Protocol (MCP) is an open standard that lets AI agents securely connect to external tools and data sources. Feature1 exposes its workflow through an MCP server so compatible agents can carry planning context, implementation tasks, validation status, and PR metadata across the delivery loop.

Claude Code
Cursor
Windsurf
Custom Agents
feature1-mcp-server
create_feature()// submit PRD-backed scope
get_planning_context()// fetch codebase intelligence
list_user_stories()// retrieve generated stories
implement_ac()// trigger AI code generation
record_validation()// link AC checks and QA feedback
create_pr()// open PR with value-linked release notes
Secure by Default
OAuth-scoped tokens, no plain-text secrets
Real-Time Context
Always-fresh codebase knowledge graph
Bidirectional
Read and write across the full workflow
Agent Agnostic
Works with any MCP-compatible client
Workflow State
Track progress across every pipeline stage
REST Fallback
Standard API available alongside MCP

Ready to ship faster?

Connect your repo, preserve product intent from PRD to sprint, and give your team clearer validation before release.