Feature Planning

AI-powered feature planning

Write PRDs, break features into tasks, create implementation plans, and hand them to AI agents for execution -- all in the same workspace.

AI-powered feature planning

The Problem

Feature planning is disconnected from implementation

PRDs and feature specs are written in one tool but implemented in another. The translation between planning and coding loses critical context.

  • PRDs are written in Notion or Google Docs, separate from the codebase
  • Requirements lose nuance as they're translated into tickets
  • No way to verify that implementation matches the original spec
  • Planning artifacts become stale as implementation reveals new constraints

How It Works

Plan, specify, and implement in one place

Write the spec
1

Write the spec

Use plan mode to create structured PRDs with acceptance criteria, edge cases, and architecture decisions. Your agent helps you think through the details.

Break into tasks
2

Break into tasks

Your agent breaks the spec into implementable tasks with clear scope, linked to specific files and modules that need to change.

Execute with agents
3

Execute with agents

Launch agent sessions for each task. The agents read the original spec and task context, then implement with full awareness of the plan.

The Difference

Plans that agents can execute

Without Nimbalyst

  • Write PRDs in Notion, convert to Jira tickets, lose context at each step
  • Developers reinterpret requirements differently than intended
  • No feedback loop between implementation discoveries and the spec
  • Finished features diverge from original requirements

With Nimbalyst

  • PRDs live alongside code -- agents read the spec and implement directly
  • Tasks link to specific files and modules for precise scope
  • Implementation discoveries update the plan in real time
  • Agents implement exactly what was specified, with full context

Nimbalyst is the visual workspace for building with Claude Code and Codex