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buildpulse/docs/ROADMAP.md
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2026-05-11 22:49:52 +02:00

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# BuildPulse Roadmap
## Philosophy
Each version must be useful on its own.
Do not build future architecture before the current manual workflow is proven.
## v0.1 — Single-Project Planning Cockpit
Goal:
Create the smallest useful cockpit for one project.
Includes:
- Single project summary
- Feature Plan
- Parking Lot
- Manual Pulse Log
- Markdown/JSON/JSONL export
- Local persistence
Does not include:
- AI
- Phases
- Releases
- Multiple projects
- Real agent integration
## v0.2 — AI Idea Placement
Goal:
Use AI to help classify new ideas.
Potential features:
- AI classify idea as Now / Next / Later / Parking Lot / Reject
- AI suggest reason for placement
- AI suggest smallest safe version
- AI detect scope creep
- AI generate acceptance criteria draft
Build only one or two AI actions first.
Highest-value first AI action:
```text
Classify new idea and suggest placement.
```
## v0.3 — Phases and Releases
Goal:
Add structured implementation planning.
Potential features:
- Phases
- Releases
- Definition of done
- Forbidden features per release
- Required vs optional features
- Release readiness view
## v0.4 — Handoff Workflow Hardening
Goal:
Turn a chosen feature into a sharp, target-specific AI coding brief with as little friction as possible.
Current shipped slices:
- v0.3.1 — focused handoff shortcuts
- v0.3.2 — target-specific handoff presets
- v0.4.0 — one-tap feature handoffs
- v0.4.1 — preview/edit before copy + explicit INTENT controls
Planned slices:
- v0.4.2 — paste agent result into RESULT/BLOCKER/TEST_RESULT pulses
- v0.4.3 — session modes (30-minute, feature-based, bugfix, QA review)
Core rules:
- Keep handoff generation close to the feature decision surface.
- Include release/phase context, blockers, parking-lot warnings, and return format.
- Do not add live execution, telemetry, router logic, or agent streaming in this phase.
## v0.5 — Local/Cloud AI Assistant
Goal:
Start learning where local LLMs are good enough.
Potential features:
- Configure local endpoint manually
- Use local LLM for summaries
- Use local LLM for feature classification
- Track model usefulness
- Manual cloud fallback
## v1.0 — Agent Pulse Ingestion MVP
Goal:
Allow real agents/tools to submit Pulse events.
Potential features:
- Simple HTTP API for Pulse events
- Append-only pulse event store
- Real-time or refresh-based timeline
- Feature state updated from events
- Basic progress computation
- Safety/event validation
## v1.5 — Agent Observability
Goal:
Show real live-ish agent activity.
Potential features:
- Agent activity view
- Blocker/risk view
- Handoff events
- Evidence refs
- Test result parsing
- Git commit refs
## v2.0 — Agent Pulse Framework
Goal:
Become a real event-driven nervous system for autonomous agents.
Potential features:
- WebSocket stream
- Event subscriptions
- Agent coordination protocol
- Ownership claims
- Handoff handling
- Progress engine
- Constraints and approval gates
- Plugin system
## Long-Term Vision
BuildPulse becomes the human cockpit for:
- Feature planning
- Idea maturation
- Scope control
- AI agent work visibility
- Local/cloud AI routing
- Autonomous agent observability