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ROADMAP

Introduction

Renderflow's roadmap describes the strategic evolution required to fulfill its vision.

Conformance

This document is authored in conformance with:

  • .github/specs/architecture/document.spec.md
  • .github/specs/architecture/foundation/roadmap.spec.md

Purpose & Scope

This document defines the long-term capability path for Renderflow.

It covers strategic phases, architectural evolution, and capability growth. It does not cover GitHub issues, sprint plans, or release schedules.

Definitions

  • Phase: a logical stage of long-term maturity.
  • Initiative: a major body of work that advances the architecture or capability surface.
  • Capability growth: strategic expansion of what Renderflow can express, plan, or execute.

Renderflow Roadmap

Phase 1: Canonicalize the contract

Renderflow strengthens its role as a specification-first transformation system.

Key outcomes:

  • architecture and terminology remain canonical and discoverable,
  • CLI, docs, examples, and validation stay aligned,
  • execution plans and diagnostics remain first-class explanation surfaces.

Phase 2: Deepen universal transformation planning

Renderflow matures from a powerful renderer into a more general transformation planner.

Key outcomes:

  • richer graph reasoning across more artifact classes,
  • stronger optimization guidance around cost, quality, and reuse,
  • clearer plan export and explanation for humans and automation.

Phase 3: Expand bounded extensibility

Renderflow broadens what can participate in the system without weakening the core model.

Key outcomes:

  • plugin participation becomes easier to adopt without hiding capability boundaries,
  • AI-assisted transforms gain stronger governance, provenance, and operational transparency,
  • extension contracts stay explicit enough for library embedding and advanced workflows.

Phase 4: Increase trust and reproducibility at scale

Renderflow becomes more dependable as workflow complexity grows.

Key outcomes:

  • stronger provenance around outputs and reused work,
  • more explicit policy surfaces for AI, plugins, and external tools,
  • clearer confidence signals across local development, CI, and release automation.

Phase 5: Broaden ecosystem portability

Renderflow continues to travel well across environments and adopters.

Key outcomes:

  • distribution and embedding pathways remain coherent,
  • the architecture supports long-lived contributor and AI onboarding,
  • the project can evolve without coupling its identity to one interface or platform.

Requirements, Constraints & Guidelines

Requirements

  • Roadmap phases must align with Renderflow's vision.
  • Strategic capability growth must remain more important than implementation detail.
  • Architectural evolution must be visible across phases.

Constraints

  • No issue lists, sprint plans, or deadlines.
  • No technology-specific roadmap organization.
  • Short-term implementation tasks must not substitute for strategic direction.

Guidelines

  • Organize by capability maturity.
  • Prefer phases over dates.
  • Preserve flexibility inside each phase.

Authoring Contract

Purpose

Own the strategic path of Renderflow's long-term evolution.

Responsibilities

This document owns:

  • strategic phases,
  • major capability growth,
  • architectural maturation direction.

Non-Responsibilities

This document does not own:

  • implementation backlogs,
  • release planning,
  • engineering workflow,
  • system decomposition.

Inputs

  • PURPOSE.md
  • VISION.md
  • PRINCIPLES.md
  • FOUNDATIONS.md
  • SYSTEM.md
  • ARCHITECTURE.md

Outputs

  • milestone planning
  • implementation prioritization
  • documentation evolution

AI Generation Rules

AI systems should organize the roadmap around capability phases and architectural outcomes, not feature tickets.

Validation

The roadmap should communicate direction without turning into a project plan.

Acceptance Criteria

  • Strategic initiatives are visible.
  • Phases are logically ordered.
  • Architectural evolution is explicit.
  • Implementation tasks and deadlines are absent.

AI Authoring Strategy

AI systems should:

  1. read upstream architecture,
  2. identify major required capabilities,
  3. group them into phases,
  4. keep the result flexible and implementation-independent.

Rationale & Context

Renderflow already demonstrates strong foundational capabilities: declarative configuration, graph planning, DAG execution, plugins, AI integration, caching, and packaged delivery. The roadmap explains how those capabilities should mature into a more universal, trustworthy, and portable transformation platform.

Dependencies & External Integrations

Upstream Dependencies

  • PURPOSE.md
  • VISION.md
  • PRINCIPLES.md
  • FOUNDATIONS.md
  • SYSTEM.md
  • ARCHITECTURE.md

Downstream Dependencies

  • implementation priorities
  • documentation strategy
  • packaging and release direction
  • contributor onboarding

Examples & Edge Cases

Example

Improving plan explainability belongs to Phase 1 or Phase 2 because it strengthens the contract and planning layers rather than representing a one-off feature.

Edge Case

A high-value near-term integration might ship before a phase is fully realized, but the roadmap remains correct if the integration still advances the capability outcomes of its phase.

Validation Criteria

This document is valid when contributors can explain where Renderflow is heading without referencing dates, issues, or sprint milestones.

  • .github/specs/architecture/document.spec.md
  • .github/specs/architecture/foundation/roadmap.spec.md