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PERSONAL_MODEL

Introduction

Renderflow's personal model describes the assumptions it makes about the people who use, maintain, embed, and supervise it.

Conformance

This document is authored in conformance with:

  • .github/specs/architecture/document.spec.md
  • .github/specs/architecture/domain/personal-model.spec.md

Purpose & Scope

This document defines the human model underlying Renderflow's design and architecture.

It covers agency, needs, constraints, and trust expectations. It does not define interfaces, implementation, or clinical claims about people.

Definitions

  • Operator: a person running or supervising a Renderflow workflow.
  • Author: a person providing the source artifact and desired outputs.
  • Maintainer: a person evolving Renderflow itself.
  • Integrator: a person embedding or extending Renderflow through plugins or automation.
  • Agency: the ability to understand, choose, and override system behavior.

Renderflow Personal Model

Renderflow assumes that people are intentional operators, not passive recipients of automation.

Human assumptions

  • People want to describe outcomes once and avoid rebuilding shell pipelines repeatedly.
  • People benefit from seeing what the system plans to do before expensive work begins.
  • People need predictable behavior because outputs often matter for publication, delivery, or archival use.
  • People operate in imperfect environments where dependencies, providers, and external tools may fail.
  • People need reversible and inspectable automation, especially when AI is involved.
  • People have different roles—author, maintainer, integrator—but they share a need for clear contracts.

Human needs Renderflow should preserve

  • Clarity: the system should explain configuration, planning, and failure states.
  • Control: operators should be able to choose targets, inspect plans, and govern optional AI behavior.
  • Trust: repeated runs should feel dependable.
  • Portability: workflows should survive machine changes and team growth.
  • Leverage: the tool should reduce repeated operational work without hiding meaningful choices.

Requirements, Constraints & Guidelines

Requirements

  • Human agency must remain explicit.
  • The personal model must support both manual and AI-assisted workflows.
  • Trust and inspectability must shape downstream design decisions.

Constraints

  • People must not be modeled as infinitely attentive or infallible.
  • Automation must not assume that hidden behavior is acceptable.
  • This document must not become a UI specification.

Guidelines

  • Prefer assumptions that support transparency.
  • Prefer operator empowerment over system cleverness.
  • Prefer models that hold across CLI, docs, plugins, and AI supervision.

Authoring Contract

Purpose

Own Renderflow's human assumptions.

Responsibilities

This document owns:

  • assumptions about users and maintainers,
  • agency and autonomy expectations,
  • the needs downstream design should preserve.

Non-Responsibilities

This document does not own:

  • interaction patterns,
  • system decomposition,
  • implementation detail,
  • medical or psychological claims.

Inputs

  • PURPOSE.md
  • PRINCIPLES.md
  • ONTOLOGY.md
  • observed repository support for dry runs, diagnostics, watch mode, caching, plugins, and AI governance

Outputs

  • DESIGN.md
  • DESIGN_SYSTEM.md
  • AI_CONSTITUTION.md

AI Generation Rules

AI systems should describe the people Renderflow serves with respect and without prescriptive overreach.

Validation

Downstream experience design should be able to cite this model when deciding how visible, reversible, or guided a workflow should be.

Acceptance Criteria

  • Human assumptions are explicit.
  • Agency and trust needs are documented.
  • The personal model aligns with Renderflow's purpose and principles.
  • The document stays independent of implementation detail.

AI Authoring Strategy

AI systems should:

  1. infer the human needs implied by Renderflow's architecture,
  2. describe operators, authors, maintainers, and integrators,
  3. make trust and agency explicit,
  4. avoid turning the model into interface design.

Rationale & Context

Renderflow includes dry runs, plan visualization, diagnostics, and optional AI behavior because it assumes people need to stay in control of automated transformation. This document makes that assumption explicit so future design choices preserve it.

Dependencies & External Integrations

Upstream Dependencies

  • PURPOSE.md
  • PRINCIPLES.md
  • ONTOLOGY.md

Downstream Dependencies

  • DESIGN.md
  • DESIGN_SYSTEM.md
  • AI_CONSTITUTION.md

Examples & Edge Cases

Example

A contributor deciding whether to expose graph diagnostics is guided by this model: users are assumed to value inspectability and informed control.

Edge Case

In watch mode, resilient behavior may keep work moving after a transform failure, but the personal model still requires that the operator be able to understand what happened.

Validation Criteria

This document is valid when design and governance decisions can explain how they preserve user agency and trust.

  • .github/specs/architecture/document.spec.md
  • .github/specs/architecture/domain/personal-model.spec.md