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Documents as Context

In “Vibe Coding,” AI’s context is a black box — you don’t know what it assumed. In OpenLogos, every decision lives in a document. The same prompt with the same documents yields consistent results, regardless of which AI tool or team member runs it.

When you tell AI “build a login feature” without documents:

  • Requirements? Guessing.
  • UI design? Guessing.
  • API structure? Guessing.
  • Edge cases? Guessing.

Output varies wildly. Every session starts from zero. Decisions are lost.

When you provide structured documents (requirements → design → API spec → test cases), AI reads them all and produces consistent, traceable output.

Everything lives in a structured directory under logos/. Each phase’s output becomes the next phase’s input — all in human-readable formats:

logos/
├── logos.config.json # Project config
├── logos-project.yaml # AI collaboration index
├── resources/
│ ├── prd/
│ │ ├── 1-product-requirements/ # Phase 1 · WHY
│ │ ├── 2-product-design/ # Phase 2 · WHAT
│ │ │ ├── 1-feature-specs/
│ │ │ └── 2-page-design/
│ │ └── 3-technical-plan/ # Phase 3 · HOW
│ │ ├── 1-architecture/
│ │ └── 2-scenario-implementation/
│ ├── api/ # OpenAPI YAML specs
│ ├── database/ # SQL DDL / schema
│ ├── test/ # Test case specs (Markdown)
│ ├── scenario/ # API orchestration tests (JSON)
│ └── verify/ # Acceptance reports
├── changes/ # Delta change proposals
│ ├── <slug>/ # Active proposal
│ │ ├── proposal.md # Impact analysis + summary
│ │ ├── tasks.md # Phase-based task checklist
│ │ └── deltas/ # Changed artifacts per task
│ │ ├── prd/
│ │ ├── api/
│ │ ├── database/
│ │ └── scenario/
│ └── archive/ # Completed proposals
├── skills/ # AI Skills (SKILL.md per skill)
│ ├── prd-writer/
│ ├── product-designer/
│ ├── scenario-architect/
│ ├── api-designer/
│ ├── db-designer/
│ ├── test-writer/
│ ├── code-implementor/
│ ├── code-reviewer/
│ ├── change-writer/
│ ├── merge-executor/
│ └── ... # 13 built-in skills
└── spec/ # Methodology specifications

See Project Structure for the full specification.

PropertyDescription
ReviewableEvery piece of information AI uses is in Markdown, YAML, or JSON. You can read, audit, and correct any assumption before code is generated.
ReproducibleSame documents → same context → consistent AI output. Switch AI tools, switch team members — the result stays predictable.
CumulativeDocuments are project knowledge assets. Decisions never get lost. New team members read the docs and understand the full history — no tribal knowledge needed.

When AI opens your project, it reads AGENTS.md first. This file acts as a GPS:

FunctionDescription
Phase detectionScans logos/resources/ to find current phase
Next stepSuggests what to do next based on what’s missing
Active skillsLists which AI Skills to load for each task
Rules”Never write code without design docs” — enforced automatically

The AI doesn’t need you to explain the project every time. It reads the docs, detects the phase, loads the right Skill, and gets to work — with full context.

ArtifactFormatRationale
Requirements, designMarkdownHuman-readable, version-controllable, AI-friendly
API specsOpenAPI YAMLIndustry standard, tooling ecosystem
DB schemaSQL DDL or YAMLDirect database compatibility
Test resultsJSONLStreamable, language-agnostic
ConfigJSONMachine-parseable, schema-validatable

All formats are plain text — git diff shows exactly what changed.


See also: Interactive deep dive — Documents as Context