Workspai.dev
The official learning path for Workspace Intelligence.
Workspai.dev is the public knowledge portal for Workspace Intelligence: the evidence-backed architecture layer that helps humans, CI, IDEs, and AI agents understand the same software system.
Workspai turns repositories, projects, dependencies, rules, changes, and evidence into shared understanding for developers, CI, IDEs, and AI agents.
This site teaches the architecture. It is not the cloud app, not a dashboard, and not a repository upload surface.
Learning path
1. Concepts
Understand why Workspace Intelligence is different from RAG, memory, repository indexing, and chat.
2. Software System Understanding
Learn the structure, relationships, intent, evolution, trust, and reasoning layers an AI needs.
3. Mental Models
Reason about shared system models, evidence-backed context, workflow boundaries, and agent authority.
4. Architecture
Study the input layer, Workspace Intelligence core, and consumers.
5. Workspace Model
See how projects, runtimes, commands, policies, contracts, and evidence become one model.
6. Workspace Graph
Separate code graphs from a graph of the software system: structure, runtime, ownership, change, and evidence.
7. Evidence
Learn how reports, contracts, gates, freshness, and verification keep claims trustworthy.
8. Agent Grounding
Understand how AGENTS.md, context packs, skills, IDE files, and MCP access align AI tools.
9. Create and Adopt
Learn how existing projects enter through adopt/import and which supported kits can start new projects.
10. Contract Catalog
Inspect every versioned contract, field, artifact, producer, and consumer boundary.
11. Command Catalog
Follow every CLI command to its canonical execution, artifacts, and governing contracts.
Publications
Essays
Category-shaping positions on repositories, AI engineering, and shared software-system truth.
Research
Evergreen requirements and evaluation models for evidence-backed software system understanding.
What this portal should help you answer
- What is Workspace Intelligence?
- What is the difference between a repository graph and a workspace graph?
- Which facts are verified, observed, inferred, stale, or unknown?
- How does a project enter the workspace: native, official, or existing?
- What context should an AI agent receive before it acts?
- Which commands create model, context, impact, verification, and release evidence?
- Which public claims are allowed by the shipped contracts?
Boundaries
Workspai.dev stays focused on public education: concepts, architecture, mental models, contracts, commands, guides, essays, research, RFCs, glossary, and release notes.
Interactive product experiences, hosted workspace operations, live repository analysis, account workflows, and commercial surfaces belong on workspai.com.
RapidKit Labs brand and ecosystem pages belong on getrapidkit.com.