Software Intelligence Runtime for AI-native development.
View on GitHub ↗Homepage ↗Software Intelligence Runtime for AI-native development.
Keep models replaceable. Make software continuously converge toward its intended design — with evidence.
wcode turns Design State, Software Graph, Traceability, Risk, Verification, Evidence, and Reconciliation into the durable layer around AI-generated software. Code and Git remain first-class implementation artifacts, but the primary control plane becomes what the software should be, what it actually is, what changed, what is risky, and what evidence proves the result.
Models are execution providers, not the product core. Claude, ChatGPT, Grok, Mistral, coding agents, and future models connect through Remote MCP as replaceable builders/reviewers while wcode owns the local software-intelligence state and security boundary.
Design State · Software Graph · Verification Mesh · Evidence & Risk · Reconciliation.
Website & User Docs · Releases · Software Intelligence · 中文 · Agent Integrations · Product Scopes · Development
Live terminal dashboard — local health, public tunnel readiness, OAuth pairing, MCP activity, and workspace tasks in one view.
Browser setup — connect a model executor and inspect the active local runtime.
Project Observatory, local authorization, and detailed workspace intelligence.
AI coding is getting better at producing code. The harder problem is keeping a software system aligned with its intended design while models, humans, tests, dependencies, and runtime behavior keep changing. wcode is built for that control problem.
From the project README.
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