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AJ AI Brain
Then I taught it what good work looks like.
A general AI model knows a great deal about everything and nothing about how your project names a duct. So the agent reads a proven knowledge package before it acts — task skills, techniques and working code captured from real projects — and then carries out real modelling work on the live, open Revit model through a Node.js MCP bridge.
What it is made of
9task workflows, from air terminal layout to NFPA 13 sprinkler spacing checks
267reusable Revit API C# fragments, compile-checked against the real API
23knowledge documents the agent reads before it acts
- Team-wide, not personal. Packaged with an installer, version-controlled in Git, documented. The time saving is shared.
- Quality built in. Automated checks compile-verify the C# against the real Revit API and flag documentation drift on every edit.
- Built the way it runs. AJ-Tools itself is written with AI coding tools — Claude Code, Codex and Antigravity — against the same compile-checked codebase the agent draws from.
- Honest tooling. A tool that has never been run against a real model says so.
The model is still the job. The tools just stop it eating the day.
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