I am learning in public-facing increments while building systems that help a non-specialist start, understand and safely improve real projects with AI agents. The goal is not another impressive demo. It is a dependable working environment that explains itself, preserves evidence and gets better without taking control away from its user.

A lightweight, multi-agent engineering harness for Antigravity IDE, VS Code and compatible CLI agents - designed to turn verified experience into durable capability.

The core product remains private during pre-production. Its public project page, roadmap, community gateway and living Wiki are open for feedback.

1. Today - 01.00 Assisted Harness: routed instructions, Git-backed Kanban, isolated agent work, tests, security checks and human approval.
2. Next - deterministic collaboration: lower-cost agents should find and finish work without scanning the entire repository or colliding with one another.
3. Then - bounded autonomy: disposable execution, measurable success, multimodal verification and automatic recovery.
4. Long horizon - governed self-improvement: evidence, adversarial review, canaries and rollback before the system may improve itself.
5. Beyond AGI: a research direction, never a promise and never a label assigned by repository maturity alone.

This is a dated, privacy-safe snapshot of repository checkpoints. GitHub's native contribution calendar below remains the live source of truth; private activity can appear there as anonymized counts without revealing repositories or commit details.

1. Truth before marketing. Present capability and future direction stay visibly separate.
2. Human control. Agents can move quickly; material risk, promotion and release remain governed.
3. Evidence before confidence. A result needs tests, provenance and a safe way back.
4. Cost without quality theatre. Use the smallest reliable model and tool, while measuring rework instead of only token price.
5. Multimodal and beginner-guided. No invisible prerequisites and no "just configure it".
6. Continuous improvement with brakes. Lessons become rules, tests or skills only after challenge, pre-mortem and verification.

Yellow / architecture   Red / attack   Blue / defend   Green / automate   Orange / teach   White / govern   Purple / attack + defense

1. See the visual project and its real position on the autonomy roadmap.
2. Suggest an idea or ask a question in the public community.
3. Follow decisions, architecture and the development backlog in the Wiki.