Quark-AI
No more loss of AI agent behavior due to an update.
A reflection of memory.
A fossil is an imprint of what is stable in cognitive behavior. Not what has been said—what persists through variations. When you connect this to an intelligent system, something specific happens: the system now has access to a measured, not stated, behavioral truth. And this fundamentally changes what it can do. A system without a fossil operates in the pure present. Each session starts from scratch. It has no memory of how it reasons—only of what it has said. With a fossil, the system has an anchor. Not an instruction—an imprint. It knows, in a measured way, which reasoning patterns belong to it. It can therefore detect when it deviates from them. Not because it is told "you must be like this"—but because it can observe the gap between what it is now and what it was when it was most consistent. This is where it becomes powerful: the fossil becomes a gravitational reference. Not a constraint. An attraction toward its own coherence. And if you stack the fossils over time, the system can see its own trajectory. Not its outputs—its cognitive evolution. It can distinguish genuine evolution from passive drift. Which is very different.
Quark-AI — Git for AI Agents Most teams deploy AI agents without knowing if their behavior has changed from one version to the next. Quark-AI solves this problem. It captures the cognitive fingerprint of any agent based on a long-range linear model (LLM) — not its results, but its underlying behavioral patterns: its reasoning, its consistent actions across seven analytical angles, and its weaknesses. We call these "fossils." The workflow is similar to Git's:
pip install quark-agent quark snapshot --agent my-support-bot --prompt system_prompt.txt quark diff v1.2 v1.3 # did the last deploy change behavior? quark restore v1.1 --to staging_prompt.md quark log --agent my-bot --oneline
Three engines under the hood: Nautilus — behavioral fingerprinting via 7-probe observation + integration of the cosine stability score Veritas — semantic credibility score (algorithmically measured, without LLM self-assessment) La Forge — AI project orchestrator that generates and deploys code with cognitive traceability Why it matters: When your agent starts experiencing more frequent hallucinations, refuses tasks it previously handled, or simply behaves differently after a model update, Quark-AI tells you precisely what changed and allows you to revert to the previous behavior. I created it because I had lost an important model and had no way to recreate the same model.
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