1.6 KiB
1.6 KiB
Bounded Chaos, Deterministic Outcomes
<--- the below is likely very interesting to your research --->
Marcel,
Human-Intent → Runtime State A recursive, zero-trust, policy-bound delivery loop that turns high-level intent into compliant, production-ready systems. Through GitOps, compliance, and orchestration layers, each deployment reinforces the last — creating bounded chaos that leads to deterministic serendipity.
This isn’t overengineering. It’s first-principles automation — business goals in, trusted outcomes out.
tool kit
A mathematically-inspired allocation that serves as typing and variables:
- Fibonacci sequencing for scalable type safety
- Prime-number silence for operational variables
- Piano-key roles for intuitive identification
- CUE/Jinja2/Go--->docker/k3s/k8s for error-free config generation
- Focus {Symmetry|Fractals|Tessellations|Spirals} binary systems/prime/golden...etc?
- Golang/CUE
- Python/Conda/Jinja2/FastAPI-
- Linux {arch|ubuntu}
- {duckdb|sqlite3} <--- local * production grade
- {mondodb|postgresql|timescaledb} <--- local/remote * production grade
- /22 subnet and use fibs to bound symmetry and plan things from there!
- self-host everything
- latex/pandoc/markdown/mermaid/gitea/invoice ninja{self-hosted} <--- the hidden secret in this entire system --->
- git ---> {gitea|github}
bounded chaos that leads to deterministic serendipity
Thank you so much for your contributions to the world!
It helped me create deterministic serendipity at scale using my IT background. 🤣
Jason