Logic Production System (LPS) programming language interpreter implemented in JavaScript for Node.js and browsers.

MIRROR of https://codeberg.org/catseye/Samovar : Model worlds using propositions and run simulations in them

Documentation for the TriplyDB and TriplyETL products

Logic Production System (LPS) CLI Toolset using lps.js

Official companion repository for Designing Scalable, Reliable Data and AI Systems for Production — architectures, code, templates, and production frameworks.

Curated collection of production-grade engineering system designs, backend patterns, DevOps architectures, data pipelines, and scalable infrastructure examples inspired by real-world systems like Netflix, Google, and Uber.

A curated collection of papers describing real-world production systems from top systems conferences (2020+).

This repository documents realities that surface only after scale,authority,and commitment eliminate reversibility—where decisions ossify into structure, costs compound beyond instrumentation, failures persist without incident,accountability diffuses,and systems continue operating long after meaningful correction has become structurally impossible.

A public repository of technical case studies examining the operational challenges faced by technology platforms in Africa as they scale, handle outages, and maintain reliable systems.

Tool for prototyping production systems structures

An atlas of AI-native production systems and domain operating layers

A complete end-to-end System Design learning path covering fundamentals, distributed systems, scalability, real-world case studies, architecture patterns, and production-ready system thinking.

Notes on Production Systems lectures

A structured DevOps path from Linux fundamentals to production clusters — every phase ships a real pipeline or running system, not just notes on theory.

Public architecture and production-line design of Tradu, a distributed AI document processing platform.

NOEME — screenplay pilot

Cloud-native, scalable & enterprise-grade schema-driven Master Data Management engine built with FastAPI, Prisma (Python), & PostgreSQL, paired with a Next.js TypeScript admin UI. Delivers dynamic, metadata-aware, allow-listed CRUD, pg_catalog introspection, data validation, paginated search, stateless REST APIs, & production-ready cloud governance

Systemic Assessment of Node Failures in HPC Production Platforms

Cloud-native, scalable & enterprise-grade schema-driven Master Data Management engine built with FastAPI, Prisma (Python), & PostgreSQL, paired with a Next.js TypeScript admin UI. Delivers dynamic, metadata-aware, allow-listed CRUD, pg_catalog introspection, data validation, paginated search, stateless REST APIs, & production-ready cloud governance

End-to-end ownership of production AI systems: architecture, risk management, execution, and scaling under real constraints.