This GitHub repository contains the complete code for building Business-Ready Generative AI Systems (GenAISys) from scratch. It guides you through architecting and implementing advanced AI controllers, intelligent agents, and dynamic RAG frameworks. The projects demonstrate practical applications across various domains.

Claude Code best practices -- applied to application design. Interactive HLD/LLD visualization, implementation example. LLM-agnostic, DB-governed, GDPR-ready.

Neuromodulatory Control Networks (NCNs), a novel LLM architectural modification inspired by the neuromodulatory systems in the vertebrate brain.

Step by step code samples showing how AI agent architectures evolve from simple to production ready using AWS services including Amazon Bedrock AgentCore Runtime.

“Semantic Latent Engineering (SLE) is a high-level framework for reasoning about meaning, intent and agents on top of LLMs. It combines math, cognitive architecture and practical patterns (SD, HDSA, ABC, CPP, MMOR) to move from prompt tricks to auditable, testable semantic engineering.

Understand and build embedding models, focusing on word and sentence embeddings, dual encoder architectures. Learn to train embedding models using contrastive loss, implement them in semantic search and RAG systems.

ASAN: A conceptual architecture for a self-creating (autopoietic), energy-efficient, and governable multi-agent AI system.

PromptWeaver: RAG Edition helps design effective prompts for Traditional, Hybrid, and Agentic RAG systems. It offers templates, system prompts, and best practices to improve accuracy, context use, and LLM reasoning.

Architecture for coherence wherever AI moves faster than humans can synchronize.

AI-powered multi-agent system for automated proposal generation using context-aware retrieval and persona-based writing.

Conformal Geometric Algebra (CGA) with efficient sequence modeling by introducing a recurrent rotor mechanism and a novel bit-masked hardware kernel that solves the computational bottleneck of Clifford products.

Conceptual proposal for a distributed AI personality system where each device hosts a unique avatar and shares semantic memory. Inspired by the vision of a collaborative, growing AI companion.

Enterprise Salesforce + AI architecture templates with ADRs, Mermaid blueprints, governance checklists, and validation workflows for architects.

ABES: Adaptive Belief Ecology System. A headless cognitive memory engine for autonomous AI. Beliefs act as living organisms that decay, conflict, and mutate over time, managed by a 15 phase scheduler and an optional RL tuning layer.

Offline-first cognitive operating system for synthetic intelligence. Features belief ecology, RL-based goal evolution with differential privacy, contradiction tracing, HMAC-signed audit logs, sandboxed execution, and local LLM inference. Designed for air-gapped, adversarial environments.

Architecture decision records, system design case studies, and delivery templates demonstrating pragmatic SaaS architecture, cloud trade-offs, and consulting-grade technical leadership.

Гибридная модель ИИ для автошахмат, сочетающая формальные эвристики и адаптивное поведение.

Deterministic context budgeting for LLM prompts, demonstrating stable prompt packing within fixed token limits.

Production-ready enterprise AI framework with three-layer architecture: UX Automation → Data Intelligence → Strategic Intelligence

Seven architectures, of one.