Agentic AI
Agent Name Service
ANS Protocol from OWASP GenAI Security Project — foundational framework for secure AI agent discovery and interaction.
View on GitHub →Agentic AI architectures · Quantum cryptography · Brain-computer interfaces · Security research. Founder at Agentics.inc.
Organized by domain — from agentic orchestration to quantum algorithms to BCI tooling.
ANS Protocol from OWASP GenAI Security Project — foundational framework for secure AI agent discovery and interaction.
View on GitHub →End-to-end code-first tutorials covering every layer of production-grade GenAI agents — from spark to scale with reusable blueprints.
View on GitHub →Agent Name Service registry implementation based on IETF draft-narajala-ans-00 specification.
View on GitHub →Enterprise-grade AI development orchestration with advanced swarm intelligence and seamless Claude Code integration.
View on GitHub →Specification and documentation standard for agent skills — defining capabilities, interfaces, and composability patterns.
View on GitHub →Open-source application for building, observing, and collaborating with teams of AI agents in shared environments.
View on GitHub →Build production-ready agentic workflows with natural language — keeping operations persistent and reliable.
View on GitHub →Open-source framework to build and deploy intelligent agents with composable, extensible architecture.
View on GitHub →Flexible Python implementation of the Quantum Approximate Optimization Algorithm — designed for researchers to test new ansätze and classical optimizers.
View on GitHub →Toolkit for reproducible study, application, and verification of QAOA — standardizing benchmarks across implementations.
View on GitHub →Exploratory research at the intersection of quantum computing and artificial general intelligence architectures.
View on GitHub →Notebooks demonstrating quantum computing applications with Amazon Braket — circuits, algorithms, and hybrid classical-quantum workflows.
View on GitHub →Course material with Jupyter notebooks covering linear algebra and mathematical prerequisites for quantum computing.
View on GitHub →Quantum-resistant DAG-based anonymous communication system — TDD implementation of the QuDAG protocol with Claude Code.
View on GitHub →Pure Python, zero-dependency, from-scratch Bitcoin implementation for educational cryptographic study.
View on GitHub →Tooling for the Muse EEG headband — signal processing, artifact removal, and brainwave feature extraction for BCI applications.
View on GitHub →Multimodal model for brain response prediction — training and evaluation code for neural decoding at scale.
View on GitHub →Sync thinking with AI reasoning models for deeper cognitive alignment — follow, learn, and iterate within one turn.
View on GitHub →AI patient advocacy tool for cancer treatment — understand labs, find clinical trials, track treatment. Open source, used in active treatment.
View on GitHub →Purpose-trained guardrails that make AI agents secure and compliant — policy enforcement at the agent boundary.
View on GitHub →Security-domain language model — fine-tuned BERT variant for threat classification, vulnerability analysis, and cyber NLP tasks.
View on GitHub →Sample application showcasing Tasks and Entities APIs for automated security reconnaissance workflows.
View on GitHub →OpenAI Frontier Evaluations — assessment frameworks for model capability and safety at the capability frontier.
View on GitHub →Implement a ChatGPT-like LLM in PyTorch from scratch — step by step, layer by layer, with full conceptual commentary.
View on GitHub →The simplest, fastest repository for training and fine-tuning medium-sized GPTs — minimal dependencies, maximum clarity.
View on GitHub →Minimal codebase for training large language models — stripped to essentials for research and experimentation at scale.
View on GitHub →Domain Adapted Language Modeling Toolkit — end-to-end RAG pipeline with retrieval augmentation and domain fine-tuning.
View on GitHub →RAG on everything with 97% storage savings — fast, accurate, 100% private RAG on personal devices with LEANN indexing.
View on GitHub →Train the smallest language model that fits in 16MB — competitive efficiency benchmark pushing model compression limits.
View on GitHub →Benchmark evaluating AI models at the absolute frontier of human knowledge across expert-level questions.
View on GitHub →Tensors for High-dimensional Object Representations — research into geometric deep learning and tensor decomposition methods.
View on GitHub →Intelligent integration between Claude Code and Google Gemini for large-scale code analysis across massive codebases.
View on GitHub →Convert AI Skills (Claude Skills format) to MCP server resources — part of the BioContextAI ecosystem.
View on GitHub →Analyze your website's AI-readiness, powered by Firecrawl — structured scoring across discoverability, schema, and agent accessibility.
View on GitHub →Fair-code workflow automation platform with native AI capabilities — 400+ integrations, visual building with custom code, self-hostable.
View on GitHub →Automate research publication discovery and analysis — find papers similar to a URL, surface dataset results, re-imagine literature review.
View on GitHub →Skills repository for Pika — composable AI capabilities designed for rapid deployment in agentic pipelines.
View on GitHub →40+ articles on agentic AI, security architectures, quantum systems, and emerging technology. Published on LinkedIn.
Building the infrastructure layer for autonomous AI — where agents are first-class citizens.
Founder
Agentics.inc focuses on the architecture, security, and deployment of autonomous AI agent ecosystems. Work spans multi-agent orchestration protocols, agent identity and trust frameworks, and production-grade agentic infrastructure.
Autonomous multi-agent architectures, swarm intelligence, orchestration patterns, and production deployment.
QAOA, quantum cryptography, post-quantum security, and hybrid classical-quantum algorithm design.
EEG-based biometric systems, neuromorphic hardware integration, bidirectional neural interfaces.
Adversarial defense, ITAR/NIST compliance, agent identity frameworks, and threat modeling for LLM systems.
I work at the intersection of autonomous AI systems, quantum computation, and advanced human-machine interfaces. My research spans the full stack — from hardware-level neuromorphic devices to protocol-level agent communication standards.
At Agentics.inc, the focus is on making agentic AI deployable, secure, and trustworthy at enterprise scale. This means working on agent identity (ANS/MCP protocols), adversarial robustness, and compliance with ITAR and NIST 800-171r3 frameworks.
On the quantum side, my interest is in near-term advantage — QAOA for combinatorial optimization, quantum-resistant cryptographic protocols, and the convergence of quantum and classical AI.
BCI work centers on the Trinity Puck and MW75 Neuro — EEG-enabled biometric verification devices that use neural signals as authentication primitives, opening up entirely new paradigms for identity and access management.