Agent Architect | Quantitative Modeler | AI Systems Engineer
Designing intelligent systems that bridge AI, automation, and structured reasoning
| Public repos | Packages on PyPI | Agents in Haive | *dantic libraries |
OOAI services |
Haive is a namespaced polyrepo with a central controller โ 9 coordinated repos publishing under a unified haive.* namespace, with 53+ production-ready agents (Simple, React, Multi, Memory, RAG variants, and more). The *dantic family pushes Pydantic from data validation into symbolic mathematics, structural typing, meta-programming, CLI/shell frameworks, and more.
AI agents are more than just prompts and responsesโthey require structured reasoning, modular execution, and real-time adaptability. My focus is on designing scalable, interpretable, and modular AI architectures that can dynamically retrieve, process, and act on information.
๐น Multi-Agent Architectures โ Building intelligent, cooperative agents with dynamic workflows
๐น Graph-Based AI โ Leveraging structured data to improve reasoning and context understanding
๐น RAG Pipelines & Knowledge Retrieval โ Optimizing AI workflows for efficiency and accuracy
๐น Autonomous Decision Systems โ Integrating real-time adaptation and policy-based execution
AI isn't just about languageโit's about pattern recognition, probabilistic modeling, and structured intelligence. My work integrates quantitative finance, computational models, and AI-driven decision systems to optimize real-world applications.
๐ Stochastic & Algorithmic Models โ Applying ML to financial markets, simulations, and predictive modeling
๐ Time Series Forecasting โ Building statistical & deep learning models for market predictions
โก Risk & Portfolio Optimization โ Designing AI-driven investment strategies
๐ข Probabilistic Graph Models โ Structuring uncertainty for AI decision-making
๐ค Agentic Systems, Orchestration & Evaluation
Agent/runtime design ยท graph composition ยท multi-agent orchestration ยท RAG ยท knowledge graphs ยท persistent memory ยท A2A ยท HITL ยท tracing ยท evaluation ยท self-improving systems
Frameworks & Runtimes
Evaluation, Tracing & Observability
LLM Providers
๐ Quantitative Finance & Equity Research
Equity research ยท stochastic & algorithmic modeling ยท time-series forecasting ยท risk & portfolio optimization ยท probabilistic graph models ยท statistical evaluation
Numerical & Statistical Stack
๐ง AI/ML Foundations
Frameworks & Libraries
Vector Search & Knowledge
โก Languages & Backend
Languages
API & Data Layer
๐งฌ The Pydantic Ecosystem โ *dantic family
A family of frameworks built on Pydantic โ pushing it from "data validation" into mathematical computing, symbolic logic, structural type analysis, meta-programming, CLI, shells, files, and more.
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Symbolic mathematics framework built on Pydantic โ 21-version evolution. |
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Mathematical computing framework built on Pydantic. |
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Structural type analysis framework for Pydantic โ with algebraic properties. |
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Meta-programming framework for Pydantic โ 40-phase evolution (P1โP40). |
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Shell CLI framework built on Pydantic โ evolution from clidantic. |
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Typed Command-Line Interfaces powered by Click and Pydantic. |
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Functional programming primitives on top of Pydantic. |
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Flexible structural typing and runtime validation for Python โ duck-typing for Pydantic models. |
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Agent workspace normalizer for .awsp projects โ file classification, templates, validation. |
๐๏ธ Systems, Infrastructure & Observability
Datastores & Messaging
Workflows & Runtime
Observability
๐ง Developer Tooling & CI/CD
Version Control & CI
Linting, Typing & Testing
Packaging & Build
Documentation
Multi-agent architectures with dynamic workflows and structured reasoning |
ML-driven financial modeling and algorithmic trading strategies |
Knowledge graphs and RAG pipeline optimization |
Real-time decision systems with uncertainty modeling |
An ecosystem of agent runtimes, prompt/skill services, and applied tools โ designed to be composable, observable, and safe.
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Haive AI Agent Framework โ production-ready namespaced polyrepo with a central controller: 9 coordinated repos publishing under a unified haive.* namespace, with 53+ agents, RAG, memory, knowledge graphs, and games.
The umbrella runtime: scalable multi-agent intelligence with dynamic workflows, structured reasoning, configurable graph composition, and persistent memory. Everything below plugs into it.
Central controller |
The central coordination repo โ orchestrates the haive.* namespace, glues the 9 sibling packages into a unified runtime, and houses the 53+ agent catalog, RAG, memory, and knowledge graph infrastructure. |
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Foundation for the Haive AI agent framework โ engines, graph builder, state schemas, persistence, and stores. |
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Production-ready agent implementations: SimpleAgent, ReactAgent, MultiAgent, MemoryAgent, RAG variants, and more. |
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Dynamic MCP integration for AI agents โ search 1,960+ servers, install with HITL approval. |
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Haive Agent Protocol โ MCP for Agents. Orchestrate multiple AI agents in complex workflows. |
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Tool implementations for Haive agents โ search, calculators, APIs, and integrations. |
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Data processing pipelines and ETL workflows for Haive agents. |
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LLM-powered game agents for chess, Go, poker, social deduction, and 20+ other games. |
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Prebuilt Haive recipes and starter configurations. |
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Universal Python documentation generator โ 40+ Sphinx extensions pre-configured. Zero-config beautiful docs. |
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Service-first database intelligence platform Safe inspection, guarded SQL, retrieval, and agent-ready context. DB-RAG with long-term memory, schema-aware exploration, query planning with guardrails and HITL, iterative self-improvement. |
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Agentic web infrastructure (PyPI: fetchkit)Autonomous fetching, scraping, extraction, and download with realistic browser fingerprints, structured outputs, and a full crawl-scrape-download pipeline backed by Postgres and MinIO. Ships an MCP server so agents can call it as a tool. |
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Modular Symbolic Logic for Agent Reasoning SAT solving and LLM-enhanced proof systems. Propositional/predicate logic ASTs, sequent-calculus proof validation, truth-table/SAT validity, machine-checkable traces and counterexamples. |
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Browser automation toolkit 45-version evolution for web agent development. |
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OOAI core runtime โ the foundation for the OOAI agent platform. |
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Prompt registry and runtime delivery scaffold for LangChain and LangGraph. Versioning, storing, serving templates/chains/few-shot sets with caching and safe retrieval. |
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Multi-agent skills registry โ ingests curated "awesome skills" repos, normalizes SKILL.md, enables safe distribution and execution across runtimes with MinIO-backed storage. |
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Graph-based computation and workflow management. |
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OOAI agent implementations. |
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OOAI API layer. |
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Adversarial prompt corpus & defenses Showcases methods of prompt injection and counter-defenses. 200+ adversarial cases integrated into agent workflows for guardrails and few-shot selection. |
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Python project scaffolder for humans and agents 105 groups, 22 recipes, MCP server, group-aware templates. Generates reproducible, agent-operable AI/Python projects and multi-service platforms. |
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Handwriting/PDF โ LaTeX Converts handwritten notes, PDFs, and images into structured LaTeX. OpenCV preprocessing + OCR plus LLM-based generation with self-correction and long-context support. Used by Math/CS students. |
The equity-expert anchor: a coordinated set of libraries for quant research, technical analysis, valuation, and forecasting.
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The ultimate quant finance toolkit for Python The flagship of the AWT quant stack โ a comprehensive library for equity research, modeling, and analytics. |
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Advanced Quantitative Forecasting SPDE, GARCH, and LLMs for financial time-series. Stochastic PDE solvers, volatility modeling, and language-model-augmented forecasting in one package. |
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Technical Analysis Indicators A comprehensive library for technical analysis indicators in financial markets โ trend, momentum, volatility, and volume indicators. |
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Discounted Cash Flow valuation Equity valuation models built on the AWT toolkit. The valuation half of the equity-research stack. |
๐ Configuration Notes
Metrics Configuration:
- Auto-updates every 12 hours via
.github/workflows/metrics.yml - Includes: lines of code, languages, activity, habits, achievements
- Theme: Consistent purple (#A855F7) across all elements
Visual Assets Organization:
images/banners/- Header and section bannersimages/badges/- Custom badges and shieldsimages/stats/- Statistical visualizationsimages/dividers/- Section separators and decorative elements
Color Palette:
- Primary:
#A855F7(Purple) - Secondary:
#8B5CF6(Lighter Purple) - Accent:
#A7F3D0(Mint Green) - Background:
#0D1117(Dark) - Text:
#E9D5FF(Light Purple)