3. Data, Science & AI

Submit Python functions for GPU workloads and AI training jobs on Modal with job tracking via the ModalJob decorator.

Creates CLAUDE.md and thoughts/ directory structure to initialize AI engineering workflows in repositories.

Extracts and validates structured data from LLM responses using Pydantic models for type-safe generation and reliable output.

Optimizes data ingestion into DuckDB via C++ bindings for high-performance analytics workloads.

Unified access to 100+ AI models via OpenRouter, enabling cost management, provider routing, and fallback strategies for multi-model LLM applications.

Provides a unified API to interact with 100+ LLM providers, enabling cost optimization, multi-provider fallbacks, and gateway deployment.

Command-line interface for initiating AI coding agents with initial prompts, supporting developer workflows for agent-based coding tasks.

Builds RAG applications and knowledge bases using LlamaIndex for efficient document search and LLM integration.

Deploys LLMs using Hugging Face Text Generation Inference with quantization and tensor parallelism for high-throughput production serving.

Builds enterprise AI applications with Microsoft Semantic Kernel, enabling plugin creation, memory systems, and LLM orchestration for .NET/Python development.

Guide for connecting local AI models (Ollama, Llama.cpp) to QuanuX C++ engine for embedded AI deployment.

Provides natural language interface for executing SQL queries, managing schemas, and performing CRUD operations on SQL Server databases.

Resolves disagreements between AI model outputs (Cursor and Gemini) through weighted expertise prioritization and harmonization.

Sets up autonomous coding agent projects with Archon MCP for state management, including scaffolding for prompts, feature tracking, and security configuration.

Guides development and operation of the QuanuX Statistics & Research Node for statistical analysis and data-driven research workflows.

Expert guidance for Microsoft Fabric Real-Time Intelligence (RTI) including KQL query execution, eventstream management, and trigger configuration for real-time analytics.

Designs web scrapers for real estate listings and government data, ensuring anti-bot evasion and data accuracy.

Enables creation of autonomous multi-agent systems with roles, tools, and collaborative workflows for complex task automation and research.

Manages machine learning lifecycle with experiment tracking, model packaging, registry management, and deployment for AI operations.

Enables persistent AI agents to complete tasks through continuous iteration loops with Archon state management and AI framework integrations.

Assists in designing, optimizing, and managing PostgreSQL databases with features including indexing, JSON operations, full-text search, and pgvector for AI embeddings.

Provides best practices for RAG pipelines including chunking, embedding, retrieval, reranking, and generation for document QA and semantic search.

Builds interactive data science and ML dashboards using Streamlit's Python-native framework with layouts, charts, and deployment capabilities.

Builds enterprise AI applications using Azure AI services for document processing, intelligent search, and cognitive capabilities.