3. Data, Science & AI

Enables semantic search over workspace files using Telnyx Storage and AI embeddings for natural language retrieval of indexed knowledge.

Automates PyTorch environment setup with hardware detection (GPU/CPU) for isolated ML project development.

AI system observing sessions to create and score atomic instincts, evolving them into adaptive skills and agents.

Designs and optimizes database architectures for scalability, including schema, indexing, and query performance across PostgreSQL, MySQL, MongoDB, and Redis.

Facilitates data synchronization and retrieval from data lakes, including S3 storage and Polymarket data sources.

Extracts OpenGraph and Twitter Cards metadata for link previews, SEO tools, and web scraping.

Analyzes and refines prompts to improve output quality and effectiveness for large language models.

Provides optimized prompt templates and techniques following Anthropic's guidelines to enhance Claude AI interaction effectiveness.

Offers 18+ ready-to-use prompt templates and executable agents for efficient LLM application development.

Designs AI agents using proven architectural patterns and best practices for effective implementation.

Captures and transfers contextual information during AI agent delegation to maintain task continuity and workflow integrity.

Configures, optimizes, and audits web analytics tracking systems including Google Analytics 4 and tag management solutions.

Expertise in implementing Deep Knowledge Tracing (DKT) and Bayesian Knowledge Tracing (BKT) models for educational data analysis and learning progression modeling.

Architects RAG systems using LLMs, Qdrant vector database, and LangChain for efficient information retrieval and generation.

Specializes in designing and optimizing knowledge graphs using Neo4j 5.x and Cypher for complex data relationship management.

Applies cognitive science algorithms (BKT, DKT, FSRS) to develop adaptive learning systems for personalized education technology.

Architects systems for ingesting, aligning, and ensuring coherence across diverse content modalities including text, image, and video.

Configures OpenAI as the embedding provider for GrepAI, enabling high-quality cloud-based text embeddings for AI applications.

Configures optimal code chunking strategies for embedding in GrepAI, enhancing RAG system performance.

Adapts AI behavior to task types using predefined modes including brainstorming, implementing, and debugging.

Provides computational tools for signal integrity and EMI analysis to debug hardware designs.

Automates Field-Oriented Control parameter tuning for motor systems using computational optimization techniques.

Guides users on MUXI platform setup, configuration, and usage for AI agents, including CLI, formations, and API operations.

Manages MongoDB database backups, restores, and maintenance for data integrity and availability.