3. Data, Science & AI

Orchestrates multi-agent AI workflows using SwarmKit SDK, enabling parallel processing, quality competition, and synthesis across multiple AI models for complex tasks.

Analyzes YouTube video transcripts and metadata to extract content insights through text processing and structured data handling.

Packages code repositories into AI-friendly formats for LLM analysis, including context generation, token counting, and security audit preparation.

Builds, deploys, and evaluates AI agents with multi-agent systems, workflow orchestration, and Google tool integration.

Optimizes and structures AI prompts for Claude, enhancing token efficiency and applying advanced techniques like CoT and few-shot to improve system instructions and agent behaviors.

Enables multimodal AI processing including audio transcription, image captioning, video analysis, and document extraction via Google Gemini API.

Processes and analyzes Excel spreadsheets with support for formulas, charts, pivot tables, and multiple file formats including CSV and TSV.

Provides development guidance for GAIK, enabling structured data extraction from documents, PDFs, and audio via AI-powered parsing and classification pipelines.

Validates and registers new System of Truth (SoT) IDs with cross-reference integrity for BR, UJ, API, and CFD entry types.

Automates memory management in AI systems via a Retrieve-Respond-Save loop to maintain long-term context and conversation history.

Analyzes coding agent session transcripts to improve existing AI skills or extract new ones through data-driven insights.

Adds new exercises to the workout tracker database, enabling expansion of the exercise library and verification of existing exercises.

Provides a Prompt API for constructing, merging, and manipulating conversational prompts with Effect AI using messages, parts, and composition operators.

Configures and composes AI provider layers for multiple LLM services with abstraction and runtime flexibility.

Enables text generation, structured outputs, streaming, and tool calling via Effect AI's language model service for conversational AI development.

Enables type-safe tool definitions, parameter validation, and handler implementations for LLM integrations using @effect/ai APIs.

Converts PDF documents into well-structured Markdown files, extracting and organizing text content for seamless editing and reuse.

Applies graph theory to visualize and analyze complex interconnected systems, aiding in problem-solving and architectural design.

Performs gene set enrichment analysis to identify biological pathways and functional associations from gene lists using AI-powered research tools.

Converts PDF, Office, image, HTML, and web content to Markdown for data processing, text extraction, and RAG pipeline integration.

Expertly deploys, monitors, and scales machine learning models and LLM systems in production environments with MLOps and RAG capabilities.

Provides advanced data science capabilities including statistical modeling, A/B testing, and predictive analytics using Python, R, and SQL to drive data-driven business decisions.

Expert computer vision skill for building and deploying AI systems including object detection, segmentation, and video analysis using PyTorch, OpenCV, and vision transformers.

Provides advanced prompt engineering for LLM optimization, RAG, agent design, and structured outputs to build effective AI products.