3. Data, Science & AI

Generates R tutorials for specialized data science applications including health economics, epidemiology, and signal processing.

Assists with database schema design, query optimization, migration management, and indexing strategies for efficient data handling.

Generates comprehensive R-based statistical tutorials for regression, survival analysis, causal inference, and Bayesian methods.

Builds data analysis pipelines for government open data sources, enabling processing and insights from datasets like Peru Compras.

Local, private, offline speech-to-text transcription using Parakeet MLX on Apple Silicon for audio files.

An AI agent system that iteratively refines search queries using subcall agents to synthesize comprehensive answers from memory.

Enables multi-agent coordination through blackboard architecture for mnemonic-based knowledge sharing and task execution in AI systems.

Configures Claude AI to proactively use mnemonic memory techniques without user input, enhancing recall efficiency.

Enables ontology-based entity discovery, validation, and relationship mapping for mnemonic memory systems through custom namespace definitions.

Spawns subagents early to parallelize research, review, and planning while conserving context in AI workflows.

Analyzes recent agent task executions to refine instruction sets and rule-based systems for improved AI agent performance.

Executes multi-agent AI evaluation scenarios with symbolic reasoning, large-context handling, and checkpointing, capturing structured evidence.

Creates and manages evidence-based benchmarks for AI agent performance testing, including infrastructure setup and scenario development.

Provides structured guidance for crafting effective prompts for large language models (LLMs) like Gemini Pro, GPT-4o, and Claude 3.5 Sonnet, emphasizing context and structure.

Expertise in ClickHouse database management including schema design, query optimization, cluster configuration, and monitoring for high-performance analytics.

Extracts verified quotes from Lenny's Podcast transcripts to populate PM Philosophy Recommendations with grounded content.

Configures combustion simulation cases with chemistry, boundary conditions, and solver settings for dfLowMachFoam, dfSprayFoam, and dfHighSpeedFoam solvers.

Automates setup of OpenFOAM CFD cases with boundary conditions, solver configuration, and physics modeling for incompressible and non-reacting flows.

LLM-powered extraction of structured CFD data from research papers, analyzing combustion simulations, turbulence models, and solver settings.

Manages agent configuration settings such as style, capabilities, and MCP server connections for AI agent customization and operation.

Executes code cells, reads notebook content, and runs Python scripts within Jupyter notebooks for data analysis and AI experimentation.

Provides Supabase-specific best practices for optimizing PostgreSQL performance, schema design, and database configuration.

Assists in implementing LTI systems, designing controllers, and analyzing system dynamics in control theory using Slicot.

Guides users in navigating and utilizing the SLICOT control theory library's 578 functions for system analysis and design.