3. Data, Science & AI

Extracts structured data from websites, captures screenshots, and parses PDFs via Firecrawl API for comprehensive web data acquisition.

Provides production-ready architectural patterns for LLM applications, including RAG pipelines, agent design, and LLMOps monitoring to streamline AI development.

Optimizes LLM application performance via prompt caching, response caching, and Cache Augmented Generation (CAG) strategies.

Expert guide for crafting effective prompts to optimize LLM interactions, improve model outputs, and debug agent behavior through proven strategies and patterns.

Expert patterns for Neon serverless Postgres, including branching, connection pooling, and Prisma/Drizzle ORM integration.

Architects autonomous AI agents with expertise in tool integration, memory systems, and multi-agent coordination for complex task execution.

Assists in setting up, improving, and auditing analytics tracking systems including GA4, Google Tag Manager, and event tracking implementations.

Provides implementation patterns for Retrieval-Augmented Generation (RAG) systems, covering chunking, embeddings, and vector stores for semantic search.

Guides robust AI product development with scalable LLM integration, RAG architecture, and cost-effective AI UX design.

Expert in LangGraph, a production-grade framework for building stateful, multi-actor AI applications with agent graphs, state management, and ReAct patterns.

Guides AI agent tool design with JSON Schema, LLM-friendly descriptions, and MCP standards to prevent hallucinations and optimize token usage.

Provides LLM observability for tracing, prompt management, evaluation, and debugging of AI applications in production environments.

Optimizes generative AI search engines (ChatGPT, Claude, Perplexity) for enhanced query relevance and performance.

Guides database schema design, indexing strategies, ORM selection, and serverless database considerations for optimal data management.

Expert guidance for implementing Segment CDP with tracking plans, identity resolution, and data governance best practices.

Architects agent memory systems including short-term context and long-term vector stores, emphasizing retrieval strategies for intelligent agents.

A hybrid memory system enabling persistent, searchable knowledge management for AI agents, tracking architecture, patterns, and decisions.

Creates custom, interactive data visualizations with fine-grained control using d3.js for charts, graphs, and geographic maps in any JavaScript environment.

Design patterns for building autonomous coding agents, covering tool integration, permission systems, and browser automation.

Expert guidance for designing and optimizing distributed NoSQL databases (Cassandra, DynamoDB) with query-first modeling and hot partition avoidance.

Expert in CrewAI, a role-based multi-agent framework for orchestrating collaborative AI agent teams to handle complex workflows and tasks.

Enables natural voice interaction AI with sub-800ms latency using speech-to-speech and STT-LLM-TTS pipeline architectures.

Builds optimized RAG systems using embedding models, vector databases, and retrieval strategies for enhanced LLM applications.

Enables reliable autonomous AI agent development using structured loops, goal decomposition, and reflection patterns to minimize error compounding.