Working Hard at Working Smart
AI-Assisted by Day, AI-Native by Night
With the advent of AI, working smarter not harder has a whole new meaning. I help businesses and developers leverage AI tools and frameworks like CrewAI, Model Context Protocol (MCP), and emerging agent technologies to build better software faster.
As an AI-native developer, I bridge the gap between traditional software development and the new paradigm of AI-assisted and AI-driven applications. My expertise spans the full spectrum of modern AI development:
AI Integration & Strategy — I help organizations identify high-value opportunities for AI integration and develop practical implementation roadmaps. Whether you're looking to enhance existing products with AI capabilities or build new AI-native applications from the ground up, I provide hands-on technical consulting that delivers results.
Model Context Protocol (MCP) Development — As an early adopter and active contributor to the MCP ecosystem, I specialize in building custom MCP servers that extend AI assistants with powerful integrations. From API wrappers to complex tool chains, I create MCP servers that unlock new capabilities for AI agents.
Multi-Agent Systems — I design and implement sophisticated multi-agent architectures using frameworks like CrewAI. These systems combine specialized AI agents that collaborate to solve complex problems, from automated content workflows to intelligent research assistants.
Open Source Contributions — I actively contribute to the AI development ecosystem through open source projects, including MCP servers, comparison frameworks, and educational resources. My work helps developers worldwide navigate the rapidly evolving AI landscape.
From consulting on AI integration to developing custom MCP servers and multi-agent systems, I bring practical expertise in TypeScript, Python, and the rapidly evolving AI development landscape. I work with businesses of all sizes — from startups exploring their first AI integration to established companies scaling their AI capabilities.
Featured Projects
Open source contributions to the AI development ecosystem.
MCP Server - Gamma
Model Context Protocol server for Gamma presentation platform.
Awesome Comparisons
Curated comparisons of AI tools and frameworks.
Active in AI Communities
- Community Moderator for Block Goose AI
- Beta Tester for Tessl Framework
- Active in Skool's Coding the Future with AI
- Maintaining thirdbrain.tech - technical blog on AI development
Frequently Asked Questions
Common questions about AI-native development, MCP servers, and consulting services.
What is AI-native development?
AI-native development is building software where AI is a core architectural component from the start, not just an add-on. This includes multi-agent systems, AI-assisted workflows, and applications that leverage foundation models (like Claude or GPT-4) as integral parts of their functionality. Unlike traditional AI integration where AI is bolted onto existing systems, AI-native apps are designed around AI capabilities from day one.
What is the Model Context Protocol (MCP)?
MCP is an open protocol that standardizes how AI assistants connect to data sources and tools. Think of it as a universal adapter that lets AI agents interact with APIs, databases, file systems, and other services in a consistent way. I specialize in building custom MCP servers that extend AI assistants with new capabilities - from CRM integrations to specialized data sources.
How do multi-agent systems work?
Multi-agent systems use multiple specialized AI agents that collaborate to solve complex problems. For example, you might have a researcher agent that gathers information, a writer agent that creates content, and an editor agent that refines the output. Frameworks like CrewAI orchestrate these agents, managing their interactions and ensuring they work together effectively. This approach often produces better results than single large prompts.
What kind of projects do you take on?
I work on AI integration consulting, custom MCP server development, multi-agent system implementation, and AI strategy for businesses. Projects range from adding AI capabilities to existing products, building new AI-native applications, to developing internal AI tools and workflows. I work with both startups exploring AI and established companies scaling their AI capabilities.
How long does a typical AI integration project take?
Project timelines vary widely based on scope. A simple MCP server might take 1-2 weeks, while a comprehensive multi-agent system could take 2-3 months. During our initial consultation, I'll assess your needs and provide a realistic timeline based on project complexity, integration requirements, and desired features.
Do you work with companies outside your timezone?
Yes! I work with clients globally and am experienced in asynchronous collaboration. I provide regular updates, maintain clear documentation, and schedule calls at mutually convenient times. Most AI development work can be done asynchronously, with periodic sync meetings to align on direction and review progress.
Let's Build Something Together
Available for AI integration consulting, MCP server development, multi-agent systems, and custom AI solutions.