AI Engineer | Researcher | Educator | Building Infrastructure for AI-Native Development
I design, build, and ship developer tools for AI coding agents: from observability and governance layers to MCP integrations and evaluation frameworks.
I also test frontier models, review AI developer platforms, and teach 100K+ engineers how to build with AI through long-form technical writing, courses, and open-source references.
These are the best entry points into my current AI work:
| Resource | Description |
|---|---|
| 500+ AI Tools Testing Reviews & Tutorials | My public research log for model releases, AI coding tools, automation workflows, and AI engineering patterns |
| Claude Code Masterclass | My newsletter and course ecosystem for Claude Code, Codex, agents, and AI-native development |
| Claude Code Cheat Sheet | A practical Claude Code reference covering commands, workflows, subagents, automation, and power-user usage |
| AutoWP MCP | A production-ready MCP server that connects Claude to WordPress publishing workflows |
| AgentTrace | A local-first CLI for observability and audit trails of AI-assisted coding work AgentTrace Docs |
I am focused on the practical discipline of AI engineering: building intelligent software systems that combine LLMs, agents, tools, automations, integrations, evaluations, and human workflows.
Over the last year, I have been testing new AI tools, publishing deep technical content, reviewing industry trends, and teaching developers how to use AI systems in real work.
| Platform / Skill | Content / Audience |
|---|---|
| Technical writing | 500+ articles on AI, software engineering, automation, AI coding, and AI developer tooling |
| Medium | 23K+ followers across AI and software engineering content |
| Newsletter | 70K+ subscribers on Claude Code Masterclass |
| YouTube | Built a channel around AI tools, model releases, workflows, and practical AI engineering |
| Project | What It Does | Pain Point Solved | Status |
|---|---|---|---|
| AgentTrace | Records AI coding tasks, Git diffs, test evidence, review notes, PR metadata, EvalOps evidence, and local dashboard reports | Gives teams an audit trail for AI-assisted coding instead of vague "the agent fixed it" claims | Public |
| MCPGuard | Governance, approvals, policy, and audit trails for MCP tool calls | Helps teams safely connect AI agents to external tools and sensitive systems | Building next |
| EvalOps | Benchmarks coding agents and model releases on practical engineering tasks | Turns AI tool reviews into repeatable evidence and enterprise-grade comparison reports | Planned |
| Resource | Description |
|---|---|
| Claude Code Cheat Sheet | Practical reference covering commands, workflows, subagents, hooks, automation, and power-user patterns |
| Claude Code Tutorials | Step-by-step demos and real use cases for learning Claude Code through working examples |
I run structured evaluations across the AI engineering stack and publish the results:
- Frontier models — OpenAI, Anthropic, Google, DeepSeek, Qwen — tested on coding, reasoning, refactoring, debugging, agent behavior, and context handling.
- AI coding platforms — Claude Code, Codex, Cursor, Windsurf-style IDEs, and terminal-first agentic workflows compared on real engineering tasks.
- Agent infrastructure — MCP servers, tool use patterns, subagents, hooks, project instructions, coding manifests, and AI-native dev environments.
- Automation systems — Connecting LLMs to APIs, data sources, content pipelines, and business operations at production scale.
500+ published articles and tutorials. 70K newsletter subscribers. 23K Medium followers. A YouTube channel with demos, model tests, and workflow walkthroughs.
| Channel | Focus |
|---|---|
| Medium | Deep technical articles — AI engineering patterns, tool reviews, automation workflows, model release analysis |
| Claude Code Masterclass | Newsletter and course ecosystem — Claude Code, Codex, agentic coding, and AI-native development |
| YouTube | Demos, coding tool comparisons, model benchmarks, and practical AI engineering walkthroughs |
| GitHub | Reference implementations, portfolio projects, and reusable developer workflows |
Python, TypeScript, JavaScript, React, Next.js, Vue, REST APIs, GraphQL, LLM APIs, MCP servers, retrieval systems, structured outputs, evaluation pipelines, and automation infrastructure.
I'm open to roles and collaborations in AI engineering, developer tooling, agent infrastructure, and technical education.
