Product engineer building AI automation systems, agentic developer tools, and vertical SaaS products.
I work across product, automation, and infrastructure: TypeScript/Next.js apps, Python services and CLIs, workflow automation, agent integrations, and practical OSS maintenance.
- AI automation systems: context capture, memory layers, MCP/agent integrations, n8n workflows, and RAG-style prototypes.
- Vertical SaaS products: finance tooling, compliance-oriented crypto systems, operational dashboards, bots, and internal workflow products.
- Developer infrastructure: local-first tools for agent handoff, repo analysis, CI triage, README validation, and GitHub Actions hygiene.
| Project | Focus |
|---|---|
| issue-to-agent | Turns GitHub issues into ready-to-run task packs for Codex, Claude Code, Cursor, and Copilot. |
| mergepack | Turns PR diffs into agent-ready merge packets for maintainers and reviewers. |
| loopback-litmus | Checks browser-to-localhost exposure in local AI agent, MCP, and WebSocket control planes. |
| repo-brief | Generates compact repository briefs for humans and coding agents. |
| ci-fix-brief | Condenses noisy CI logs into repair briefs for coding-agent sessions. |
| action-pin-check | Audits GitHub Actions workflows for mutable or missing action pins. |
| readme-command-check | Checks README shell commands before users copy broken quickstarts. |
Recent Python ecosystem contributions include open pull requests in:
TypeScript, React, Next.js, Python, FastAPI, pytest, PostgreSQL, Prisma, Docker, GitHub Actions, MCP, n8n, and LLM tool-calling workflows.
- AI-native product systems with reliable context and memory.
- Agent workflows that turn messy work into scoped, verifiable tasks.
- Practical automation for finance, operations, compliance, and developer productivity.