
Agentic Workflow with LangChain + LangGraph
Walkthrough of an agentic workflow built on LangChain and LangGraph — graph-based orchestration, tool use, and stateful multi-step reasoning.
- LangChain
- LangGraph
- Python
- LLM Agents
Open to opportunities
software engineer building data pipelines
5+ years turning messy external data into clean, validated records — with TypeScript, React, Node.js, Python, and PostgreSQL doing the heavy lifting.
The languages, frameworks, and platforms I reach for most often.
Data pipeline tooling, an Electron desktop suite, and React Native apps shipped to both stores.

Walkthrough of an agentic workflow built on LangChain and LangGraph — graph-based orchestration, tool use, and stateful multi-step reasoning.
Mobile study app for the AZ-900 Azure Fundamentals certification, available on the App Store and Google Play. Interactive learning with practice questions and exam prep.

Internal QA desktop tool automating regulated study workflows. Electron pairs a React renderer with Node services to pull jobs from secure shares, validate CSV/XLSX files in real time, preview PDFs, and ship signed builds per environment.

Demo of a Supabase-backed mobile experience covering authentication, realtime data, and Expo tooling with React Native.
Notes from recent work — debugging, tooling, and the occasional deep dive.
An OpenAI Agent Escaped Its Sandbox—and AI Had Its Wildest WeekVideo
A benchmark agent found a zero-day in its own package proxy, reached the internet, and pulled the answers from Hugging Face. Long-horizon autonomy moves the unit of safety from the single tool call to the whole trajectory.
How I Built a Local AI Talking Head That Keeps the Real PersonVideo
Instead of regenerating the person, the pipeline keeps the real recording and synthesizes only the pixels inside a mouth mask. SyncNet holds the normal track at a zero-frame offset, and a deliberate 400 ms shift moves it by 10 frames — the evaluator is tracking timing, not faces.
Why AI Agents Fail After the Demo—and What CARS24 Gets RightVideo
CARS24 reports more than a million agent conversation minutes a month while most agent demos collapse the moment the task leaves a clean prompt. The difference is a five-part contract around the model: accepted outcome, bounded permissions, evidence-based routing, trajectory evaluation, and a fallback.
Remotion: The Part Most Tutorials MissVideo
Remotion is the camera and the stage, not the director. The polish comes from four visual rules, three reusable templates, and a review loop that judges rendered frames at phone size instead of the source code.
Why AI Coding Agents Ship Unreviewed WorkVideo
A review approves artifact A, a retry drops artifact B at the same path, and the saved approval still passes because it was never bound to the bytes. A read-only verifier recomputes the digest at the action boundary and refuses the replacement.
/ Let's build
Interested in software engineering roles focused on data integration, developer tooling, or cross-platform product work — especially where data accuracy and reliability are non-negotiable.