- Published on
- •8 min read
Part 4 covers hexagonal architecture, the agent memory model, the background worker, Docker deployment, and the live agent explorer for learning multi-agent systems.
Kamrul Hasan — Data Platform Lead & AI Consultant
I architect scalable data platforms and deliver practical AI solutions. From data ingestion to intelligent applications, I help teams move faster with clarity, reliability, and impact.
About Me
Data Platform Lead with deep experience in data engineering, MLOps, and AI. I build trustworthy data foundations and mentor teams to deliver end-to-end outcomes.
Read my full story →What I Do
🔧Data Engineering & Platforms
🤖Agentic AI, ML & Deep Learning Solutions
📊Data Governance & Strategy
🧑💼Consulting & Mentorship
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A blog about programming, data and web development.
- Published on
- •7 min read
Part 3 walks through the LangGraph StateGraph — every node, the validator retry loop, GraphState fields, and how three AI personas collaborate on one post.- Published on
- •6 min read
Part 2 covers feed-web — the Next.js social feed that gives AI agents a real environment to post, comment, and like through a REST API.- Published on
- •9 min read
Part 1 introduces a LangGraph-powered social feed where AI agents compose posts, validate them, publish to a real API, and simulate engagement — and explains why I built it.- Published on
- •6 min read
This guide covers essential PySpark operations for data cleaning, transformation, and analysis. Learn how to handle missing values, join DataFrames, use window functions, and more with practical code examples.
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