Geet Sharma

@geetsharma

Joined January 2026

Geet Sharma's blogs

Agentic AI & System Designgeetsharma.hashnode.dev13 posts

Data Engineering + platform architecturedata-engineering-platform-architecture.hashnode.dev5 posts

Architecture&Designarchitectureanddesign.hashnode.dev4 posts

DECODING INDUSTRY & DOMAINdecoding-industry-and-domain.hashnode.dev4 posts

AI System Reliabilityai-system-reliability.hashnode.dev4 posts

Recently published

building-an-ai-data-pipeline.hashnode.dev

Building an AI Data Pipeline Using Python, Pandas, Flask, and Generative AI

Introduction Most real-world AI systems start with data pipelines, not models. Raw data must be ingested, cleaned, transformed, and analyzed before any AI can generate meaningful insights. In this article, I’ll show how to build a simple AI Data Pipe...

Jan 292 min read

ai-sales-insights-dashboard.hashnode.dev

Building an AI Sales Insights Dashboard Using Python, Flask, and Local LLM

Introduction Sales teams deal with large volumes of data but often struggle to extract meaningful insights quickly. Dashboards provide metrics, but they don’t explain why trends happen or what actions to take next. In this article, I’ll show how to b...

Jan 283 min read

building-an-ai-job-description-analyzer.hashnode.dev

Building an AI Job Description Analyzer Using Python, Flask, and Local LLM

Introduction Job descriptions often contain large blocks of unstructured text. Recruiters and candidates manually scan them to identify required skills, experience levels, and role expectations. This process is time-consuming and inconsistent. In thi...

Jan 282 min read

building-your-own-local-ai-copilot.hashnode.dev

Building Your Own Local AI Copilot Using Python + Flask + Ollama

Most developers today rely on cloud-based AI tools such as ChatGPT or GitHub Copilot. While powerful, these tools introduce several challenges: Privacy concerns Dependency on external APIs Cost unpredictability In this article, I’ll show how to ...

Jan 272 min read

ai-system-reliability.hashnode.dev

Chaos Engineering for AI Agents: Breaking Your System on Purpose

Most AI systems look perfect during demos. Then they meet reality. Servers go down.APIs timeout.Vector databases slow.Models hallucinate. Chaos engineering exists for one reason: To discover failure before users do. Instead of waiting for disasters, ...

Jan 273 min read