The Fifth Elephant OSAI meet-up - Hyderabad edition
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The Fifth Elephant OSAI meet-up - Hyderabad edition

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Prudhvi Krovvidi

Prudhvi Krovvidi

AI as Your Co-Developer: Automating Schemas, Quality Checks, Ingestion

Submitted Sep 6, 2025

Type of session: 25-35 min talk

Abstract

AI is moving beyond code completion to act as a true co-developer across the software development lifecycle (SDLC). From structuring raw data into validated schemas to guiding reliable data workflows, AI can reduce friction in everyday developer and data science tasks.

This talk showcases SchemaForge, an open-source experiment that demonstrates this shift:

  • SchemaForge: Goes beyond schema inference by creating ready-to-use DBT models, test rules, and ER diagrams. It also supports Python-based ETL pipelines, making schema outputs directly usable in production workflows.

Through live demos, we’ll explore how AI can ground generative outputs in structure, validation, and execution—and what this means for the future of AI-assisted development.

What the audience will take away

  • How AI can generate DBT-ready rules from raw data, with optional Python ETL ingestion support.
  • Patterns for integrating generative AI into real-world SDLC stages beyond “autocomplete.”
  • Lessons from building open-source AI tools: trade-offs, reliability concerns, and guardrails.

Format

  • Duration: 30 minutes
  • Type: Experiential talk with live demos
  • Structure:
    • Framing: AI in SDLC beyond code completion (5 min)
    • Demo: SchemaForge — schema inference → DBT rules → ingestion → execution (20 min)
    • Reflections and Q&A (5 min)

Target Audience

  • Data engineers and analytics developers who deal with repetitive schema, ingestion, and pipeline tasks.
  • Data scientists who want faster, structured ways to prepare and validate datasets.
  • Developers interested in building or contributing to AI-assisted open-source tools.

Speaker Bio

I’m Prudhvi Krovvidi, a Data Scientist at Gramener, where I explore how AI can simplify and accelerate data workflows. Most of my work ends up as open-source experiments on GitHub — from schema inference and quality checks to decision tree generation and AI-assisted analytics. I enjoy building lightweight tools that bring AI into everyday developer and data science tasks — and when I’m not doing that, you’ll probably find me out on my bike.

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