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Prabhav Jain

Prabhav Jain

Agentic AI engineer building resilient, production-ready AI agents

prabhav
Bengaluru, Karnataka, India
Joined February 2026
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Summary

Practical agentic AI engineer focused on reliability and survivability in production: Prabhav consistently emphasizes memory, state persistence, failure recovery, and distributed-systems best practices for AI agents — arguing that durable context and observability separate demos from production-ready agents. nitter+2
Technical writer and educator: he authors long-form guides and tutorials (MCP guide, agentic AI roadmap) aimed at developers learning to build tool-using, multi-step agents and publishes on TapNex Wiki, DEV, and Forem. dev+2
Early-stage founder and community engager: listed as a co-founder at TapNex and active as a campus/community representative and ambassador in multiple programs, indicating involvement in both product-building and developer outreach. rocketreach+1
Active social presence focused on agentic AI topics: uses social platforms to share short-form insights, threads, and tips about building resilient AI agents and to engage with the developer community. nitter+1

Work

Education

Projects

Writing

Model Context Protocol (MCP) Explained for Developers: Why AI Agents Need It

January 1, 2026

Explains the Model Context Protocol (MCP), why persistent structured context is important for agentic AI, and how MCP enables tool use and reliable multi-step workflows.

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What Is Model Context Protocol (MCP)? A Simple 2025 Guide for AI Agents

December 1, 2025

Long-form guide on MCP: architecture, use cases, security/governance, and how MCP improves reliability for agentic workflows.

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Complete Roadmap to Become an Agentic AI Engineer in 2025

December 1, 2025

Comprehensive roadmap covering skills, frameworks, projects, and career strategies for building and deploying agentic AI systems.

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Hobbies

Writing and sharing technical guides and daily tips about agentic AI on developer platforms and social media. dev+1