10+ years building enterprise systems. Now I teach professionals how to use AI tools in their actual work — not toy demos, not vibes, just what works.
AI tools, engineering workflows, and lessons from building in production.
Stop one-shot prompting. I engineered Claude Code with CLAUDE.md, custom commands, skills, and task phases — then let it build a full React + Firebase app from structured context.
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Live demo: Claude Cowork running 4 real tasks on my laptop — browser automation, PPT creation, YouTube data analysis, and parallel multi-tasking. Not a simulation.
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3 features professionals use daily: /init for persistent memory, Plan Mode for think-before-code, and --add-dir for multi-project context. Live demo: 53 unit tests written automatically on a real .NET SaaS app.
Watch →A folder-based workflow automation system for Claude Cowork. Define repeatable AI workflows once — manual pipelines with approval gates, scheduled tasks, multi-stage projects. Includes a YouTube content pipeline and daily community scout out of the box.
A plugin for Claude Code and Cowork that prevents accidental file deletion and overwrites. Adds automatic backups, dry-run planning, and activity logging — a safety layer for AI-assisted development.
YouTube content management PWA for tracking ideas, scripts, feedback, and publishing workflow. Built to solve my own problem of managing 20+ video ideas at once.
I teach in-person, not just on screen. Hands-on sessions where people build real things with AI.
A hands-on session where developers use Claude Code and non-technical professionals use Claude Cowork to build an MVP together, live.
Learn more →I teach AI adoption broadly. Claude is where I go deepest — so that's where the first meetup starts.
Before I taught AI adoption, I spent 10 years building enterprise systems — multi-tenant migrations, identity platforms, deployment orchestration. That background is why I know when AI helps and when it doesn't.
Today I'd use AI to automate the tenant-by-tenant migration validation. Back then, we did it manually.
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This was AI in production before the hype cycle. Probabilistic models making real deployment decisions.
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Legacy modernization at its messiest. The kind of system complexity where AI-generated code breaks on day one if you don't understand the domain.
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Identity systems have zero margin for error. AI accelerates the boring parts — but a human must own the critical path.
View Case Study → Senior Platform Engineer with 10+ years building enterprise software and cloud infrastructure. I've architected multi-tenant Kubernetes migrations, built AI-powered deployment systems, and led identity platforms serving 50K+ daily authentications.
Now I build with AI in the open and teach engineers what I learn — through YouTube, open source, and real case studies.
Based in Mumbai. Building and teaching globally.