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.
How OpenClaw actually works internally, why it burns 10,000 tokens before your first message, and what makes it fundamentally different from Claude Code or Cowork. Real use cases, honest security risks, and whether you should try it today.
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How Claude Cowork automates the entire workflow — reading websites, analyzing content, and delivering summaries directly to Slack — without a single line of code. The Brain, Eyes, Mouth mental model for AI automation.
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One terminal, one agent, 15-minute wait per task. What if you ran 3 AI agents in parallel on the same codebase? Production-grade workflow for 3-4x development speed without sacrificing code quality or safety.
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.