Companies invest in artificial intelligence and skip the human intelligence that makes it pay off. Half of workers never touch the AI tools their company buys. Live workshops, executive briefings, and custom training that change that — taught by an ex-Amazon software engineer who runs this stack in production.
Live instruction built around your stack and your data — what actually works right now, not hype. Every session ends with a capstone on your own usage, so training produces its first finding on day one.
For leadership. Where the money goes, which line items are worth defending, and what to ask your teams in the next planning cycle.
Briefing details →Coding agents in production, harness & loop engineering, token spend, model routing, evals — run on your repos and your bills, with guardrails.
See the catalog →A curriculum designed around your tools, your data, and the roles you actually have. From onboarding cohorts to a standing enablement program.
Talk through the scope →2,000+ original practice questions across the AI certifications, free. Plus short Claude Code courses, each with a free preview lesson. The same material the workshops are built from.
Start free at learn.cloudyeti.io →"Extremely full of useful techniques and ways of thinking. He was clear in his presentation. One of the best Udemy courses I have taken."
"You do an excellent job explaining. I had been a technical instructor for many years — you are elite."
"You explain conceptually, then show the console. Most instructors start with the console and miss the concepts, the differences, the insights."
From 50,000+ students across Udemy, YouTube, and live bootcamps.
Teams that go through a workshop usually surface the next hard question — a vendor, an architecture, a bill. This is where that goes.
Audits, second opinions, and ongoing counsel from someone with no stake in what you buy.
I go through your AI and cloud bills line by line, match the spend to what it produced, and give you a list of cuts and keeps you can act on.
See the audit →You have a decision on your desk: a vendor, a model, an architecture. Send it over and get an honest read from someone with no stake in the outcome.
How it works →Keep me on call. Monthly review, async questions between calls, and help with vendor pricing before you sign.
See the retainer →Fixed-scope sprints with your engineers — architecture, implementation, or debugging. Scoped up front, handed over with a runbook.
Tell me what's stuck or what you want built — a broken agent setup, a workflow to implement, an architecture call to get right. We scope it in one conversation, I work alongside your engineers until it ships, and your team owns the code and the runbook.
Talk through the scope →Saurav Sharma. Six years at Amazon: first as a Senior Technical Account Manager working with large enterprise customers on architecture, cost, reliability, and scaling, then building LLM and GenAI platforms as a software engineer.
I have taught 50,000+ students across Udemy, YouTube, and in-person bootcamps, and run the CloudYeti YouTube channel. Based in Washington, DC.
The AI side isn't theory. I run my own production LLM pipelines across OpenAI, Anthropic, and Google today. The pricing fine print I teach is fine print I pay for myself.
Tell me what your team is doing with AI and what you expected it to do by now. We'll find the gap and I'll tell you which of these actually fits, if any.
Book a free 30-minute call →No pressure. Just a short conversation to see what would be most useful.