Mihail Eric

Mihail Eric

2.1K Subscribers

Head of AI at Monaco, Creator of Stanford's AI Coding Course

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Mihail Eric will make you and your engineering team AI-native

I’m Head of AI at Monaco, a startup building the future AI-powered revenue platform for GTM teams, backed by Human Capital, Benchmark, and Founders Fund. I'm also an adjunct professor at Stanford, where I created and teach "The Modern Software Developer", the university's first course on AI software development. I've trained hundreds of engineers on AI coding principles and have advised dozens of global software teams including Amazon, Allianz Global, Upstart, and more.

In past lives, I was a technical lead at Amazon Alexa where I built the first LLMs for the organization. I also founded a YC-backed AI coding company. Before that I started Confetti AI, a machine learning education startup that trained thousands of students globally and that I led until its acquisition in 2022.

Previously at
Y Combinator
Alexa
Stanford University

Alumni reviews

Junaid

Live cohort
Software Developer · Woolworths

Building an AI-Native Engineering Team

I've said this before after attending one of Mihail's previous courses: he'll change your life! Even though I may not be the primary decision-maker in my organisation, this course gave me a much better understanding of how to guide those conversations, ask the right questions, and communicate effectively with the people making those decisions. Where it was especially valuable for me was in the context of my own small software development consultancy. The course gave me practical frameworks and a clearer way of thinking about how to help clients and engineering teams adopt AI in a thoughtful, structured way. I can definitely see myself applying this in the real world.

Hannah

Live cohort
Senior Engineering Manager, AI Team · Honeycomb

Building an AI-Native Engineering Team

An excellent primer on the many dimensions of building an AI-native organization. Mihail draws on emerging patterns across companies to cover the full picture, from the software development lifecycle to organizational design, roles, hiring, cost governance, and ROI. The course begins with a practical four-point AI-native readiness scorecard, which gives participants a useful framework for assessing their organizations and contextualizing the material that follows. My organization averaged a 3, with 4 representing fully AI-native, so some of the foundational sections reinforced concepts that were already familiar to me. I found the greatest value in the second-half discussions about cost-governance models and demonstrating organization-wide ROI.

Rich

Live cohort
Director · Mastercard

Building an AI-Native Engineering Team

The best part of the course was learnings and insights from the current state of the art from silicon valley. The cohort made it even more interesting, with learners from varied backgrounds, sharing their experiences, struggles and wins.

Jaco

Live cohort
Solutions Architect AI · Allianz Global Investors

AI Software Development: From First Prompt to Production Code

Eric explains the material clearly and keeps it practical rather than overly academic. The course gives you a good understanding of not only what to do, but why certain approaches are better than others.

Kimmo

Live cohort
Software Engineering Manager · Kiwa

AI Software Development: From First Prompt to Production Code

A great course for engineers and engineering teams that are adopting or have adopted AI in software development.