# The Modern Software Engineer

Page: https://stenobird.com/podcast/mlops-community/the-modern-software-engineer
Text version: https://stenobird.com/podcast/mlops-community/the-modern-software-engineer.md
Podcast: [MLOps.community](https://stenobird.com/podcast/mlops-community)
Published: 2026-04-14T18:58:01+00:00
Episode link: https://podcasters.spotify.com/pod/show/mlops/episodes/The-Modern-Software-Engineer-e3hsucv
Audio file: https://anchor.fm/s/174cb1b8/podcast/play/118437727/https%3A%2F%2Fd3ctxlq1ktw2nl.cloudfront.net%2Fstaging%2F2026-3-14%2F422044684-44100-2-1cdbd093dfe5f.mp3
Processing state: processed
JSON: https://stenobird.com/v1/public/podcasts/mlops-community/episodes/the-modern-software-engineer
Duration seconds: 3217

## Resource

This episode is brought to you by the MLflow team. Check out more information at MLflow.org . Mihail Eric is Head of AI at Monaco and Adjunct Lecturer at Stanford University, where he teaches CS146S: "The Modern Software Developer" — the first course in the world dedicated to how AI is transforming every stage of the software development lifecycle. With 12+ years building production AI systems at Amazon Alexa, Storia AI (YC S24), and early-stage startups, Mihail has one of the most grounded, practitioner-level takes on what it actually means to be a software engineer in 2026. The Modern Software Engineer // MLOps Podcast #370 with Mihail Eric, Head of AI at Monaco 🧠 What the modern software engineer actually looks like — why the job description has fundamentally shifted from writing code to designing systems and directing agents ⚙️ Agents require more thinking, not less — why the engineers getting the most out of coding agents are the ones who invest the most upfront in architecture, planning, and codebase structure 🎓 Inside Stanford's "Modern Software Developer" course — what Mihail teaches in the first CS course in the world focused entirely on AI-transformed software development 🏗️ From writing code to designing systems — how the best developers are repositioning themselves as architects of agentic workflows rather than line-by-line coders 🔁 The Build System: how to run agents at scale — practical lessons from building multi-agent pipelines, parallel subagent batches, and automated retrospectives📉 What junior engineers should actually focus on — the skills that remain irreplaceable and the paths that still produce strong software engineers in an AI-first world 🚀 Building Monaco's AI-native revenue engine — what it's like building AI infrastructur…

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## Transcript

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