Scaling with Parallel Agents and Practical Limits

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 infrastructure for a fast-moving $35M-funded startup disrupting enterprise CRM

🎯 How to ace AI engineering interviews — Mihail's framework for demonstrating real AI engineering competence beyond prompt engineering basics. Essential watching for software engineers, ML practitioners, and engineering managers who want an honest, practitioner-level view of where the profession is going — from someone who's both teaching it at Stanford and building it in production.

🔗 Links & Resources

Mihail Eric on LinkedIn: https://www.linkedin.com/in/mihaileric/

Mihail's website: https://www.mihaileric.com

Stanford course "The Modern Software Developer": https://themodernsoftware.dev/

Maven course — AI Software Development: From First Prompt to Production Code: https://maven.com/the-modern-software-developer/ai-course

Free AI Engineer interview prep course: https://course.aiengineermastery.com/

Monaco (AI-native revenue engine): https://monaco.com

MLOps.community Slack: https://go.mlops.community/slack

⏱️ Timestamps

00:00 Intro — Mihail Eric & Monaco

04:00 What has actually changed for software engineers in 2026

09:00 Inside Stanford's "Modern Software Developer" course

15:00 Why agents require more human thinking, not less

21:00 From writing code to designing systems — the architect mindset

27:00 The Build System: running agents at scale in production

33:00 What junior engineers should focus on right now

39:00 Building AI infrastructure at Monaco

44:00 How to demonstrate real AI engineering competence

49:00 Skills that will remain irreplaceable

52:00 Rapid fire/closing thoughts