Does moving faster with AI mean you get to skip the laws that governed every software project before it? Milan Milanovic argues the opposite, the old laws of software engineering now apply twice as hard.

In this episode, Milan Milanovic, CTO and author of Laws of Software Engineering, returns to unpack why the laws that have quietly governed software projects for decades are more relevant than ever in the AI era. He walks through Gall’s Law and why AI lets teams generate complex systems on unvalidated assumptions faster than ever, Conway’s Law and how it now runs twice, shaping both human organizations and agent topologies, and Goodhart’s Law and the trap of “tokenmaxxing” as a metric. Milan also covers Hofstadter’s Law and the 90-90 rule, explaining why the last 10% of a project still takes as long with AI in the loop, and the Dunning-Kruger effect, where vibe coders overestimate their skills while senior engineers underestimate theirs. The conversation closes with his advice for juniors entering the field, his top five must-read books, and how he personally uses AI for research and planning rather than implementation.

Key topics discussed:

Gall’s Law: the trap of generating complex systems with AI
Conway’s Law now runs twice, on humans and on AI agent topology
Why software architects should help design your org chart
Goodhart’s Law and the danger of “tokenmaxxing” as a metric
The 90-90 rule: why AI’s last 10% still costs half the project
Dunning-Kruger effect on vibe coders and experts
Why less code beats more, even with AI writing it for free

Timestamps:

(00:00) Trailer & Intro
(03:02) What Inspired Milan to Write Laws of Software Engineering?
(05:32) How Did a Book on Software Laws Reach Such a Global Audience?
(06:49) How Should You Read the Laws of Software Engineering Book?
(08:51) Why Does the Book Cover People and Planning, Not Just Technical Laws?
(11:07) What Is Gall’s Law in Software Engineering?
(14:46) How Can You Apply Gall’s Law When Using AI?
(17:34) What Is Conway’s Law in Software Engineering?
(19:34) How Should Big Corporations Build New Products Without Structural Reorganization?
(21:26) How Does Conway’s Law Apply to Small AI-Powered Product Teams?
(23:25) What Is Goodhart’s Law in Software Engineering?
(25:52) What Are the Best Examples of Counterbalance Metrics for Leaders Today?
(28:06) What Kind of Outcomes Should You Actually Measure?
(31:01) What Is Hofstadter’s Law in Software Engineering?
(33:35) How Does Hofstadter’s Law Apply in the Age of AI?
(36:41) What Is the Dunning-Kruger Effect?
(40:10) How Does the Dunning-Kruger Effect Apply to Experienced Engineers Learning AI?
(42:46) Are Any of These Laws Becoming Less Relevant Because of AI?
(44:32) What Does the Lindy Effect Say About the Fate of Software Developers?
(47:49) What Is the Best Career Advice for Junior Developers Entering the AI Landscape?
(50:34) What Are the Top Five Must-Read Books for Software Engineers?
(55:46) How Can Software Engineers Apply These Laws in Their Daily Work?
(57:26) 3 Tech Lead Wisdom

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Milan Milanovic’s Bio
Milan Milanović is the CTO and the author of Laws of Software Engineering. He holds a PhD in Computer Science, has more than 20 years of experience across .NET, Azure, and mobile development, and is a Microsoft MVP. He runs Tech World With Milan, a software engineering newsletter and community followed by more than 400,000 engineers. He writes about architecture, engineering leadership, and how AI is changing the way software gets built.

Follow Milan:

LinkedIn – linkedin.com/in/milanmilanovic
Twitter / X – @milan_milanovic
Personal website – milan.milanovic.org
Book’s website - lawsofsoftwareengineering.com
Newsletter - newsletter.techworld-with-milan.com

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Software Engineering Laws Every Developer Must Know in the AI Era - Milan Milanovic

Tech Lead Journal

Software Engineering Laws Every Developer Must Know in the AI Era - Milan Milanovic