Podcast Summary: The Third Golden Age of Software Engineering – Thanks to AI, with Grady Booch

Podcast: The Pragmatic Engineer
Host: Gergely Orosz
Guest: Grady Booch
Date: February 4, 2026

Overview

In this engaging episode, legendary software engineer Grady Booch joins Gergely Orosz to discuss the history and future of software engineering in light of rapid AI advancements. Contrary to doomsayers predicting the obsolescence of software engineers due to tools like ChatGPT and AI coding assistants, Booch argues we are entering the “third golden age” of software engineering. Drawing on decades of experience, Booch takes listeners through key inflection points in the industry, examines recurring existential fears, and explains why human-centric engineering skills remain vital—even as AI transforms our tools and workflows.

Key Discussion Points and Insights

1. The Nature and Evolution of Software Engineering

• Origins of “Software Engineering”
  • Coined by Margaret Hamilton (Apollo Program), establishing distinction from hardware engineers.
    • "She began using the term software engineer. And I think we can rightfully give her the claim to the first one that coined that." (Grady, 01:29)
  • Initially applied engineering rigor to code—optimizing solutions while balancing technical and human factors.
  • Even from inception, software was seen as a process of balancing technical limitations, human concerns, and ethics.
    • "We build systems that balance those forces. And we do so in a medium that is absolutely wonderful." (Grady, 04:52)

2. The Golden Ages of Software Engineering

First Golden Age (late 1940s–late 1970s)

• Defining Features
  • Focused on business/mathematical automation.
  • Primary abstraction: algorithms, flowcharts.
  • Software inseparable from hardware until the rise of assembly and higher-order languages.
• Complexity and Bottlenecks
  • "The primary means of decomposition was algorithmic abstraction." (Grady, 13:09)
• Foundations of Open Source and Shared Knowledge
  • Early software was sometimes freely shared, e.g. IBM Share.
• Defense & Innovation
  • Military drove much progress (e.g. SAGE air defense system).
  • "Much of modern computing is really woven upon the loom of sorrow." (Grady, 15:48)

Second Golden Age (late 1970s–early 2000s)

• Rising Complexity & Distributed Systems
  • Push toward distributed, larger-scale, and real-time systems (influenced by defense and enterprise needs).
  • "We saw a new rise in levels of abstraction from individual components of our software programs to whole libraries and packages." (Grady, 44:46)
• Introduction of Object-Oriented Paradigms and Platforms
  • Shift from process-centric to object-centric/code and data encapsulation.
  • Platforms and reusable components began to dominate (e.g., Salesforce, SAP).
• Economic and Cultural Context
  • Growth of the personal computer, software becomes more accessible—hobbyists and counterculture play a role.
  • The internet and open-source models take hold.

Third Golden Age (Early 2000s–Present)

• Explosion of Tools, Higher-Order Abstractions, and AI
  • Software systems now often composed by integrating existing libraries, APIs, and cloud services.
  • AI assistants are now pushing the abstraction level further, prompting an existential re-examination by professionals.
  • New challenges: supply chain security, safety, scale, and ethics.
• AI as a Force Multiplier, not a Replacement
  • "The problems we have now ... are different than they were ... but equally as exciting." (Grady, 49:36)

Existential Dread: AI and the Future of Coding

1. The Recurring Fear

• Every major abstraction leap (compilers, high-level languages, platforms) created existential angst.
  • "Developers have faced this exact existential crisis before. Multiple times in fact... Each time the people who understood ... it was just a new level of abstraction, they came out ahead." (Host, 76:23)
• Coding has always been a part—never the whole—of software engineering.
  • "Software engineers are the engineers who balance these forces. We use code as one of our mechanisms, but it's not the only thing that drives us." (Grady, 59:32)

2. The Role (and Limits) of AI

• Grady’s personal use of AI assistants:
  • “I use Claude...for problems with JavaScript, Swift, PHP, and Python. It’s been a great thing for me...to accelerate my understanding.” (Grady, 58:13)
• AI agents excel at automating patterns and well-trodden code—especially CRUD, web UIs, etc.
• True software engineering—balancing technical, human, economic, and ethical constraints—remains beyond current AI.
  • "None of the things ... attend to any of those decision problems that a software engineer has to deal with. None of those we see within the ... realm of automation." (Grady, 59:45)

3. Response to Dario Amodei’s Claim (Anthropic CEO)

• Amodei: “Software engineering will be automatable in 12 months.”
• Booch: "It's utter bullshit. That's the technical term, because I think he's profoundly wrong." (Grady, 59:32)
• Main points of critique:
  1. Amodei’s view is limited to automatable aspects (repetitive patterns, code generation).
  2. Most engineering, especially at scale, involves systems thinking, context, ethics—irreducible to automation.
  3. AI will automate away tedium and enable non-experts ("hobbyists") to build more, echoing impacts of the PC era.

What’s Becoming Obsolete and What Matters More

1. Skills at Risk (66:11–68:00)

• Low-level, repetitive code construction (e.g., setting up boilerplate, wiring up infrastructure, simple apps).
• Manual, rote programming—especially as AI handles standard patterns.

2. Skills Growing in Importance

• Systems thinking and systems theory (complexity, distributed systems, emergent properties).
• Ability to manage and coordinate distributed, socio-technical systems.
• Human-centric communication: understanding business context, ethics, and tradeoffs.
• Architecture and orchestration at a platform or system level.
  • "The shift now ... is less so from dealing with programs and apps to dealing with systems themselves. And that's where the new skill set should come in." (Grady, 68:00)

3. Advice to Students and Professionals (69:07–73:27)

• Return to fundamentals, especially systems theory (Simon, Newell), complexity science (Santa Fe Institute), and studies in biological/neurological systems.
• Study works like Minsky’s Society of Mind for insight into multiple-agent systems and emergent behaviors.
• “By looking at architecture from a systems point of view, from biology, from neurology, from systems in the real world ... this is what’s guiding me to the next generation of systems.” (Grady, 73:10)

The Opportunity Ahead

Imagination and Creation Unleashed

• Barriers and costs of software construction are dropping—imagination and systems understanding become limiting factors.
• "You are actually being freed because ... the costs of development are actually disappearing for you ... So think of it as an opportunity." (Grady, 74:28)
• Era parallels to previous golden ages where outsiders contributed transformative ideas.

Closing Reflection

• “It’s an exciting time to be in the industry. It’s frightening at the same time, but that’s as it should be. When there’s an opportunity where you’re on the cusp ... you can either look and say, crap, I’m going to fall into it, or say, no, I’m going to leap and I’m going to soar. And this is the time to soar.” (Grady, 75:21)

Notable Quotes & Memorable Moments

• On AI’s Limits:
  "Your tools are changing, but your problems are not." (Grady, 59:45)

• On Fear & History:
  "Developers have faced this exact existential crisis before. Multiple times in fact." (Host, 76:23)

• On Dario Amodei’s prediction:
  "It's utter bullshit. That's the technical term, because I think he's profoundly wrong." (Grady, 59:32)

• On Abstraction:
  "Every major leap in abstraction brought with it a new existential dread, and every time the field as a whole just moved up a level." (Paraphrase, multiple segments)

Key Timestamps

• 00:00–05:44: Origins of software engineering; Margaret Hamilton; early history
• 09:16–19:33: The First Golden Age—algorithmic abstraction, business automation, defense projects
• 19:33–27:56: The "software crisis" and push towards new abstractions (object/object-oriented, functional)
• 27:56–35:45: Second Golden Age—PC revolution, counterculture, rise of platforms and object-oriented design
• 44:22–50:26: Third Golden Age—component abstraction, explosion of libraries, onset of modern AI tools
• 52:08–55:56: The existential dread cycle; coding is not the full story
• 57:23–62:00: Dario Amodei’s predictions and Grady’s direct, scathing response
• 66:11–69:07: Which skills will become obsolete, what will matter more
• 69:07–73:27: Foundational knowledge for the AI era and recommendations
• 74:13–76:14: How to thrive in new golden ages; advice for the next generation

Summary & Takeaways

• Software engineering is not going away—it is rising to a new level of abstraction, as it always has.
• AI coding assistants are the compilers and high-level languages of today—they will commoditize some skills but make others (systems thinking, ethics, context) even more vital.
• The biggest limitation now is imagination, not code—software professionals should embrace the new tools to build what was previously impossible.
• History shows the field grows, not shrinks, with each abstraction leap—those who understand this are primed to succeed in the third golden age.

For further reading, Grady Booch recommends:

• Herbert Simon & Allen Newell: Sciences of the Artificial
• Marvin Minsky: Society of Mind
• Complexity science works from the Santa Fe Institute

“When there’s an opportunity where you’re on the cusp of something wonderful, you should look at the abyss and say: You can either fall, or you can leap and soar. This is the time to soar.” – Grady Booch (75:21)