While the speed of disruption from AI feels unprecedented, we can look to history to see what happens when a technical industry undergoes a massive, orders-of-magnitude jump in developer productivity.
If you want to see this playbook in action, look at the video game industry.
The Era of Floppy Disks and Bespoke Engines
In the early 1990s, when a studio built a new game, there were no ubiquitous off-the-shelf commercial game engines. Virtually every major title was built around a bespoke, ground-up rendering codebase. If your project fell behind schedule, you couldn't just hire a contractor who "knew the engine". The engine only existed on your studio’s hard drives.
Collaboration tooling was equally non-existent. Git didn't exist. Integrating your co-worker's code meant saving a file to a 3.5-inch floppy disk, walking across the room, physically handing it to them, and praying you didn't overwrite local changes. Want to ship on multiple platforms? You weren't tweaking build targets; you were manually rewriting C or assembly line by line for entirely different CPU architectures.
By today’s standards, the teams that created foundational genres were ridiculously small:
- Final Fantasy (1987): Defined the JRPG—crafted by a core team of roughly 7 people at Square.
- Wolfenstein 3D (1992): Practically birthed the modern FPS—built by a core team of just 6 people at id Software.
- Quake (1996): Brought true 3D and client-server multiplayer to the genre—required roughly 9 core developers at id (a lineup that reads like a hall-of-fame roster of gaming legends) working 100-hour crunch weeks for nearly two years.
The Productivity Explosion
In the decades that followed, a firehose of productivity tools reshaped development:
- Commercial engines like Unreal and Unity abstracted away lower-level graphics math so designers could focus on mechanics rather than writing custom texture-mapping routines.
-
Git saved us from email threads full of
pathfinding_v2_FINAL_for_real.zip. - Cross-platform compilation allowed a single codebase to target PC, consoles, iOS, and Android simultaneously.
Fast forward 20 years from Quake, and even before the rise of LLMs, game development productivity had increased so dramatically that a single developer at a 48-hour game jam could routinely build a functional 3D prototype with technical feature parity to id's 1996 masterpiece.
The breakthroughs that once required an entire R&D phase on the project delivery timeline—true 3D rendering, baked lighting, a high-level scripting language, and client-server netcode—are now done the moment a developer clicks File -> New Project in Unity.
Jevons Paradox in Action
So, logically, game development studios should have shrunk, right? If one engineer can now do what required nine world-class wizards in 1996, the industry should need fewer people. Marketplaces full of cheap 3D assets should have put artists out of work.
The reality was the exact opposite.
Today, end-game credits for a AAA title routinely run for 30 to 40 minutes. Top studios employ teams of PhDs dedicated entirely to the procedural physics of how individual strands of hair, grass, and cloth react to wind. These hyper-specialized roles were completely unimaginable when John Carmack was writing raycasting algorithms. And while individual legacy roles disappeared (few people earn a living hand-porting assembly between custom chipsets today), the total workforce building games has expanded exponentially over the last three decades.
This phenomenon isn't a fluke. It's a classic economic principle known as Jevons Paradox: as technological progress increases the efficiency with which a resource is used, total consumption of that resource increases rather than decreases.
When you make software production 10x cheaper and faster, you don't get 10x fewer developers. You get 100x more ambitious software.
What This Means for AI and Software Engineering
Of course, this won't be a smooth, uninterrupted climb. Every tech paradigm shift brings market volatility: a wave of layoffs one year as executives try to pocket the efficiency gains, followed by a hiring boom the next when competitors use that same efficiency to ship vastly superior products. There will always be good times, bad times, and painful transitional jitters, but the trendline will bend upward.
We are about to see this exact paradox play out with AI and general software engineering. As AI tools lower the cost of writing syntax, we won't stop needing engineers. We’ll just build systems so complex, immersive, and context-aware that today’s software will look like Wolfenstein 3D by comparison.
I look forward to seeing what software roles we have in ten years that sound as absurd to us today as "Senior Hair Strand Simulation Engineer" would have sounded to Carmack and Romero in 1992.
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