The Code Inflation

Exploring the evolution of the cost of generating a line of code—from early expert-written code on enormous machines to today's LLM-generated code—highlights dramatic shifts in computation, labor, tooling, and economics. Here's a step-by-step walkthrough of this progression:

• Machines: ENIAC, UNIVAC, IBM 1401

• Expertise: PhDs or highly trained engineers; only a handful globally had this skill.

• Tooling: Machine code or early assembly language; punch cards.

• Time & Cost:

  • Writing and debugging a single line might take hours or days.

  • Mainframe time was extremely expensive (hundreds to thousands of dollars per hour).

  • Adjusted for inflation, writing one line could easily cost $100–$1,000+.

• Overhead: No IDEs, no testing frameworks, no real debugging tools.

• Machines: PDP-11, VAX, IBM System/370

• Tooling: Basic editors, debuggers, and compilers.

• Labor Cost: Still expensive developers, but more widespread (~$30–$50/hour).

• Time & Cost:

  • A line of functional code could cost $5–$20, factoring in wages, tooling, and overhead.

  • Projects required many engineers and careful planning (e.g., waterfall model).

• Machines: x86 PCs running Windows, Linux, Mac.

• Languages: C++, Java, Visual Basic.

• Tooling: IDEs (Visual Studio, Eclipse), version control, debugging tools.

• Labor Cost: Developers ~$50–$100/hr in developed countries.

• Time & Cost:

  • More productivity: a line of code might cost $0.50–$5 depending on complexity.

  • Reusability and open-source libraries significantly reduced cost.

• Machines: Scalable cloud (AWS, Azure, GCP)

• Languages: Python, JavaScript, Go, etc.

• Tooling: GitHub, Docker, Kubernetes, automated testing.

• Labor Cost: Devs still ~$50–$150/hr, but output improved with automation.

• Time & Cost:

  • Some estimates suggest $0.10–$1.00 per line, factoring in modern efficiency.

  • Open-source reuse and Stack Overflow further reduced marginal cost.

• Machines: GPUs or TPUs in data centers (invisible to user).

• Tooling: GitHub Copilot, ChatGPT, Replit Ghostwriter, etc.

• Labor Cost: Developer oversees or edits output, but may not write it directly.

• Inference Cost:

  • Token-based pricing: One line of code (~10–30 tokens) may cost $0.001–$0.01.

  • Electricity and infra per token: Small but non-zero—maybe $0.0001 per line in bulk inference.

• Time & Cost:

  • Effective marginal cost: ~$0.001–$0.10 depending on LLM, quality, and post-editing effort.

  • Total cost drops by 100x–1000x compared to early computing.

EraTypical Cost/LoCPrimary Factors1940s–1960s$100–$1,000+Manual labor, hardware cost, low abstraction1970s–1980s$5–$20Higher-level languages, minicomputers1990s–2000s$0.50–$5IDEs, reusable code, lower hardware cost2010s–early 2020s$0.10–$1.00Cloud, DevOps, open-source libraries2023–2025 (LLMs)$0.001–$0.10AI inference cost, assisted productivity

• The cost to generate a line of code has dropped by ~5–6 orders of magnitude.

• From human labor bottlenecked by hardware, we've moved to machine-generated code bottlenecked only by creativity and correctness.

• We’ve gone from coding on million-dollar machines to generating code for fractions of a cent in seconds.