FAQ

What Is the Cost Per Line of Code With AI-Assisted Development?

AI Economics

Key Takeaways
  • The COCOMO II (Constructive Cost Model) framework, the industry standard for software cost estimation, places typical development costs at $3-$18 per line of code depending on project complexity, team experience, and development environment.
  • The $0.06/LOC figure is not a projection.
  • Cost per LOC is a useful comparison metric because it normalizes across project sizes and timelines.

The audited cost per line of code with AI-assisted development is $0.06/LOC, based on Stealth Labz's $65,394 total build cost divided by 596,903 lines of production code across 10 deployed systems -- 50x-300x cheaper than traditional software development benchmarks.

Traditional Benchmarks

The COCOMO II (Constructive Cost Model) framework, the industry standard for software cost estimation, places typical development costs at $3-$18 per line of code depending on project complexity, team experience, and development environment. For mid-complexity business applications -- the category that covers CRM systems, lead generation platforms, and e-commerce tools -- COCOMO II estimates typically land at $8-$15/LOC. At those rates, Stealth Labz's 596,903-line portfolio would cost $4.8M-$9.0M.

How $0.06/LOC Was Achieved

The $0.06/LOC figure is not a projection. It is calculated from QuickBooks-verified expenditures:

Cost Category Amount
CON-02 (primary contractor) $40,700
CON-03 (secondary contractor) $9,722
CON-03/additional (contractor) $12,308
Anthropic/Claude (AI) $1,333
OpenAI (AI) $1,301
Leonardo.AI $30
Total build cost $65,394
Total LOC 596,903
Cost per LOC $0.06

The cost per LOC also decreased over time as the portfolio compounded. Early projects carried higher per-LOC costs because infrastructure was being built for the first time. Later projects inherited 95%+ of their codebase from the foundation, driving the marginal cost per new line toward zero.

Why This Metric Matters (and Its Limits)

Cost per LOC is a useful comparison metric because it normalizes across project sizes and timelines. The 50x-300x gap between $0.06 and the $3-$18 COCOMO II range reflects three structural advantages of the CEM approach:

  1. Foundation reuse: 95%+ of infrastructure code was written once and deployed across all 10 systems. Traditional development rebuilds this infrastructure for every project.
  2. AI-assisted generation: AI tools handled boilerplate, pattern implementation, and documentation -- work that traditionally consumes 40-60% of developer time.
  3. Compounding cost reduction: The 97.6% cost reduction over the portfolio was driven by each project making the next one cheaper, not by any single efficiency gain.

The limitation: LOC is a quantity metric, not a quality metric. However, the portfolio's 12.1% product defect rate (against 20-50% industry norms) confirms that lower cost per line did not produce lower quality code.

For decision-makers evaluating development proposals: ask for cost-per-LOC estimates and compare against the $3-$18 COCOMO II baseline. Any AI-assisted operation with a compounding methodology should demonstrate costs well below traditional benchmarks.


Related: [FAQ #67 — Cost of Custom Software With AI]

References

  1. Boehm, B.W. et al. "COCOMO II Cost Estimation Model." Per line of code cost benchmarks for software development.