A $50k contract delivered for $297. Not a typo.
The "Ralph Wiggum loop" is an autonomous coding pattern where an AI agent restarts with fresh context in each iteration, reading filesystem state and tests to decide what to fix next. It sounds simple because it is. But the implications are profound.
For greenfield work (new projects, clean slate), the unit economics have inverted. The marginal cost of labor now approaches compute costs, not human salaries. This means outsourcing firms' traditional pricing model is broken for this class of work.
What this means for your Build vs. Buy strategy:
- In-source greenfield projects. One senior engineer + discipline (strong types, test-first spec) = synthetic team executing 24/7
- Your role shifts from "I write every line" to "I define what done looks like" (acceptance criteria, tests, architecture)
- If you're buying, renegotiate contracts. If you're selling, expect fixed-price or outcome-based models
- If you're not outsourcing today, you won't be tempted to tomorrow
The real insight: Ralph isn't clever. The workflow is disciplined. Strong type systems, clear specs, executable tests: these become your interface to a relentless, low-cost team.
Brownfield work? Legacy systems? That's a different conversation. But greenfield? The economics have permanently changed.
What's your experience with agentic loops in production?