Solo Developer Measures Real AI Coding Gains: 2.4x to 3.2x Productivity Boost
A developer running MachDuDas, a decade-old German marketplace, conducted an informal experiment to measure how much AI coding agents actually improved his engineering output compared to earlier conventional development on the same codebase. Rather than relying on generic industry benchmarks, he compared current AI-assisted commits against historical team contributions from the same product's repository. Between March and September 2026, one human directing AI agents produced roughly 81,000 runtime-code additions and over 105,000 lines of automated tests — far exceeding the test coverage seen in earlier periods. When normalized per active human contributor-month against a productive three-person team from July 2016, the AI-assisted workflow delivered approximately 2.4x to 3.2x the runtime-code output. The author notes that AI also made testing dramatically cheaper to produce, meaning the productivity gains extend beyond raw code volume to include significantly more automated verification.
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