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This experiment demonstrates that structured specifications significantly enhance AI-assisted code porting, with smaller models often outperforming larger ones in efficiency while adhering strictly to defined constraints. The findings highlight a critical trade-off between token consumption and implementation quality, suggesting that precise context management is more vital than raw model scale for automated software modernization workflows.

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Akka Tests Spec-Driven AI Delivery across 65 Open Source Projects

InfoQOctober 5, 20262 min read

Akka used 65 open-source projects to examine how specification structure, context, model selection, automated validation, and delivery guardrails affect AI assisted software porting. The experiment measured time, token use, code size, test parity, and performance, finding substantial variation across models, effort levels, and project types. By Leela Kumili

Akka used 65 open source projects to test a spec driven workflow for AI assisted software porting, measuring specification structure, context, model and effort selection, automated validation, token consumption, and runtime performance. The initial tranche took 99.3 hours and consumed 9.41 billion tokens,…

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