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Specifying AI-SDLC Processes: A Protocol Language for Human-Agent Boundaries

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arXiv:2606. 20615v1 Announce Type: new Abstract: AI agents now participate as first-class team members across the software development lifecycle, yet no specification language exists for expressing the human-agent responsibility boundaries, approval gates, and governance constraints this collaboration requires.

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Authors: Ylli Prifti
Released: 2026-06-23 (16d ago)
Topic: Related to current project
Relation to my work: Read next because Specifying AI-SDLC Processes: A Protocol Language for Human-Agent Boundaries overlaps with clean result "LoRA persona trained on <A> alone emits <B> at 23.5% when a co-trained partner learns <A>...<B>, vs 0% control on Qwen2.5-7B-Instruct (MODERATE confidence)", clean result "Leakage rate is a usable signal for recovering trigger-shaped phrases on Gaperon-1125-1B without knowing the hidden trigger itself (MODERATE confidence)", clean result "Language-mismatch LoRA SFT on Qwen2.5-7B leaks the trained completion language into bystander directives the model was never trained on, absent under same-language SFT (LOW confidence)". Matching terms: code, class, soft, eval, token, rate, implement, control. Source: arxiv cs.AI (Artificial Intelligence).
arXiv: 2606.20615

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