UA-ChatDev: Uncertainty-Aware Multi-Agent Collaboration for Reliable Software Development
Academic proposal for uncertainty-aware multi-agent collaboration to make AI-driven software development more reliable.
3 items · 3 sources · 3 days
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Anthropic's Deputy CISO published how its Security Engineering team secures a software development lifecycle where AI now authors 80% of merged code — the thread's first concrete production account, following two earlier research/industry reliability proposals.
Academic and industry work through early July proposed uncertainty-aware and multi-agent approaches to make AI-driven software development more reliable and controllable. By Jul 21, Anthropic detailed how it secures a real production pipeline where AI now authors 80% of merged code.
Arc
Academic proposal for uncertainty-aware multi-agent collaboration to make AI-driven software development more reliable.
Industry presentation argues for adaptive multi-agent systems over simple autocomplete to break the AI productivity ceiling.
Anthropic's Deputy CISO details how Security Engineering secures an SDLC where AI authors 80% of merged code.
Academic proposal for uncertainty-aware multi-agent collaboration to make AI-driven software development more reliable.
Industry presentation argues for adaptive multi-agent systems over simple autocomplete to break the AI productivity ceiling.
Anthropic's Deputy CISO details how Security Engineering secures an SDLC where AI authors 80% of merged code.
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