AI & ML
Toward Methods and Tools for Critical Examination of Disparate Systems for Discovery of Hidden Dependencies in Engineering of Autonomous and Semi-Autonomous Systems
arXiv cs.SE0 views
arXiv:2610.34974v1 Announce Type: new Abstract: We present a methodology, an initial AI Skill package, and emerging results, for enhancing software engineers' acquisition and application of domain knowledge and system-wide engineering perspectives towards the development of an autonomous or semi-autonomous system in a domain that may be new to them. At the core of the approach is a process involving proactive adversarial critiquing of videos of disparate systems in related environments. Among other things, the engineers and automated AI tools look for interactions, dependencies, and environment assumptions manifested in the observed systems, which are applicable also to the target system, but that otherwise might remain unarticulated in project artifacts. The approach and its supporting tools can enhance the quality of the target system, the individual engineer's skills and the organization's engineering practices.
Source:https://arxiv.org/abs/2610.34974PreviousRivet: Utility-Preserving Context Control for Repository-Level Coding AgentsNextV$^3$AST-Bench: Verifiable, Valid, and Versatile Safety Evaluation for Coding Agents
Related posts

The Download: the agentic web arrives and the drive for safer roads
0MIT Technology Review

Stop counting tokens, start counting what ships
0MIT Technology Review
OpenAI is finally merging ChatGPT’s chat and Work tabs
0TechCrunch

10 Open-Source Robotics Repositories for 3D Perception, VLA Policies, and Sensor Calibration
0dev.to
My self-modifying system tried to wire a gate-passing module into its own protection enforcer. It was refused three times.
0dev.to
Last night an AI agent performed brain surgery on a mouse
0Hacker News