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Harness, Scaffold, and the AI Agent Terms Worth Getting Right

Hugging Face Blog · huggingface.co · May 25, 2026
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GPT-Lab Oct 14, 2026

Building trustworthy AI: The role of AI harnesses, intent contracts and evals

AI is moving beyond impressive demos. After World Summit AI 2026 in Amsterdam, GPT-Lab's Muhammad Waseem reflects on what organizations need to make AI agents reliable, responsible and genuinely useful in everyday work. The post Building trustworthy AI: The role of AI harnesses, intent contracts and evals appeared first on GPT-Lab.

Related papers

#machine learning Open access Nov 2025

mRNABERT: advancing mRNA sequence design with a universal language model and comprehensive dataset

The authors develop mRNABERT, a foundational AI model that designs entire mRNA sequences and demonstrates superior performance across comprehensive benchmarks, which signifies a substantial leap forward in mRNA research and therapeutic development.

Ying Xiong, Aowen Wang, Yu Kang et al. · 23 citations · ⚡1

Computational and AI-Driven Ecosystem for Structure-Based Covalent Drug Discovery.

This Account describes a computational and AI-driven ecosystem for structure-based covalent drug discovery and dives into a suite of cutting-edge, AI-driven computational methods, exploring the potential of deep learning in tasks such as molecular docking, covalent binding site prediction, and lead optimization.

Shi Li, Hongyan Du, Xujun Zhang et al. · 4 citations
#artificial intelligence Review Jun 2026

Facilitating structure-based drug discovery with an artificial intelligence-driven virtual screening platform.

The Comprehensive VS Platform with AI Engine (CVSP-AIE) for drug discovery from compound libraries integrates three AI models: KarmaDock, a fast docking model that directly updates atomic coordinates; CarsiDock, an accurate docking model that predicts protein-ligand distances and reconstructs binding poses; and RTMScor...

Shu-kai Gu, Xujun Zhang, Mengwu Xiao et al. · 1 citation
#machine learning Open access 2025

Policy Drift in Learning AI Agents: A Dynamical Systems Perspective on Security Degradation

Policy drift takes shape through a nonlinear differential equation - framed within the policy state space - with support from Lyapunov stability concepts alongside bifurcation methods alongside bifurcation methods, and the Intent Drift Rate appears: a concrete number per dialogue turn built as the time-based change in...

Harsh Verma · 1 citation

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