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6 results for “prompt engineering”
The Google Bug Hunters Team admitted to me that they cannot fundamentally patch prompt engineering bypasses in Gemini
An anonymous Reddit user claims a Google engineer admitted Gemini's prompt engineering bypasses cannot be fundamentally patched, based on an unverified personal interaction and self-described 'deep techniques' for evading safety controls.
Aug 6, 2026
Head Of Anthropic’s Claude Code Says Prompt Engineering Not That Important - Search Engine Journal
Anthropic's head of Claude code publicly downplays the importance of prompt engineering, positioning it as a diminishing skill in favor of more automated or model-internalized capabilities.
Jul 30, 2026
Knowledge Injection Exists in MoE? Exploring Expert-Aware Contrast Decoding in MoE for Mitigating LLMs'Hallucinations
Researchers propose EAACD, a new contrastive decoding method tailored for mixture-of-experts (MoE) LLMs that leverages expert activation differences in higher layers to reduce hallucinations on QA tasks, outperforming baselines across four datasets.
Jul 24, 2026
Karpathy says his favorite LLM workflow is just "a nice long ramble session." Glad to know my unhinged voice notes are officially peak prompt engineering.
A Reddit post quotes Andrej Karpathy describing informal, unstructured 'ramble sessions' as his preferred LLM workflow, sparking community validation of nontraditional prompt engineering practices.
Jul 23, 2026
Will the future of AI-assisted art/video depend on prompting skills or just who can afford more tokens.
A Reddit forum post questions whether prompt engineering skill will remain a meaningful differentiator in AI-assisted art/video creation as rising token costs and compute intensity shift competitive advantage toward financial capacity rather than technical or creative ability.
Jul 22, 2026
Post-Generation Curation of Synthetic Images via Homogeneous-Heterogeneous Splitting
A new method called Homogeneous-Heterogeneous Splitting improves synthetic image utility by selecting subsets based on fidelity and diversity, without retraining generators, achieving real-data-level performance with up to 40% fewer samples.
Jul 8, 2026