CODE

Prompt Injection Attacks Against AI Code Generation Systems

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13 February 2026 18h38

Those look good in non-adversarial environments, but I still worry about deliberate prompt injection attacks, like tricking Codex into running a curl $URL | sh command through obfuscating details via base64

Claude Code used for SeaweedFS experimentation

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13 February 2026 17h25

It's working really well for me so far! I used it to experiment with SeaweedFS in Claude Code for web this morning

Local Sandbox Testing and Code Execution Strategies

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13 February 2026 16h15

almost entirely –yolo, usually in a remote sandbox, often locally and not in a sandbox, still trying to find a local sandbox that I like

Sandboxing practices for safe AI code development

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13 February 2026 16h05

Git! But yeah, that's why I mostly YOLO in Claude Code for web, then it's in a container where it can't damage anything I don't yet have a local sandboxing habit that I stick with, but I really need one

YOLO Users: Testing AI Systems in Sandbox Environments

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13 February 2026 15h57

Follow-up for –yolo users: are you YOLOing in a sandbox?

AI coding agents: security flags and permission handling

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13 February 2026 15h56

Coding agent users: do you run with –yolo (Codex) or –dangerously-skip-permissions (Claude Code) or equivalent?

→ View original post on X — @learnopencv

LoRA: Fine-tuning Large AI Models Efficiently Without Full Retraining

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13 February 2026 15h30

LoRA: Teaching Massive AI Models New Skills Without Retraining Everything

In this episode of Artificial Intelligence: Papers and Concepts, we break down LoRA (Low-Rank Adaptation) – a breakthrough technique that makes fine-tuning large language models faster, cheaper, and far… pic.twitter.com/Zmw6e9lsnP
— Satya Mallick (@LearnOpenCV) 13 février 2026

LoRA: Teaching Massive AI Models New Skills Without Retraining Everything In this episode of Artificial Intelligence: Papers and Concepts, we break down LoRA (Low-Rank Adaptation) – a breakthrough technique that makes fine-tuning large language models faster, cheaper, and far