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Wuthering Waves characters are seriously way too gorgeous >"< My closet is basically turning into Wuthering Waves at this point 📷 This month’s rewards feature the youthful and charming Linai ✨ Only 5 days left—don’t miss your chance to collect her~ 鳴潮的角色真的都香到不行>"< 衣櫃要變成鳴潮的樣子了📷 這個月的獎勵有青春滿滿的琳奈哦！ 剩下5天還可以收藏收藏~ #鳴潮# #琳奈# #WutheringWaves# #Linai# #Cos#

Jensen Huang, le CEO et co-fondateur de Nvidia, vient de démissionner parce qu’on lui a découvert deux liaisons extra-conjugales avec des femmes adultes et consentantes. Pendant ce temps, les pédophiles, violeurs et cannibales du réseau Epstein restent confortablement en poste. Elle est pas belle, la vie?

Liebe chinesen Ich habe drei Tage und drei Nächte lang darüber nachgedacht, ich konnte es nicht lösen, Dieser bewaffnete Angriff in Hangzhou Linping Warum machen sie nicht gute Nachrichten, Was gibt es darin zu verbergen, Haben die Menschen nicht das Recht, Informationen zu erhalten?

That’s Like This! 🤷🏾‍♂️💬 Watch 📲: YouTube (Episode 95 LinkInBio) Audio 🎧: Spotify • Apple Podcasts • Amazon Music 💬 #CultureChatGPT# #CCGPT# #Podcast# #Fyp# #ForYou# 😎💬 @TheRealBL @cheismack @TheDonMcghee 💬

I've been working on a skill that makes better HTML plans in Claude Code. It uses simple language, shows code snippets, surfaces questions & makes mockups. Linting reduces the normal failure cases that Claude runs into. Would love your feedback before shipping more broadly!

Learn Harness Engineering from scratch! This repo is a full learning path around harness engineering, with 14 lectures, 8 projects, reusable templates, and hands-on exercises. The course focuses on the environment around coding agents and how that environment affects whether an agent can reliably work inside a real repository across longer tasks and multiple sessions. It starts with the fundamentals of harness engineering and gradually gets into things like repository structure, persistent state, task boundaries, verification, observability, session handoffs, automated loops, and graph engineering. A harness in this context has five core parts: - Instructions that tell the agent how to work inside the repo - State that persists progress across sessions - Verification through tests, linting, type checks, and full-pipeline runs - Scope controls that keep the agent focused on one task at a time - Session lifecycle so every run starts and ends in a usable state The projects are also connected rather than being isolated examples. You keep working on the same Electron-based knowledge app while gradually improving the harness around it. You start by comparing prompt-only vs. rules-first agents, then build multi-session continuity, runtime feedback, verification, a complete harness, automated maker-checker loops, and eventually represent the workflow as a graph with parallel execution, rollback, and human approval. What I like is that you can actually take parts of the repo and use them directly in your own projects. There are templates for things like "AGENTS. md", "init. sh", feature lists, progress tracking, loop state, maker-checker prompts, and a "harness-creator" skill that can scaffold the basic harness structure for an existing project. The repo also covers the progression from a single agent loop to graph engineering, including when you actually need nodes, shared state, routing, parallelism, and recovery instead of forcing everything into one loop. A solid resource if you're working with coding agents and want to understand the engineering around making them reliable over longer tasks. 100% open source

Doing a bit of a self-experiment. Goal: use my personal health and travel data to provide personalized diet and exercise recommendations for me, using frontier models but in a way that avoids leaking to them any private information. Strategy: use a local model (Qwen 3.8 Flash Next) to orchestrate, and use powerful remote models as a tool call to benefit from higher-level thinking and knowledge that the local model does not have. Three-layer approach to privacy: Avoid leaking personally identifiable information, or leaking my identity through writing style -> local model writes the queries to the frontier model, not me Avoid leaking who I am through the payment channel -> zkAPI Avoid leaking who I am through networking / IP -> Tor You need all three (and finally we have all three, at least to some extent) A skill file teaches the local model when and how to construct minimally-data-revealing requests to remote models. Use zkAPI-wrapped-with-Tor as a CLI tool. And everything works! I got the recommendations back, info from frontier models helped to improve them. Main deficiencies: * Tor is really not optimized for request-by-request de-linking, which is the only form of network-layer privacy that really makes sense in today's world (long-running identifiers are too fragile). Probably not private enough, and latency 10-100x higher than it could be, at the same time. * The skill file's request construction strategies are definitely far from optimal. * Qwen 3.8 Flash Next is still too slow for comfort. It's comfortably running at 20-30 TPS, but it would only really start to feel fast at 100+ * There is a tradeoff: the more careful you are about what data you give to a remote model, the less it can help you

@Diistortiionxx Ur point is irrelevant. I cosplayed Remielle because I genuinely enjoy her character design/zzz. Me linking my stats was me showing it went beyond “seeking male approval” gg go next