arcraiderlover retweeted
รู้สึกว่าต้นทุนของผู้หญิงที่อยากมีตัวตนบนโซเชี่ยลยุคนี้มันสูงมาก และกลายเป็นแพทเทิร์นเดียวกันหมด มีรูปกินร้านหรู รูปมุมฮิตในคาเฟ่ รูปเที่ยวตปท. ถึงเทศกาลอะไรก็ต้องแต่งตัวให้เข้าแล้วโพสรูป
ไม่ได้มีปัญหาอะไรกับผญ.ที่ทำแบบนี้นะ แต่เห็นใจผู้หญิงอีกหลายคนที่พยายามจะทำตามจนแทบไม่เป็นตัวของตัวเอง และอยากพูดในฐานะผู้ชายว่า จริงๆ เสน่ห์ของผญมันมีหลายด้านมากๆ โดยเฉพาะความเป็นตัวของตัวเอง ไม่จำเป็นต้องดูหรู ดูแพงอย่างเดียวก็สร้างคุณค่าตัวเองได้ แถมยังดูแตกต่างด้วย
arcraiderlover retweeted
มาก รำคาญ gender role อิเหี้ย กุขอ-โทษ tiktok ที่เผยแพร่แนวคิดเหี้ยนี่ จนคนมองว่ามันปกติ สเปคมีได้ แต่เอาคุณค่าของตัวเองไปผุกไว้กับการเลี้ยงข้าวของผุ้ชายจนพาลมาเป็นพวก toxic princess treatment นี่ไม่ไหวจริง คนแบบนี้น่ารำคาญไม่ต่างกับชายแท้
arcraiderlover retweeted
กุไม่เข้าใจว่าเพศกุจะผูกคุณค่าที่ไว้การเลี้ยงข้าวทำไม มึงบ้าปะเนี่ย เชื่อกันเป็นตุเป็นตะว่าถ้ามีค่ามากพอ ผชจะไม่ขอหาร รำคาน เมื่อไหร่จะเลิกยัดเยียดบทบาททางเพศ
arcraiderlover retweeted
Ran the numbers on the plan changes for Codex, looking pretty good!
$500 plan nets to ~$10.5k/month of usage
$200 plan nets to ~$4.3k/month of usage
arcraiderlover retweeted
Literally what the fuck was going on here
i expanded the neuron persona library to 180,000+ personas across 9 models :)
there is genuinely so much new wild stuff in here; please help me find more!
neuronpersonas.com
arcraiderlover retweeted
Run UNCENSORED LFM3-1.7B locally 🔥
Our Atomic Dynamic GGUFs come in 1.1 GB and 1.6 GB
Refusals dropped from 61.7% to 0% with no accuracy loss
Get quants here 👇
huggingface.co/AtomicChat/LF…
Introducing 𝙻𝙵𝙼𝟹: our new generation of Liquid Foundation Models. With a new tri-hybrid architecture and new multimodal encoders, the LFM3 family is the ideal model suite for specialized intelligence.
> 6 model instances, across text, audio, vision, and omni modalities, generative and decision models.
> 𝙻𝙵𝙼𝟹-𝟷.𝟽𝙱: text, 256k context window.
> 𝙻𝙵𝙼𝟹-𝚅𝙻-𝟸𝙱: vision-language model with video-input support for spatial understanding
> 𝙻𝙵𝙼𝟹-𝙰𝚞𝚍𝚒𝚘-𝟸𝙱: tool calls, voice chat, reasoning in 18 languages.
> 𝙻𝙵𝙼𝟹-𝙾𝚖𝚗𝚒-𝟸𝙱: an omni model combines vision, audio, and language.
> 𝚍𝟷-𝟸𝙱 and 𝚍𝟷-𝙾𝚖𝚗𝚒-𝟸𝙱: decision models with typed outputs and calibrated probabilities in a single pass. Omni adds audio input.
> fine-tune on 1 GPU.
> a new tri-hybrid architecture
> architecture optimized for 14 processor classes across GPUs, CPUs, and NPUs.
> 𝙻𝙵𝙼𝟹-𝚅𝙻-𝟸𝙱 is a beast. It performs competitively with Gemma 4 12B (6x larger), and Gemini 3.5 Flash Lite, and GPT-5.6 Luna, with 1.9B parameters.
> 𝙻𝙵𝙼𝟹-𝟷.𝟽𝙱 is #1 on the Pareto frontier of device intelligence 𝚙𝚒𝚙𝚎𝚝𝚝𝚎.𝚕𝚒𝚚𝚞𝚒𝚍.𝚊𝚒
Every modality for specialized intelligence. Pick the one that fits your use case, customize it, and run it on-device.
1/ 🧵
Why do people expect so much from strangers, lol? In harmless, non-life-threatening or non-emergency situations, people would rather do nothing because of the risk that can come with it. People should learn to depend on themselves and not expecting of others.
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arcraiderlover retweeted
i'm begging you to paste this into Claude Code before your next session.
it checks your whole setup and plugs the 5 leaks quietly draining your Opus 5.5 tokens, without touching output quality.
every one of the 10 leaks is broken down in the article.
steal the prompt before your next bill does:
arcraiderlover retweeted
The most annoying issue with current agentic models is their hygiene.
The way they pollute the system environment, don't rotate logs, archives and dumps, install packages uncontrollably, etc., really shows how they were trained in throwaway VMs and it really affects usability.
arcraiderlover retweeted
holy f*ck
Grok Bot (@bot) engineer Lauren Tan showed her pstack setup for coding agents:
request → /poteto-mode → playbook → targeted skills → verification
30 selected skills handle execution. 24 principle references guide design decisions, code quality and failure handling:
→ 5 startup skills
/poteto-mode - routes the task
/poteto-help - explains commands and workflows
/setup-pstack - configures models and reasoning budget
/in-your-own-words - restates the goal before execution
/sharpen - strengthens the prompt’s methods and verification
→ 6 context skills
/how - traces implementation
/why - investigates design rationale
/teach - connects mechanics with reasoning
/recall - restores relevant prior context
/ketchup - summarizes chat progress and pending decisions
/bro - restates the last message without jargon
→ 4 design skills
/architect - defines interfaces, types and boundaries
/arena - compares solutions to the same problem
/swarm - distributes separate work slices
/figure-it-out - designs a playbook when existing ones don’t fit
→ 7 verification skills
/interrogate - challenges the diff across models
/tdd - writes a failing test before the fix
/benchmark-checklist - checks measurement validity
/create-verification-skill - builds runtime checks and a feature map
/maintain-verification-skill - updates verification as the app changes
/blast-radius - examines impact beyond the diff
/show-me-your-work - records a reviewable decision trail
→ 3 writing skills
/unslop - removes generic AI prose
/technical-writing - structures technical documentation
/no-comments - reviews comments and applies accepted fixes
→ 5 improvement skills
/automate-me - derives a personal mode from work history
/reflect - captures completed-work lessons as skill updates
/correct - turns recurring mistakes into constraints
/make-bot-ui - builds interfaces that trigger Grok Bot through webhooks
/typescript-best-practices - applies TypeScript type-system practices
+ 24 engineering principles
cover domain modeling, module boundaries, idempotent operations, behavior-based tests, context management and encoding lessons into project structure
Give the router a checkable finish condition:
/poteto-mode
> reproduce the failure in the running app
> define the observable success condition
> make the smallest justified fix and repeat the check
> return the diff, verification commands, results and blockers
the playbook selects the skills. the completion check determines whether the task is done
Save this before building another agent workflow from scratch ↓
arcraiderlover retweeted
So uh...I guess it's time to announce tstack? I caved. I am publishing my skills now.
arcraiderlover retweeted
Top open weights models for Cyber - updated list
based on our experience
DeepSeek V4.1 Flash 1017 is insane value.
arcraiderlover retweeted
We’re excited to announce our new CapCut plugin is coming soon to @ChatGPT at CapCutWorldLA.
The plugin brings CapCut's video editing and generation tools alongside ChatGPT. You can start with an idea in ChatGPT, bring it to life with the CapCut plugin right inside ChatGPT, then take your draft video to CapCut's web editor to refine, share and publish.
By bringing the CapCut product you already love and use in ChatGPT, we're making content creation more seamless and efficient.






































