Try it on your own small model. It is free. Inspired by MIT CSAIL researchers' Weight-Space Programming blog post (Nov 2, 2026): https://t.co/TEu1izfwyS . Not affiliated with MIT. #LocalLLM
76.11 to 85.56. One small AI model. 129,897 numbers changed. No retraining. WSP-Kit (Weight-Space Programming Kit) did it. 5 of 7 real tries failed and shipped nothing. 16 GitHub stars so far. #SmolLM
Your one star encourages our team to keep building incredible things — free for everyone — and to grow this community. Send this to one friend who works with AI models. https://t.co/TNcp30BaAg https://t.co/1wNAJ9HUbs
Your AI-built app can work and still leak user data.
In Supabase, turn on Row Level Security (RLS) for every table. Without it, anyone with your app's public key may read or change that table.
Then test as a normal user. Is RLS on for all your tables? #VibeCoding#AppSecurity
939 clones in the last 14 days. Clones are not people.
Inspired by MIT CSAIL researchers' Weight-Space Programming blog post (Nov 2, 2026): https://t.co/TEu1izeYJk Not peer-reviewed. Not affiliated with MIT. Credit and inspiration: @lateinteraction
One tiny AI model: 37.78 to 67.22 on one test. Here is the catch.
WSP-Kit (Weight-Space Programming Kit) changed 0.022% of its numbers. The test counts repeats twice, so the true gain is smaller.
5 of 7 tries failed and shipped nothing. #Qwen#SmallModels
Your one star encourages our team to keep building incredible things — free for everyone — and to grow this community.
Try it on your own small model. It is free. Send this to one friend who works with AI models.
https://t.co/TNcp30BaAg https://t.co/1wNAJ9HUbs
One tiny AI model: 37.78 to 67.22 on one test. Here is the catch.
WSP-Kit (Weight-Space Programming Kit) changed 0.022% of its numbers. The test counts repeats twice, so the true gain is smaller.
5 of 7 tries failed and shipped nothing. #Qwen#SmallModels
A vague bug report gets expensive fast.
"Login is broken" = hours of guessing.
Send 4 things: what you clicked, what you expected, what happened (paste the exact error), and a screenshot.
What do you forget most? #VibeCoding#AIApps
Inspired by MIT CSAIL researchers' Weight-Space Programming blog post (Nov 2, 2026): https://t.co/TEu1izfwyS Not peer-reviewed. Not affiliated with MIT. Credit and inspiration: @a1zhang@rikiyatakehi
Four questions. Then your small AI model gets a fix.
WSP-Kit (Weight-Space Programming Kit) has an easy mode. Type "wsp auto", answer 4 questions, and it runs by itself.
5 of 7 real tries failed and shipped nothing. That is on purpose. #LocalLLM#ModelEditing
Your one star encourages our team to keep building incredible things — free for everyone — and to grow this community.
Try it on your own small model. It is free. Send this to one friend who works with AI models.
https://t.co/TNcp30ACKI https://t.co/1wNAJ9HmlU
Inspired by MIT CSAIL researchers' Weight-Space Programming blog post (Nov 2, 2026). Not peer-reviewed. Not affiliated with MIT. https://t.co/TEu1izeYJk
Can you fix a small AI model without retraining it?
WSP-Kit (Weight-Space Programming Kit) changes a few numbers inside it. 5 of 7 real tries failed our safety check and shipped nothing.
816 clones in the last 14 days. Clones are not people. #SmallModels#LLM
Your one star encourages our team to keep building incredible things — free for everyone — and to grow this community.
Try it on your own small model. It is free. Send this to one friend who works with AI models.
https://t.co/TNcp30BaAg https://t.co/1wNAJ9HUbs
Building your app with AI takes a weekend. Fixing it when it breaks can take your whole week.
Tell ORA what's wrong in plain English and it fixes your GitHub code after you approve. Works when your app's code is on GitHub.
Who fixes yours today? #VibeCoding#AIApps
Your one star encourages our team to keep building incredible things — free for everyone — and to grow this community. Please share this with a builder you know. https://t.co/TNcp30ACKI #WeightSpaceProgramming
Qwen3-0.6B, narrow animals task. Before: 37.78. After: 67.22. We edited 0.022% of its weights (131,072). No retraining. Repeat answers are counted separately by the scorer, so the true gain is a bit smaller. #SmallModels#OpenSource