So impressed with the Opus 5.5 explainer videos - Here's another one - Serve Models from a @Kit_Ops ModelKit on @HAMiProject Detailed explanation of how Your model is packaged as a versioned ModelKit. KitOps pulls it from an OCI registry and unpacks it inside the Pod. HAMi schedules a controlled GPU share. SGLang loads the model locally and serves an OpenAI-compatible API. One clear path from model artifact to working inference. KitOps and HAMi.

Here's an video introduction to @tan_stack AI using a single prompt to generate a launch style video about Tanstack UI using @ClaudeDevs Opus 5.5 using @Remotion Prompt shared below 👇

I built WearScout because I kept seeing great outfits and spending way too long searching for similar clothes online 👕 Give it a reference image, it uses @deepseek_ai v4.1 Flash via @nebiustf to describe the look, and Jev drives a real browser using @browser_use to find similar pieces across stores, check product pages, and return a shortlist with prices and links. I tried it with a Tom Cruise outfit. I made a wrong call on privacy with my first demo, so I took that post down and changed the example. Heavily inspired by and adapted from @_nancychauhans’ Hearth project 🙌

@farisaziz12 @ReactAlicante

this is great, you can run it with @nebiustf TF Relay now - nebius-tf-relay.vercel.app/

@_nancychauhan @mritunjay394 @deepseek_ai @nebiustf @typesafeai

I built a very similar 3d world like GTA Style Gameplay UI andcompared @xai @grok 4.7 against Fable 5.1, Kimi K3, and GLM 5.3 Flash and pretty surprising to see how cost efficient Grok 4.7 is. While the UI levels / 3d artifacts don't match levels of Fable 5.1, it is significantly cheaper to run.

Got hands on with @arduino Ventuno Q - time for some on device VLM model inference 🎉 with @Qualcomm_Dev Hexagon NPU inference

I got early access to the new @Cline Open Source Desktop app! I wanted to see how it would fit into my everyday development workflow, so I tested it with the free GLM-5.3 Flash model across coding, scheduled reviews, and conversation handoffs. For the coding task, I asked Cline to build a small Node.js task-list CLI with persistence and tests. After resolving an initial environment issue and fixing how the CLI handled corrupted JSON, it successfully passed all 15 tests. But scheduling was the feature that stood out most. I scheduled a background review of the code and documentation. Cline compared the README with the actual implementation and caught a genuine data-loss risk: a corrupted file could be interpreted as an empty task list and later overwritten. That is the kind of work I don’t want to repeatedly remember to do myself. Overall, the foundation feels promising. The interface makes the agent’s plan and execution visible, scheduled tasks can remove repetitive work from the development loop, and importing work from another coding agent opens up some interesting workflows. Here’s my complete experience with the app 👇

Another guide with @rudrakshkarpe also in the works using @Kit_Ops to serve models with modelkits and serve them using @HAMiProject thus providing a safe way to securely get signed models with verifiable identity github.com/Project-HAMi/webs…