imtiaz wazir

[Bryän @bryanonchain]

AI agent kamu nulis 80 baris code buat yang sebenarnya cuma butuh 1 baris?

Kenalan sama Ponytail plugin yang bikin AI coding agent berpikir seperti laziest senior dev di dunia.

"The best code is the code you never wrote."

Cara kerjanya:
1. Cek dulu: Apakah ini perlu? (YAGNI)
2. Sudah ada di stdlib?
3. Ada native feature di platform?
4. Sudah ada di dependency?
5. Bisa 1 baris?
6. Baru nulis code minimal

Hasil benchmark:
• 80–94% less code
• 47–77% cheaper
• 3–6× faster

Contoh:
❌ Agent nulis full date picker + library + wrapper + logic
✅ Ponytail: <input type="date"> <!-- ponytail: browser has one -->

Support: Hermes,Claude Code, Codex, Cursor, Antigravity, Pi Agent, OpenCode, dll.

Repo: https://t.co/EiEtlH22R9

Pasang sekarang & rasain bedanya. Agent kamu bakal jauh lebih "senior" (dan males nulis code berlebihan) 😂

Kamu sering kesal AI agent over-engineering?

Comment pengalamanmu 👇

[Hiroki Osame @privatenumbr]

If you work with images with text, or scanned documents, here's a small but powerful OCR CLI

It leverages Apple's Vision Framework so it's completely local

Tip: give it to your agent to save on vision tokens!

→ npx mac-ocr ./image.png

https://t.co/8Ig3Vc4kXk

[Bjarne Øverli @iamdothash]

I've used Kubernetes for years, and it was time to make the TUI suitable for me. Inspired by k9s and lens.

Here is kli.

[Chrome @0xchromium]

Andrej Karpathy spent 2h showing how he actually uses AI day to day

he's a co-founder of OpenAI and led AI at Tesla, so when he shows how he works, it’s worth watching

and the whole session is just him telling the machine what he wants in simple terms, like he's briefing a coworker

watch what's actually happening the entire time:

> he describes the task in normal words
> it goes off and does the work
> he glances at the result and nudges it with one more sentence

that's the whole skill, and you've had it since you learned to talk

the only gap between that and a worker that runs on its own is handing that sentence a schedule and the tools to act

check his work, then build the version that keeps working when you stop

[Alok @analogalok]

Run Gemma 4 26B MoE on 8GB VRAM with 250k context at 20+ tokens/sec

If you own any 8GB VRAM graphics card, stop what you are doing. Local AI just had its absolute "Holy Shit" moment for budget hardware.

Yesterday, I benchmarked Unsloth Gemma 4 12B Q4_K_XL on an 8GB card.

The community went wild but immediately demanded more: "Can we run a 25B+ model on budget GPUs?"

Today, I’m delivering exactly that.

I am running a massive 26B parameter Mixture of Experts (MoE) model locally on a standard 8GB VRAM setup with 250k full native context!.

If you own an RTX 3060, 3070, 4060, or any budget GPU with 8GB of VRAM, the local AI paradigm has completely changed.

The performance metrics are astonishing:

- 20 tokens/sec flat decode throughput.
- Stable, flat decode speed even with massive prompts.
- I threw a 60k token prompt at it, and it still clocked in at 20 TPS without dropping a single frame.

# What about prefill?

Yes, Time To First Token (TTFT) is slightly high when swallowing massive contexts. But with a solid 200 tokens/sec prefill speed, the wait is barely noticeable and highly usable.

And this is running completely without Multi Token Prediction (MTP) active.

How is this possible? It’s the magic of Google's new QAT (Quantization Aware Training) quants for Gemma 4.

The model weight file (unsloth gemma-4-26B-A4B-it-qat-UD-Q4_K_XL.gguf) is only 13.2 GB, making it the ultimate local powerhouse.

# The Test Setup:

CPU: Intel Core i7

RAM: 16GB System RAM

GPU: NVIDIA GeForce RTX 4060 Laptop GPU (8GB VRAM)

# The Secret Sauce (The -cmoe Flag)

To make this work properly on any 8GB card, you must use the -cmoe (CPU MoE) flag in llama.cpp.

This flag isolates the heavy MoE expert weights directly to system memory (CPU/RAM) while letting your GPU focus strictly on the Attention layers and the KV Cache.

It prevents VRAM spillage and holds the throughput rock solid.

# The flags:

-m "gemma-4-26B-A4B-it-qat-UD-Q4_K_XL.gguf" -cmoe -c 248000 -v

Once running, just open the UI on localhost and toggle the new reasoning lightbulb icon in the text input box to watch the model perform multi step thinking.

Are you still running smaller models, or are you ready to scale up your budget local setups? Let's discuss in the replies

[Ali Grids @AliGrids]

this inline table editing interaction is buttery smooth @nitishkmrk

[yui540 @yui540]

CSSアニメーションのコツ（？）的な動画も投稿しているのでご覧いただけたら嬉しいです。
https://t.co/Rh4JVJq3pH

[maxwell neely-cohen @maxnc]

Issue Five of The HTML Review is here!
Get to your browser for 15 excellent new pieces of web-based literature and art

[Balint Orosz @balintorosz]

Beautiful Mermiad is now 1.0. Huge updates on reliability in terms of rendering. Will continue to iron out edge cases - but layout logic is a lot more reliable, and capabilities extended a lot. https://t.co/zXOgaMl7f3

[Antoine v.d. SwiftLee  @twannl]

🥇 SwiftUI Agent Skill: Build better views with AI
https://t.co/h3MsgwcCzU

🥈 Swift Testing Agent Skill: Write high quality tests with AI
https://t.co/QxbwSfI2Zb

🥉 Agent Skills explained: Replacing https://t.co/KrUavQJdcG with r...
https://t.co/31mQMuxPMG

#swiftlang #swiftlee

[Framer 🇱🇹 @Framer_X]

This tool is insane.

Upload any image.
Move camera in 3D space.
And get a completely new camera angle 🤯

Also it’s free! 👇

[Simplifying AI @simplifyinAI]

Docker for AI Agents is officially over..

Pydantic just dropped Monty. It's a python interpreter written in rust that lets agents run code safely in microseconds.

no containers. no sandboxes. no latency.

100% open source.

[Tom Dörr @tom_doerr]

Visualizes transformer operations in the browser

https://t.co/BxUuXBt29N

[NorthStar AI @namjaichun8599]

@bibryam Hint: NCAF + PCM

[dmytro @pqoqubbw]

you can finally remember the name

introducing lucide-animated - a new name, a fresh look, and the same animated icons

the new website is live - come take a look!
https://t.co/01LktIPnqK

[Duy /zuey/ @goon_nguyen]

good bye clean my mac app
https://t.co/thCmDr4oet

[Itsuki @itsuki68391179]

I just published SwiftUI: Pair BLE Accessory in an Easy BUT Secure Way!
- No need to implement authorization, not need to handle TCC, no need to request Bluetooth permission! But still privacy-preserving and secure!
#swiftui #iosdev
https://t.co/PJRuZR8cO5

[Jose @josesaezmerino]

Just shipped Swift Anim 1.0.1
- Animation curves and descriptions in a popup, with immediate feedback
- See the actual curves when comparing side by side or stacked

Get it now: https://t.co/4uFhyGxOvA

[Richard Seroter @rseroter]

"Agent engineering is the iterative process of refining non-deterministic LLM systems into reliable production experiences. It is a cyclical process: build, test, ship, observe, refine, repeat." https://t.co/MLGvQLNHzN &lt; good post from @langchain

[Rudrank Riyam @rudrank]

New release of FoundationModelsKit!

https://t.co/RuWSHSBwN2