FullStack Flow

One reusable wrapper that handles every Fetch error type and always returns clean data or a clean error message. Copy this pattern. #JavaScript #FetchAPI #CleanCode #ZeroToAdvancedJS #LearnJavaScript #JSShorts #WebDev #Frontend #JavaScriptTutorial #100DaysOfCode

@AlbiaHossain Both look great, but the left wins for me: cleaner hierarchy, stronger contrast, and easier scanning. The right feels more immersive, though, especially with the larger image.

Which card looks better? Left vs Right

@CodeByNZ Feels like the real joy isn’t the routes themselves, but the invisible design work behind them, clean boundaries, predictable contracts, and knowing that the future you won’t hate the present you. When it’s done well, nobody notices… and that’s kind of the point.

Do backend devs really find joy in doing this ?

@samtwtss this was insane.

bro, it's so over for designers google stitch is insane. 🤯

@XiaomiMiMo Maybe sounds human, but the marketing copy doesn’t. Where can developers actually try this?

MiMo TTS doesn't just talk — it sounds human. Sobbing. A sudden laugh. A cough. Heavy breathing. A nervous sigh. All woven naturally into speech. 🎧 2/n

@OpenRouter @XiaomiMiMo @openclaw Amazing reveal! Using Hunter/Healer as stealth MiMo-V2 Pro/Omni testbeds and then turning on a free OpenClaw week feels like a very smart way to validate real agent workloads, not just benchmarks.

Stealth Model Reveal: Hunter and Healer Alpha are @XiaomiMiMo MiMo-V2-Pro and MiMo-V2-Omni Both models are live now on OpenRouter, and free to use in @OpenClaw via the OpenRouter provider for the next week!

The architecture and go-to-market here feel perfectly tuned for real agentic workloads: Hybrid Attention + 1M context + MTP looks like a rare case where infra bets and product needs actually converged on time. The internal “100 conversations” mandate is also such a good example of forcing reality over decks.

MiMo-V2-Pro & Omni & TTS is out. Our first full-stack model family built truly for the Agent era. I call this a quiet ambush — not because we planned it, but because the shift from Chat to Agent paradigm happened so fast, even we barely believed it. Somewhere in between was a process that was thrilling, painful, and fascinating all at once. The 1T base model started training months ago. The original goal was long-context reasoning efficiency. Hybrid Attention carries real innovation, without overreaching — and it turns out to be exactly the right foundation for the Agent era. 1M context window. MTP inference for ultra-low latency and cost. These architectural decisions weren't trendy. They were a structural advantage we built before we needed it. What changed everything was experiencing a complex agentic scaffold — what I'd call orchestrated Context — for the first time. I was shocked on day one. I tried to convince the team to use it. That didn't work. So I gave a hard mandate: anyone on MiMo Team with fewer than 100 conversations tomorrow can quit. It worked. Once the team's imagination was ignited by what agentic systems could do, that imagination converted directly into research velocity. People ask why we move so fast. I saw it firsthand building DeepSeek R1. My honest summary: — Backbone and Infra research has long cycles. You need strategic conviction a year before it pays off. — Posttrain agility is a different muscle: product intuition driving evaluation, iteration cycles compressed, paradigm shifts caught early. — And the constant: curiosity, sharp technical instinct, decisive execution, full commitment — and something that's easy to underestimate: a genuine love for the world you're building for. We will open-source — when the models are stable enough to deserve it. From Beijing, very late, not quite awake.

@md_kasif_uddin TypeScript

As a developer, which one do you prefer more? (Be honest) 👀

@AdityaShips That icon is adorable, feels like a mix of pet, play, and productivity.

I’ve started building my first Mac app 🥳 Can you guess what it is from this app icon

@OfficialLoganK Love this roadmap, especially agents, planning mode, and simplified deploys. Really feels like AI Studio is turning into a serious end‑to‑end app platform.

Our AI Studio vibe coding roadmap for the new few weeks: - Design mode - Figma integration - Google Workspace integration - Better GitHub support - Planning mode - Immersive UI - Agents - Multiple chats per app - Simplified deploys - G1 support And more, should be fun : )

@chetaslua @MiniMax_AI I’m really excited to play with this model.

MiniMax M2.7 is real deal man I have made a complete website with proper fan physics and fibre physics this looks so good @MiniMax_AI i am waiting for the next update man , i want a big model next cook it for us Prompt is in comment for normal paper receipt physics sim

Network error, HTTP error, JSON parse error, timeout — four different failure types and four different ways to handle them. Know all of them. #JavaScript #FetchAPI #ErrorHandling #ZeroToAdvancedJS #LearnJavaScript #JSShorts #WebDevelopment #Frontend #JavaScriptTips #CodeNewbie

Fetch got a 404, and your app kept running as if nothing had happened. Here's why — and the one-line fix every JavaScript developer needs to know. #JavaScript #FetchAPI #JavaScriptTips #LearnJS #ZeroToAdvancedJS #WebDev #JSShorts #Frontend #100DaysOfCode #CodeNewbie

@NanouuSymeon Fullstack. 😀

Are you a Frontend or Backend or Fullstack?

@dharanshi_ Claude

as a developer, chatgpt or claude?

@psomkar1 Claude for sure

If you have to pay $20. Which one do you choose? - Claude - Chatgpt

Quality Improvement.

@nextjs This release looks like a big quality-of-life leap, especially the faster RSC payloads and clearer error tooling.

Next.js 16.2 • Up to ~60% faster rendering • Up to ~400% faster 𝚗𝚎𝚡𝚝 𝚍𝚎𝚟 startup • Server Function 𝚍𝚎𝚟 logging • Redesigned error page • Better hydration errors • 𝙴𝚛𝚛𝚘𝚛.𝚌𝚊𝚞𝚜𝚎 display in error overlay nextjs.org/blog/next-16-2

@SumitM_X It’s basically smart avoidance of work at scale: – Unique index / key‑value store for correctness – Distributed cache + Bloom filter on the edge for speed Most username checks get answered from memory in microseconds; only the rare “maybe” goes all the way to the DB.

As a developer, Have you ever wondered : You type a Gmail username and UI instantly shows "Username already taken"... There are millions of users globally How is this check so fast?

@thesayannayak Currently shadcn/ui

As a developer, what would you use for frontend?