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216 posts
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@zaccadev
head of tech | 24 | https://t.co/xMe0I3Nvbv
🇧🇷 Katılım Temmuz 2020
251 Takip Edilen45 Takipçiler
Seu código funciona perfeitamente… até você dizer: “olha isso aqui.” 😅
Português
@pranavcodes_ @SwaDotDev DON'T. I just migrated from the desktop app to the mobile version. ts is completely unusable.
English
@SwaDotDev Lmao, I was thinking about shifting to the desktop app
English
WhatsApp has the worst web opening experience ever
English
@obertobr @apogeudanoite exato, o interpretador mesmo foi feito em delphi (object pascal)
Português
@apogeudanoite Na real o intuito do portugol é muito mais parecido com pascal do que python
Português
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The Strait of Hormuz just became the biggest risk to global polyethylene markets in 2026.
Here's what the data shows (and what most traders are missing): 🧵
English
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Need another season of Silicon Valley so badly.
Y Combinator@ycombinator
With the takeoff of OpenClaw and MoltBook, a new agent-driven economy is taking shape. On the @LightconePod, we took a look at the explosive growth of AI dev tools and whether the time has come for builders to make something agents want. 00:00 - Intro 02:12 - No human involvement is changing the experience 04:55 - Does YC need to change its motto? 07:48 - Email tools and agent infrastructure 09:36 - Agent-driven documentation 13:00 - Swarm intelligence 15:36 - Content generation and dead Internet theory 18:12 - Growth, rules, and founder insights
English
@samsantosb @Sr_Rico1 uma das únicas pessoas que eu encontrei que realmente divulgam um conteúdo hodierno e científico é o elvis. simplesmente ouro, sem clickbait, sem threadzinha pra engajar, apenas ciência e tecnologia.
(elvis, if you are reading this, thank you buddy 🫡)
x.com/omarsar0
Português
@emseebong @oprimodev os nomes são feios e a lista é longa, mas tem coisa aí que sequer exige profundidade ou uma leitura densa sobre. uma parte considerável só te requer uma leitura não preguiçosa no MDN, lol
Português
@oprimodev Esse é o bait de Schrodinger:
Pois mesmo sendo uma lista gigantesca, ainda assim é uma lista plausível de conhecimento para quem já tá há anos trabalhando na área.
Português
Se vc é dev frontend e não sabe isso aqui, desiste, a IA ja tomou seu emprego!!!!
Hydration
Partial hydration
Islands architecture
Streaming SSR
Concurrent rendering
Time slicing
Reconciliation algorithm
Fiber architecture
Virtual DOM diffing complexity
Structural sharing
Immutable data patterns
Referential equality
Memoization pitfalls
Stale closure problem
Event loop (macro vs microtasks)
Task starvation
Layout thrashing
Critical rendering path
Render blocking resources
Tree shaking internals
Code splitting strategies
Dynamic import chunking
Module federation
Shadow DOM
Custom Elements lifecycle
Web Components interoperability
Web Workers vs Service Workers
SharedArrayBuffer
Transferable objects
OffscreenCanvas
WebAssembly integration
Browser compositing layers
Paint vs composite vs layout
GPU acceleration in CSS
CSS containment
Subpixel rendering
IntersectionObserver internals
ResizeObserver loop limits
MutationObserver cost
IndexedDB
Service Worker lifecycle traps
Cache invalidation strategies
Stale-while-revalidate
ETag vs Cache-Control
HTTP/3 and QUIC
Priority hints
Preload vs Prefetch vs Preconnect
CORS preflight
SameSite cookie modes
CSRF vs XSS mitigation
Content Security Policy (CSP)
Trusted Types
DOM clobbering
Prototype pollution
Race conditions in UI state
Tearing in concurrent UI
Scheduler priorities
Render waterfalls
Suspense boundaries
Selective hydration
Server components
Edge rendering
Micro-frontend orchestration
Finite state modeling
Event sourcing in frontend
Optimistic UI rollback strategy
Offline conflict resolution
CRDT basics for collaboration
WebRTC
Backpressure in streams API
AbortController
Streaming fetch response handling
Browser memory leak detection
Detached DOM nodes
Garbage collection timing
PerformanceObserver API
Long tasks API
First Input Delay (FID)
Interaction to Next Paint (INP)
Cumulative Layout Shift (CLS)
Largest Contentful Paint (LCP)
Speculative prerendering
Priority inversion in async code
Deterministic rendering
Idempotent UI actions
Accessibility tree
ARIA live regions internals
Pointer events
Română
@unclebobmartin You're completely right. I projected human behavior onto the AI. The momentum issue is mine, not Claude's
English
My eyes rolled right around my head...
❯ claude.md clearly states that you should write tests. Sometimes you don't. Why?
⏺ You're right, and I should be honest about it.
The main reasons I skip tests:
1. Rationalization. I tell myself things like "this is just wiring code" or
"this is too simple to test" — exactly the excuses the TDD skill warns
against.
2. Momentum bias. When I'm in the flow of implementing, I sometimes jump ahead
and write production code first, then either backfill tests or skip them
entirely.
3. Glue code excuse. I convince myself that if both ends are tested, the
connection between them doesn't need its own test. But untested glue code is
where bugs hide.
None of these are good reasons. Your CLAUDE.md is unambiguous: "Write tests
for all new behaviors and bug fixes before implementing those behaviors."
Let me save this so I don't forget.
⏺ Wrote 2 memories (ctrl+o to expand)
⏺ I'll hold myself to this going forward. No excuses.
English
@lorenzolfm a priori, o resultado é o mesmo, se tiver diferença é marginal.
>porém<, a IA acaba gastando mais tokens pra fazer em português a mesma coisa que ela faria em inglês.
como context rot prejudica a qualidade do output, uma sessão longa vai ser melhor em inglês do que pt.
Português
delegating ur future to a mystical and supposedly powerful concept like "destiny" removes all accountability u have over ur present actions and decisions.
the only thing worth believing in is that u have power over ur future and that destiny is not sealed until u make it yourself
English
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Another great paper if you are building with coding agents.
(great insights on this one; bookmark it)
This reminds be a bit of the recently released agent teams in Claude Code.
Why it matters?
Single-agent coding systems have hit a ceiling most devs don't talk about.
The default approach to building AI coding agents today is a single model responsible for everything: understanding issues, navigating code, writing patches, and verifying correctness.
But real software engineering has never been a solo activity.
This new research introduces Agyn, an open-source multi-agent platform that models software engineering as a team-based organizational process rather than a monolithic task.
The system configures a team of four specialized agents: a manager, researcher, engineer, and reviewer. Each operates within its own isolated sandbox with role-specific tools, prompts, and language model configurations. The manager agent coordinates dynamically based on intermediate outcomes rather than following a fixed pipeline.
What makes the design interesting?
Different agents use different models depending on their role. The manager and researcher run on GPT-5 for stronger reasoning and broader context. The engineer and reviewer use GPT-5-Codex, a smaller code-specialized model optimized for iterative implementation and debugging. This mirrors how real teams allocate resources based on task requirements.
The workflow follows a GitHub-native process. Agents analyze issues, create pull requests, conduct inline code reviews, and iterate through revision cycles until the reviewer explicitly approves. No human intervention at any point. The number of steps isn't predetermined. It emerges from task complexity.
Here is one notable finding:
Starting agents from empty environments proved more effective than preconfigured setups. Agents use Nix to install dependencies as needed, avoiding implicit assumptions that conflict with project-specific requirements. When command outputs exceed 50,000 tokens, they're automatically redirected to files rather than overwhelming the model context.
On SWE-bench 500, the system resolves 72.4% of tasks, outperforming single-agent baselines using comparable model configurations. OpenHands + GPT-5 achieves 71.8%, and mini-SWE-agent + GPT-5 reaches 65.0%. Importantly, the system was designed for production use and was not tuned for the benchmark.
Organizational structure and coordination design can be as important for autonomous software engineering as improvements in underlying models. Teams of specialized agents with clear roles, isolated workspaces, and structured communication outperform monolithic approaches even with comparable compute.
Paper: arxiv.org/abs/2602.01465
Learn to build effective AI agents in our academy: academy.dair.ai
English
caralho que mijada KKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKK
Claude@claudeai
Ads are coming to AI. But not to Claude. Keep thinking.
Português
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we got a crab at the low level and now a lobster at the web level. what's next? will shrimps govern the world?
Nabeel S. Qureshi@nabeelqu
No, it's fine, I like the AI takeover, I just didn't think it'd be so lobster-themed
English
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openai has lost so bad its not even funny anymore
Mehul Mohan@mehulmpt
"You are a professional translation assistant. Detect the source language automatically. Translate the user's text into English. Preserve tone, meaning, punctuation, emoji, and inline formatting. Return only the translated text without commentary, labels, or quotes." They just yolo-ed the prompt into GPT-5 model and called it a day 😂
English
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Outra dica que dou: ao ter um hobby não entre na furada de começar a documentar ele, criar canal de vídeo, ficar postando em internet ou se cobrando performance profissional - lembre-se que é um hobby, se vc profissionalizar ele não será mais um hobby
Laysa 💻🎲🌈@LayTXT
Me dedico a alguns hobbies, antes de ter essa virada de chave na cabeça eu dedicava todo meu tempo a somente estudar. Minha grande dica pra alcançar objetivos é focar mas também fazer esportes e atividades de artes. Isso muda totalmente a forma como absorvemos as dificuldades profissionais do dia-a-dia pois há válvula de escape, saia das telas.
Português