Williams Almeida @williamsdev_

My god this is such a good speech that every SWE needs to hear. You know what? Every person should hear it Keep the happy memories, eyes on the reality, be excited about the future. That’s the best that anyone can do

AI red flags: - "My marketer agent just finished a meeting with my chief of staff agent - just 2 of the 127 agents on my books" - "The agent did it, not me" - "I've invented a coding language for agents" - "I've got 250K tokens in my context before I send a message, is that normal?" - "Opus 5 is way dumber today than yesterday, secret nerf?" - "Peasants, gaze upon my 600-line CLAUDE.md, my results are incredible" - "LOOK WHAT OX ALPHA JUST ONE-SHOTTED, SOFTWARE ENGINEERING IS DEAD" - "All human knowledge is worthless now" - "I turned 600 coding books into a skill" - "Coding is solved. Bugs are not solved"

If you even slightly entertain the thought of failure, you give your mind a chance to start noticing reasons to fail. But if the only option on your mind is to win, then the world seems to conspire in your favor, because your mind will notice opportunities it wouldn't have before. Become delusionally optimistic, not because it's realistic, but because it's effective. It drastically increases your chances of success.

Something I have been thinking about: in the past, the best engineers I knew spent a lot of time automating their work in various ways. Better vim/emacs automations, writing lint rules to catch repeat code issues, building up a suite of e2e tests so they don't need to smoke test the app manually. These kinds of things were the highest leverage activities an engineer could do, because it multiplied their own output, which in turn meant they could build more things. I think many of these automations have become even more important now. This is true for a number of reasons. First, infra and DevX automation speeds you up. And if you are running an army of agents, each of those agents will be sped up also. More automation == more output per unit of time. Second, moving things to code improves efficiency. Your agent could fix an issue every time it sees that issue happen, but that uses tokens and might miss cases. If Claude instead writes a lint rule, CI step, or routine, that class of issue can be fully automated forever. This is really what people are talking about when they talk about loops -- it's about automating entire types of busywork rather than solving them one off. This isn't a new idea at all. Engineers have been doing this for a long time! Third and most importantly, automation makes it possible for others to contribute to the codebase more easily. Increasingly what I am seeing is engineers are contributing to codebases on day one because Claude can navigate the codebase for them, and that non-engineers are able to contribute to a codebase as effectively as engineers can. What gets in the way of both of these is domain knowledge that lives in peoples' heads rather than in automation -- the stuff you used to have to learn when ramping up. What has changed thanks to agents is the domain knowledge that can be encoded as infrastructure is no longer limited to what is expressible in lint rules and types and tests; it can now capture nearly all domain knowledge, encoded as code comments and skills and CLAUDE.md rules and memories. If I put up a PR for an iOS codebase I don't know and a code reviewer rejects it because it doesn't use the right framework, or if a designer builds a new feature and it gets rejected because it doesn't follow the right architectural patterns, these are failures of automation. Every team should be writing the CLAUDE.md's, REVIEW.md's, skills, and docs that enable agents to productively work in their codebase with zero additional context from the prompter. This sounds crazy, and at the same time is a natural extension of the stuff engineers have always done: automate, and encode domain knowledge as infrastructure. As the model gets smarter and as the harness matures, this task becomes easier. In the meantime, it is on every team to look for ways to convert their domain knowledge to infra so that Claude can write code better, so that code review catches issues automatically, and so the next person working on your codebase can contribute more easily.

Boa parte do que torna uma interface parecer amadora é uma coisa só: hierarquia visual fraca. Tudo grita ao mesmo tempo, então nada se destaca. Você já abriu uma tela e sentiu que ela era "barulhenta" sem saber explicar por quê? Costuma ser isso. Tudo está grande, tudo está em negrito, tudo tem cores fortes, e o seu olho não sabe para onde ir primeiro. Quando tudo é importante, nada é. Hierarquia é a decisão de que algumas coisas importam mais do que outras e de fazer o resto dar um passo atrás. É você guiando o olhar da pessoa numa ordem: primeiro isto, depois aquilo e, por último, o detalhe. Toda tela boa faz isso, mesmo que você não perceba. São quatro ferramentas, e o segredo está em combiná-las. → Tamanho. Maior puxa mais atenção. A armadilha do iniciante é usar só o tamanho, deixando o secundário minúsculo a ponto de ninguém ler. → Peso. Negrito chama o olho. Guarde o negrito para o que importa de verdade. Se tudo estiver em negrito, o negrito perde o sentido. → Cor e contraste. Aqui mora a sacada que o Refactoring UI ensina bem: para diminuir a importância de um texto secundário, em vez de encolhê-lo, clareie-o. Um cinza mais suave reduz o peso sem comprometer a legibilidade. Você enfatiza com mais contraste e apaga com menos. → Espaço. O espaço em volta de um elemento é o que o faz respirar e se destacar. Ele também agrupa o que é semelhante e separa o que é diferente. Espaço vazio não é desperdício, é hierarquia. White space é saber de UI de verdade. E tem uma virada de chave que muda tudo: muitas vezes você não cria destaque gritando mais alto no elemento principal, mas silenciando os outros. Em vez de aumentar o principal, abaixe o volume do resto e ele aparece sozinho. É por isso que o bom design parece simples a ponto de parecer fácil. O iniciante adiciona mais cor, mais sombra, mais gradiente, mais negrito, achando que isso é "design". Quem sabe remove e ordena. O exagero quase nunca é sinal de um design forte. Na maioria das vezes, é sinal de uma interface sem hierarquia tentando compensar a bagunça com barulho. O que parece limpo está limpo porque o fundamento está trabalhando por baixo, de forma invisível. No fim, a pergunta certa não é "o que eu adiciono para isto parecer mais design?". É "o que eu posso silenciar para o importante ser ouvido?". Dominar hierarquia, espaço e contraste a esse ponto é o que separa uma interface amadora de uma profissional, e é o foco do UI Pro da DC.

SpaceX has exercised the option to acquire @cursor_ai in an all-stock transaction with the goal of building the world’s most useful AI models. For the past few months, SpaceXAI has been jointly training a model with Cursor, which will be released in Cursor and Grok Build soon. We look forward to working closely with the Cursor team to advance our frontier AI capabilities

SpaceX @SpaceX

6 months ago

SpaceXAI and @cursor_ai are now working closely together to create the world’s best coding and knowledge work AI. The combination of Cursor’s leading product and distribution to expert software engineers with SpaceX’s million H100 equivalent Colossus training supercomputer will

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"Engineering, product, and design are all merging into a 'builder' role" Yeah... I'm not so sure. This feels like an oversimplification and podcast talking point. Reality is a lot more complex. Even with 1000 "Member of Technical Staff" titles, someone still has to wake up and care 100x more about Product or Design than anyone else. It is their Main Thing™ That's not to say MTS titles are universally bad, but I think they're an example of this 'builder' talking point that's become bastardized. AI and coding agents have made generating code easy and yet... you're in for a world of pain if non-engineers ship a bunch of slop and don't have great engineers to tame the complexity. The SF hivemind has a tendency to overfit what works at startups for every company. And to be fair, sometimes this is true! Startups can be a leading indicator for how the industry is changing and often cause disruption. However, it is going to be incredibly hard to disrupt the extremely human parts of corporate jobs. You really think there's going to be a PM who also does some engineering and design on the side at JPMorgan Chase? This is true for the simple parts of most jobs, like people wanting to have ownership over something and do good work, move up a career ladder, support their family, get paid well, make an honest living... And also the hard parts: internal politics, some critical business system that has a bus factor of 1 which has been running for 15 years and isn't documented anywhere because it's that guy's job security. The real world has a lot of this stuff. It's easy to pontificate about all roles collapsing but it's actually really nice to have a specific person or team who is an expert in one thing that you can work with. I don't expect that to change. Further, I think AI disruption to knowledge work will take decades to play out because it is more fundamental to the human condition (e.g. sociological/organizational) than pure intelligence.

Nothing will shape your worldview as much as simply reading how humans from the past thought. You realize very quickly that our time is a radical anomaly in human history.

Auron MacIntyre @AuronMacintyre

5 months ago

Read old books

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If you don't have a goal so meaningful it makes other people's opinions irrelevant, you will lose control of your life. You will adopt the goals assigned to you by your parents, peers, or society.

it’s better to quit if you can’t keep challenging yourself to do something more complex, just quit building software people wanna keep getting joy by rewriting the same react component in neovim for the 400th time, or firing up another identical Elixir script on their split keyboard like it’s 2018 > the joy of learning is gone what they really mean is: i am sad I don’t get to learn a new JS framework go build something bigger, something that AI won’t one-shot in a single prompt, something you’ll be afraid to run on your own machine

Introducing Claude Opus 4.7, our most capable Opus model yet. It handles long-running tasks with more rigor, follows instructions more precisely, and verifies its own outputs before reporting back. You can hand off your hardest work with less supervision.

Transforme um fluxo repetitivo do seu dia em um “microproduto interno” com IA e verá sua produtividade mudar drasticamente. Exemplo: suporte, checagem de serviços, geração de PRD, quebra em issues, review inicial, atualização de status. Muita gente tenta usar IA só pra “escrever código mais rápido”, mas o ganho real aparece quando você encadeia tarefas chatas e previsíveis num fluxo que trabalha com você. Menos prompt solto. Mais sistema. Se eu fosse resumir: quem aprender a operacionalizar IA no próprio processo vai ganhar muito mais do que quem só usa pra autocomplete premium.

@mattpocockuk Concordo! Muita gente tenta escalar agent workflow terceirizando o pensamento pra framework, mas aí também terceiriza a capacidade de debugar. Quando processo, contexto e checks continuam visíveis, o ganho fica bem mais sustentável.

Now in research preview: routines in Claude Code. Configure a routine once (a prompt, a repo, and your connectors), and it can run on a schedule, from an API call, or in response to an event. Routines run on our web infrastructure, so you don't have to keep your laptop open.

A maior ilusão do dev é achar que o problema é velocidade. Quase nunca é! O que destrói teu dia é troca de contexto: feature, cliente, deploy, bug, suporte, reunião, volta pro código. No fim, tu não trabalhou pouco. Tu só trabalhou fragmentado. Produtividade não é fazer mais por hora, é interromper menos por dia.

A discussão sobre AI coding mudou de lugar. Não é mais “qual modelo escreve código melhor?”. É: qual stack de agents tu consegue orquestrar sem virar babysitter da automação. Hoje o gargalo raramente é o modelo. É contexto ruim, instrução ruim e handoff ruim entre tools. Quando acerta isso, a IA deixa de ser autocomplete caro e vira multiplicador real. O modelo importa, claro. Mas cada semana fica mais óbvio que workflow > benchmark.

Esse é o tipo de coisa que mexe no mercado de verdade. Não é só mais um modelo ou mais uma feature, é a infraestrutura que faltava pra muita gente sair do protótipo e começar a colocar agents em produção com muito menos atrito. Se a execução acompanhar a promessa, isso muda bastante o jogo.

Claude @claudeai

7 months ago

Introducing Claude Managed Agents: everything you need to build and deploy agents at scale. It pairs an agent harness tuned for performance with production infrastructure, so you can go from prototype to launch in days. Now in public beta on the Claude Platform.

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x.com/i/article/2041…

O crescimento de tools como Codex mostra uma mudança clara: IA pra dev deixou de ser feature de curiosidade e virou camada real de trabalho. Agora a disputa não é sobre quem gera código mais bonito na demo. É sobre quem economiza mais tempo e cria menos problema no fluxo real.

Tibo @thsottiaux

7 months ago

Three million people are now using Codex weekly - up from two million a little under a month ago. Incredible to see the growth. Thank you to all of you and to the ecosystem we’re part of. To celebrate, we’re resetting rate limits so you can keep building, and we’ll reset them

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🚨 VAZAMENTO CLAUDE CODE 🔥 Vazou a codebase completa do Claude Code, via um source map de 57 MB que ficou público no pacote npm oficial. E o @vineetwts já fez o que ninguém esperava: criou uma documentação completa do código em tempo recorde! Nela ele explica tudo: - Pipeline do agent - Como funciona o loop agentic - Gerenciamento de contexto - Memória persistente - Ferramentas, permissões e muito mais X/Twitter tá pegando fogo hoje 🔥 mintlify.com/VineeTagarwaL-… #ClaudeCode #AgenticAI #Anthropic