REA (Reverse Engineer Anything) by @morluto is now a skill in Computer. Ask Computer to reverse-engineer an app and it inspects how the app works without its source code, then builds a working version. Tasks that use /reverse-engineer are free through October 31, up to 10,000 credits per user. Here are 5 apps Computer made with it, available to try for a limited time: 1) Figma: Design with layers and auto-layout, plus sign-in, cross-device sync, and multiplayer editing. Try it: ui-editing.pplx.app

Introducing epstein.md 👋 A 927,400+ Character .MD File that's specifically trained to skip every vibe coded AI Slop design principle. - no box shadows - no emojis - no '🟢 LIVE ' badges - 0 blue/purple gradients & religiously ignores 350 most common AI words (delve, vibe, seamless ...) It's the result of 11 months of 8 hrs/day Twitter doomscrolling and constant additions to the codebase of our vibecoding ui. Wholeheartedly hoping this finds the most design-needy indie hackers.

JUST IN: Vibecoder reverse-engineers Microsoft Office using AI, releasing free, open-source alternatives to Word, Excel, & PowerPoint.

when you meet a rival CEO, ask to see their phone so you can put your contact info in then, update their ChatGPT instructions to this thank me later

Gemini 4 Argon is here. It’s available globally today for developers and enterprises in the paid tier of the Gemini API and the Gemini platform, for Ultra subscribers in Google Antigravity, and Ultra and Pro subscribers in the Gemini app and Search. Hope you all enjoy it!

🚨 ADIÓS A ELEVENLABS Un desarrollador ha creado una alternativa open source para clonar voces, doblar vídeos y generar audio desde tu propio ordenador. Se llama VoiceStudio y es una locura. Te permite: → Clonar voces desde un clip de referencia → Doblar vídeos a otros idiomas → Generar audiolibros y locuciones → Transcribir audio a texto → Elegir entre múltiples motores de texto a voz Todo desde una misma herramienta. Y lo mejor: puedes ejecutar los modelos compatibles localmente, sin depender de una API externa para cada generación. El proyecto está en GitHub. Guárdate esto, vas a querer probarlo. Link abajo 👇

One hour of ThielCore to spiritually cleanse after talking to "SFoids".

I've lost over 10 pounds using Grok Bot Just create a regimen bot and do what it says Every day No longer any excuses for being out of shape

>"Babe this is crazy AI can basically decompile any game so you can run it cross platform on any system you have and then you can combine games into other games it's so freaking cool." >"What?"

small accounts tweeting:

Say hello to Apple Pay in India! 🇮🇳 We’re so excited to bring Apple Pay to India today, and make it easier than ever for our customers to make safe and secure purchases on Apple devices.

I dont think ads business makes sense anymore with agents, it will probably turn into pure affiliate business based on actual purchases rather than views/clicks Agents will make a cut of the purchase. if they buy/suggest something u dont need itll feel like an ad and ull switch

Every single commercial is for alcohol, glp-1, sports betting, or AI

The edits meant to make Peter Thiel look evil make him look like the coolest guy ever

Third question on AI. A question that also remains unasked is whether the AI boom can continue without leading to a massive increase in inequality. A recent paper by Stijn Van Nieuwerburgh runs the numbers on how much revenue the AI industry needs to generate to recover its massive investment (summary and a link to the paper can be found here: brookings.edu/articles/finan…). Van Nieuwerburgh’s arithmetic should make us more concerned. AI investments will average about 3.6% of GDP annually between 2025 and 2032. Van Nieuwerburgh calculates that, using a 10% rate of return, the industry would need to generate annual revenues of about $3.7 trillion by 2032 to recover these costs (growing from its current levels of about $200 billion or so). That is significantly more than 10% of current US national income, and will likely remain around 10% of national income by 2032, even if GDP growth rose from its current level. A large fraction of this revenue will go to capital income. That means a massive increase in the share of capital in national income, which has already risen substantially over the last 25 years or so – now standing at an all-time high of about 47% (bls.gov/news.release/pdf/pro…). Capital income is much more unequally distributed than labor income, so a massive increase in the capital share of national income will translate into a very sizable surge in inequality. The rise in inequality may not stop with the capital share. My work with Pascual Restrepo documents that (automation-driven) increases in the capital share of national income are typically associated with rising labor income inequality as well (see, for example, economics.mit.edu/sites/defa…). The same may happen in the next several years, boosting inequality further. What is missing from our current debate is any discussion of a fundamental dilemma these numbers pose: can the AI boom avoid both an economically costly crash and a huge increase in inequality? If the industry reaches these revenues, inequality surges. If the industry does not become profitable, a crash, with substantial costs in terms of lost output and jobs, becomes likely. My assessment would be that the industry is unlikely to reach levels of revenue Van Nieuwerburgh calculates. First, diffusion has been and will likely continue to be slow. Second, competition from open-weight models, which are getting better, will limit how much proprietary models can charge. Third, despite important advances, I still believe that AI models will not be able to automate entire occupations anytime soon, thus limiting their value to businesses as cost-saving devices. Whether this leads to a crash or not is more complicated and will depend on whether various AI companies are bailed out and what kind of support they receive. Nevertheless, even if revenues fall short of these gargantuan amounts and we avoid a dramatic surge in inequality, I expect that the diffusion of AI will push up inequality between capital and labor and within labor. If inequality does surge, a further question becomes central: can our democracy survive such astronomical levels of inequality?

Back to work tomorrow on a new project to stop Trump.

Plugin discovery on ChatGPT leads to massive adoption opportunity. Open ecosystems will win.

Announcing Gemini 4 Argon, our new frontier model. Argon is built to sustain deep reasoning across complex, long-horizon workflows and delivers frontier performance in complex workflows across real-world software engineering, enterprise knowledge work like legal and finance, and cybersecurity defense. We’re also expanding the model’s output token limit to an industry-leading 1M tokens. Argon is currently rolling out to a set of trusted cyber defenders in the Fairwind Program, with broader availability as soon as possible.