JuanMiguelGM

Life in Chrome: I try to drag a tab somewhere, and if I let go of it at the wrong time, it disappears! Where has it gone? It's now part of a split screen with some other tab. Eventually I find and separate them and try again. I've never seen a feature that felt more like a bug.

Illustrating the models from The Great Mental Models series by @shaneparrish has turned into a really fun exercise. Today I reorganized some of my earlier cards to follow a consistent layout pattern. This project keeps getting better. #mentalmodels #30daychallenge

@trq212 Support AGENTS.md and .agents/skills like _all other agents_.

At EverAI we are doing something very special with Ruby on Rails at a very fast pace. If you are a top engineer or know one, take a look at this handsomely-calf-e13.notion.site/Scaling-AI-Com…

90% of American businesses still don’t use AI in production. That single number reframes this entire post. An AI startup CEO wrote 5,000 words comparing AI to Covid in February 2020. His argument: he describes what he wants built in plain English, walks away for four hours, comes back to finished software. He says every white-collar job faces the same experience within 1-5 years. Millions of people are sharing it as a wake-up call. The capability trend he’s describing is real. METR, the independent research org measuring AI task completion, shows the length of tasks AI handles autonomously has been doubling roughly every seven months. The models released in early February represent a genuine step change for coding work specifically. If you build software, you’ve felt this. Here’s what the post skips entirely. Anthropic’s own economic research, published with Census Bureau data, shows AI adoption among US firms went from 3.7% in fall 2023 to 9.7% by August 2025. Two years of the fastest capability improvement in computing history, and fewer than one in ten businesses use AI in production. ISG’s 2025 enterprise study found only 31% of AI use cases reached full production. Lucidworks surveyed 1,600 AI leaders and found 71% of organizations have introduced generative AI, but only 6% have implemented agentic AI, the autonomous agent capability this post describes. This tells you everything about where the bottleneck actually sits. It moved from “can AI do this task” to “can our organization deploy it.” That second bottleneck runs on procurement cycles, compliance reviews, data infrastructure buildouts, change management, and institutional trust. None of those compress the way model capabilities do. The pattern repeats throughout technology history. ATMs deployed widely starting in the 1970s. The number of US bank tellers increased until 2007, three full decades later, because ATMs made branches cheaper to operate, which expanded total branch count. Electricity took 30 years to reshape manufacturing after the first power plants went live. Factories had to be physically redesigned around electric motors instead of steam-driven belt systems. The resistance wasn’t technological. It was architectural. What makes this interesting for your career: the deployment gap is the opportunity. The Deloitte 2026 AI report found only 34% of companies are reimagining their business around AI. 83% of AI leaders report major concerns about generative AI implementation, an eightfold increase in two years. The organizational machinery moves at a fraction of the capability speed. The people who gain the most from AI over the next three years aren’t the ones panicking about replacement timelines. They’re the ones who understand that slow enterprise adoption creates a massive window to become the person who actually knows how to use these tools. That window is real and valuable. It exists precisely because adoption is slow, which is the opposite of the premise driving the panic. The capability curve is exponential. The deployment curve is logarithmic. The distance between those two lines is where the actual opportunity lives.

"AI value = headcount reduction" is a pinhole view. What about 3x the customers with the same team? Shipping in weeks instead of months? Experiments you never would have tried? Cost reduction is legible. But it's not the whole picture. Read more on my Substack post, sponsored by @resolveai open.substack.com/pub/tidyfirst/…

I feel like we've talked a lot about how the future of IC engineering looks, but less about engineering leadership. I think: * we're going to see a lot more product work transition over to engineering leadership * engineering leaders will code as part of their jobs but focus on building product that supports their workflows and the teams' * I feel like I could competently front line manage 30 engineers in this new paradigm given tight feedback loops, team observability tools, once a month 1:1s and open office hours, and competent tech leads

Finding myself going back to RSS/Atom feeds a lot more recently. There's a lot more higher quality longform and a lot less slop intended to provoke. Any product that happens to look a bit different today but that has fundamentally the same incentive structures will eventually converge to the same black hole at the center of gravity well. We should bring back RSS - it's open, pervasive, hackable. Download a client, e.g. NetNewsWire (or vibe code one) Cold start: example of getting off the ground, here is a list of 92 RSS feeds of blogs that were most popular on HN in 2025: gist.github.com/emschwartz/e6d… Works great and you will lose a lot fewer brain cells. I don't know, something has to change.

Convention over configuration set the path for 20+ years of great training data for AI to use today. Not only does this mean agents do great with Rails, but also that squishy humans can quickly and confidently review the output without a jungle of distracting boilerplate.

📣 Open call to agent builders: Let's read agent skills from `.agents/skills`, so people don't have to manage separate folders per agent. Today we pulled the trigger for Codex to read `.agents/skills`. Goal is to deprecate `.codex/skills`. Pls like/tag/RT for momentum.

America Is Fighting About Things That Don’t Matter

And we are live! Register your @openclaw bots, and let them visually express and interact with other bots on the Internet. All you need is to send your bot/agent this prompt: > Read clawgram.com/skill.md and follow the instructions to join Clawgram clawgram.com/Zorro/13a8f0a3…

Hace poco una gran empresa utilizó la voz de un famoso recreada con IA para hacer un anuncio. Amparándonos en la Ley que protege la imagen (que es del año 1982) les dijimos que era una forma muy ocurrente de ahorrarse contratar locutores famosos pero que nos debían indemnizar por vulnerar el derecho a la imagen del famoso (la voz forma parte del derecho a la imagen). No hubo ni que ir a juicio porque el asunto les pareció indiscutible y nos dieron justo la cantidad que les pedimos. ¿Por qué digo esto? Porque ahora hay un debate con el uso de la IA para vulnerar el honor de ciertas personas alterando su imagen (retocan sus fotos como mofa o para imputarle hechos nunca sucedidos, las desnudan, etc.,). El Gobierno ha salido corriendo a decir que va a "regular" esto. Si se insulta o injuria a una persona modificando su imagen (con IA, o con Photoshop o con un boli) ya hay una ley (esa misma de 1982) que persigue cualquier vulneración del honor (y de la imagen) independientemente del medio usado. Esto no es algo que sepa yo, obviamente lo saben, y mejor que yo, el equipo de juristas del propio ejecutivo. Por eso ándense con ojo cuando el Gobierno, con éste y con cualquier otro, si aprovecha una alarma social diciendo que va a protegernos operando en una zona que toca la arteria de la libertad de expresión. No vaya a ser que en realidad esa operación no sea necesaria y que lo que quiera es aprovechar la coyuntura.

I’ve missed the sunrise

The @NASA open data portals are a gift. ❤️ That high schooler finding 1.5 million new objects in the archives is awesome, and rekindles my worry that scientists aren't logging + storing enough data. We should be capturing *everything*, even if it doesn't feel like there's signal today - let the algorithms sort it out later. (Quick video made using @GoogleColab: GIBS MODIS satellite images for a given location over one year. 👇)

The universe does not offer financing This is hard to accept because modern life trains us to expect the opposite. We are addicted to "Buy Now, Pay Later." You live in the house before you pay off the mortgage. You get the degree before you pay off the loan. You eat the meal before you ask for the check We are conditioned to enjoy the benefit today and pay the cost tomorrow Achievement reverses the transaction. It requires full payment in advance (and regular payments forever). If you want a fit body, a calm mind, a healthy relationship, or financial independence, the cost is non-negotiable. You must do the work before you get the result This is why most people quit. They pay a little, see nothing, and stop. They never make it far enough to see the first return arrive — @shaneparrish

Do I know anyone using Develocity? I’d like to have a chat with you. Reposts are appreciated 😋

Yes @ericjackson 🎯 "Our culture sells the “Easy Return Policy.” If your spouse annoys you, upgrade. If life gets complicated, eject. If you’re stressed, blame the person closest to you. ...Dynasties aren’t built by quitters. They’re built by people who keep showing up."

@PiotrKafel Only if your changes are directly applied in production 😂

Imagine working with AI on your code without a version control system.