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Not today Justin
Mike Driver
The Bowery Presents
Jar Jar Binks Fan Club
Origami Around
Fai_Ryy
Monterey Bay Aquarium
hello vonnie
RMH
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we're not kids anymore.
KIROKAZE
#extradirty
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izzy's playlists!
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@divergente
WordPress Campus Connect: estudiantes, IA y EL futuro de la open web WPCC no va solo de enseñar a hacer webs. Va de abrir puertas: a la web abierta, al aprendizaje práctico, a la IA como palanca y a una primera experiencia real que puede convertirse en portfolio, confianza y profesión.... https://remotefrog.com/2026/07/17/wordpress-campus-connect-estudiantes-ia-y-el-futuro-de-la-open-web/
OMG, A slop paralysis Crysis! Understanding “slop paralysis,” and how to deal with it in 1 minute.... https://remotefrog.com/2026/07/13/omg-a-slop-paralysis-crysis/
OMG! (cielos!) slop paralysis La idea es simple: dejas que un agente genere muchísimo código, pero luego te bloqueas al revisarlo. ¿Y qué haces entonces?...
Combina bolígrafo y papel con IA para convertir flujos de pensamiento, ruminaciones creativas e ideas en bruto en diagramas más claros, limpios y fáciles de compartir.
Asistente de datos: por qué un agente sin contexto es un charlatán Un asistente de datos no mejora solo con un mejor modelo: mejora con contexto curado, asunciones claras y workspaces diseñados para responder con más utilidad y confianza....
AI is getting better at spotting patterns and producing plausible answers. But the core of analytical work still lives in the why. Minimal prompts can feel elegant. They are often lazy. If you already know the context, constraints, purpose, and risk of misinterpretation, you should share them. Otherwise, you are testing the model’s guessing ability rather than really collaborating with it.
A practical reflection on testing Atlas, an internal AI data assistant built around curated workspaces. Why tacit knowledge, assumption handling, text usability, and workspace maturity matter more than raw model power.
The best of both worlds: pen and paper, then AI Discover a workflow that combines pen and paper with AI to turn rough ideas into clearer, cleaner, and easier-to-share diagrams....
A small AI data experiment: the model still needs the why An AI assistant can spot patterns in grouped data, but the meaning of those patterns depends on what you are trying to understand. A short experiment on the importance of the "why"....
If an AI agent can write SQL against your schema, can it actually understand it? This post offers a practical guide to improve agent-readiness covering metadata, semantics, business meaning... to allow AI Agents use your data without guessing and prevent silent analytical errors.
Claude Code is brilliant. The terminal, not so much, so Nimbalyst it. Claude Code is incredibly powerful, but the terminal can get clunky once you move beyond quick tasks. Nimbalyst adds a visual workspace on top of Claude Code (and Codex), making it easier to manage sessions, review changes, work with docs and mockups, and generally keep your sanity.... https://remotefrog.com/2026/06/05/claude-code-is-brilliant-the-terminal-not-so-much-so-nimbalyst-it/
La IA puede darte una respuesta. No puede darte el porqué. y 2. La IA es cada vez mejor detectando patrones y produciendo respuestas plausibles. Pero el quiz del trabajo analítico sigue estando en el porqué, y esa parte sigue siendo humana....
Claude Code es brillante. El terminal, no tanto… A Nimbalystear! Claude Code es potentísimo, pero la terminal se vuelve torpe en cuanto sales de las tareas rápidas. Nimbalyst añade un workspace visual limpio y Open Source encima de Claude Code (y Codex), haciendo más fácil gestionar sesiones, revisar cambios, trabajar con docs y mockups y, en general, conservar la cordura.... https://remotefrog.com/2026/06/04/claude-code-es-brillante-el-terminal-no-tanto-a-nimbalystear/
Un experimento para comprender lo importante que es saber el porqué para guiar al modelo. La IA es cada vez mejor detectando patrones y produciendo respuestas plausibles. Pero ya lo dijo el Gato de Cheshire: la regla para saber cómo llegar es conocer dónde quieres ir....
Your Data Schemas Are Ready for Humans. Are They Ready for AI Too? If AI agents are going to write SQL, analyze data, and answer business questions, “somewhat documented” is no longer enough. This post explores how to assess whether a schema is understandable not just for humans, but for AI too — and proposes a practical rubric to improve it....
Le pedimos a los agentes de IA que escriban SQL, detecten patrones y razonen sobre nuestros datos. Pero si el esquema tiene conocimiento implícito, el agente improvisa: el SQL compila, corre y devuelve números plausibles... que no son correctos. Te propongo una rúbrica con cinco dimensiones y dos herramientas para evaluar y mejorar la legibilidad de tus esquemas antes de que el agente se ponga a tirarse triples.
23 looks good on WordPress. 🎂 Since May 27, 2003, WordPress has been blogging, building, publishing, shipping, translating, theming, plugin-ing, and making the web a little more wonderfully weird. Happy birthday, WordPress. 💙 #WordPress
