→ Introduction to Agent Skills Crea instrucciones reutilizables que Claude aplica automáticamente cuando las necesita. Una vez lo configuras, trabaja solo. Eso es automatización real. https://
anthropic.skilljar.com/introduction-t
o-agent-skills
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AI
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Introduction to Claude Agent Skills and Reusable Instructions
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Introduction to Claude Cowork: collaborative AI for real projects
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→ Introduction to Claude Cowork Claude trabajando directamente sobre tus archivos y proyectos reales. No es un chatbot. Es un colaborador que entiende tu contexto. Aquí deja de ser un juguete y se convierte en herramienta de trabajo real. https://
anthropic.skilljar.com/introduction-t
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AI Fluency Course for Students: Responsible Use and Collaboration
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→ AI Fluency for Students Si estás estudiando, esto cambia las reglas. > Aprende a usar IA para mejorar tu rendimiento académico
> Planifica tu carrera y colabora con Claude de forma responsable. https://
anthropic.skilljar.com/ai-fluency-for
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Anthropic offers free certified AI academy with agent courses
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Anthropic tiene una academia gratuita con certificados oficiales. 16 cursos.
Desde cero hasta agentes de IA. Te dejo los más interesantes con link directo -
DeepSeek V4: Chinese AI Model on Huawei Silicon
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DeepSeek is about to release V4, and for the first time, a frontier Chinese AI model will run natively on Huawei silicon. A brief analysis and why its much bigger than most people think. Alibaba, ByteDance, and Tencent have placed bulk orders for hundreds of thousands of
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AI Exhaustion: The Cognitive Load of Running Multiple Agents Daily
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The AI exhaustion point is so real. I run multiple agents daily and the cognitive load of reviewing and directing is genuinely harder than just doing it yourself sometimes. Especially when the task is simple but long to do, at least it used to not require mental efforts. Now I
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Commercial vs Open Source: Not Direct Competitors
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One’s a commercial product and one open source and free. Wouldn’t call that competitors.
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Genesis Energy Selects OPSWAT for Cybersecurity Solutions
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Genesis Energy chose OPSWAT after considering testimonials from customers nationally and internationally within the utility sector globally.
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Fine-tuning vs Retrieval: Fixing Hallucinations About Company Docs
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If your model is hallucinating about your company docs, fine-tuning is usually not the fix.
— Louis-François Bouchard 🎥🤖 (@Whats_AI) 4 avril 2026
That’s the trap.
A lot of teams see wrong answers about internal files and assume they need to retrain the model. But fine-tuning changes behavior, not factual recall of constantly… pic.twitter.com/LBVCwJbm3YIf your model is hallucinating about your company docs, fine-tuning is usually not the fix. That’s the trap. A lot of teams see wrong answers about internal files and assume they need to retrain the model. But fine-tuning changes behavior, not factual recall of constantly changing company knowledge. It can help with tone, structure, or broad domain patterns. It is not the best tool for making a model reliably remember your latest return policy, pricing sheet, or product catalog. For that, you usually want retrieval. In other words: fine-tuning teaches patterns, retrieval supplies facts. So if the issue is accuracy on specific documents, give the model better access to the right context instead of trying to bake those facts into its parameters. It is cheaper, easier to update, and much more controllable. Mixing those two up is one of the fastest ways to waste time and budget in AI. Have you seen teams make this mistake already?