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fought Kevin O’Leary’s AI data center Hearing tech startup Legato launches its AI hearing glasses | TechCrunch Piero Molino on AI in Games The Dot and the Swarm The State of Browser Testing - Software Engineering Daily Sidecars: A low-latency trust boundary for Sandboxes | Modal Blog Is sandboxing sufficient to contain rogue agents? Distributed databases with Peter Mattis When Glasses, Earbuds and Phones All Have AI, Who Will Unify Your “Second Brain”? | Snapdragon Summit 2026 Sierra joins the OpenAI Marketplace Episode 852 | Getting Big Name Customer Case Studies and More Listener Questions (with Ruben Gamez) Claude Sonnet 5.5 Customer testimonials published by Anthropic for Claude Sonnet 5.5 2026 in LLMs (so far) Comment: S3 Is the Future, S3 Is the Past El código generado por IA ya compite con el código humano — Daksh Gupta, Greptile Salga del camino del modelo — Kevin Hou, Google DeepMind La ingeniería de software se está convirtiendo en ingeniería de fábrica — Zach Lloyd, Warp De cero a uno en seguridad de la IA: Mike McCormick, de Halcyon, sobre el lanzamiento de 30 nuevas organizaciones y el cuello de botella de los fundadores WorldPrompt de Runway y la ingeniería de mundos en tiempo real TBPN: John Coogan sobre agentes personales y publicidad Our Investment in Ando: Modern Messaging for Teams and Agents Cómo la ciencia abierta puede ayudar a los investigadores a prepararse para la próxima pandemia Bootstrapping From a $500K Goal to a $50M Company What Comes After Transformers? De AGENTS.md a la implementación empresarial con Nick Kuhn Rethinking Communication for Human and AI Teams | Emergence Capital Comment: We just shipped support for the ugliest part of HTTP: Vary YouTube CEO Neal Mohan: Why We’re Betting On AI And Not Afraid Of It Tool: Gemini 3.8 TTS Playground Ingeniería de diseño con Maggie Appleton Parsing “Can” from “Should”: How Netflix's Product Team Got Thousands of Creatives to Trust an AI Overhaul 🔬 La bioseguridad es una carrera armamentística de IA - Eric Nguyen (CEO, Radical Numerics) How to train your own Jev for $17 TBPN: John Coogan sobre agentes, interfaces de aplicaciones y publicidad NVIDIA Launches DSX Ready to Qualify Power and Cooling Products for AI Factories From Enablement to Execution, Egypt’s AI Ecosystem Reaches Production Scale The Overhang Sin código sigue siendo código: Wade Foster, CEO de Zapier, sobre herramientas headless, Zapier MCP y Automation Bench Habilidades en IA con Matt Pocock Inside OpenAI’s First Chip Cómo lograr visibilidad en la búsqueda con IA Ali Ghodsi sobre el aprendizaje como CEO y la evaluación de prácticas de gestión Anton Leicht sobre despliegue de IA, disrupción económica y riesgos Aaron Levie, de Box: sobre reinventarse en la era de la IA y la difusión empresarial The Home Depot When Everyone Is 10x More Productive, No One Is Voice Agent Function Calling: Real-Time Data Lookup Guide Investigadores de IA debaten cuán cerca estamos de la auto-mejora recursiva One resignation turned the embers of AI fear into a wildfire Agentes de uso informático y el futuro del Internet agéntico Construyendo Codex con Tibo Sottiaux Simpler, outcome-based AI pricing AI, tools and transformation — Benedict Evans Forking Cal.com to closed source (Changelog Interviews #685) Katie Parrott sobre el uso de ChatGPT para la escritura y la reflexión profesional From enterprise search to enterprise context: what AI agents actually need Ajeya Cotra sobre persistencia de agentes, coordinación y trampas en benchmarks Haciendo extraordinarias a las ciudades: Nick Noone y Ben Rudolph, de Peregrine Exploring Static Embedding Retrieval Parag Agrawal, de Parallel: construyendo una nueva web para agentes de IA Real-Time Voice AI Stack for Agents: Architecture Guide Release governance: guardrails for agents at scale An Agent Is Just an LLM in a For-Loop When AI art has no author: MIT study finds generated images often can't be traced to any training data | MIT CSAIL Quienes entienden no construyen; quienes construyen no entienden | CrewAI GitHub Copilot app for Beginners: Write your first prompt Disney: El Renacimiento y el Imperio Reconstructing how OpenAI agents attacked Hugging Face El CEO filósofo | Kareem Amin, cofundador de Clay Why Agentic Systems Need Ontologies — Frank Coyle, UC Berkeley Yash Poojary sobre la automatización de experimentos de crecimiento en Every Chris Pedregal sobre startups y el trabajo más allá de las notas de reuniones Tarek Mansour, de Kalshi, contra el Gobierno Federal Harness Engineering for Self-Improvement Cartesia | A Guide to Choosing Voice AI Models The Walt Disney Company Demis Hassabis on Scientific Discovery and Personal Agency Jean-Baptiste Kempf sobre calidad del código de código abierto, mantenimiento y compilaciones seguras How to make remarkable videos with Seedance 2.0 – Replicate blog Jensen Huang sobre seguridad de agentes de IA, liderazgo y confianza Orchestrating Self-Evolving Agents with CrewAI and NVIDIA NemoClaw | CrewAI Palo Alto Networks con Nir Zuk y Nikesh Arora: el rencor que transformó la ciberseguridad Bolt con Markus Villig: del bootstrapping en Estonia a líder global en movilidad Supercell con Ilkka Paananen: cómo un cambio temprano condujo a ‘Clash of Clans’ y ‘Brawl Stars’ Lyft CEO David Risher on paying drivers more and the shift to robotaxis Trade Winds: The Rise, Reckoning and Reimagining of Vlad Tenev | Index Ventures 12-Factor Agents: Patterns of reliable LLM applications — Dex Horthy, HumanLayer Gen AI Present and Future: A Conversation with Jim Swanson, CIO at Johnson & Johnson | Greylock Dario Amodei, Amanda Askell y Chris Olah sobre el desarrollo y la seguridad de la IA Duolingo CEO Luis von Ahn thinks AI has a lot to teach us Pieter Levels sobre la creación autónoma de startups, los modelos de imágenes con IA y el desarrollo independiente Runway Research | Introducing General World Models Año de publicaciónTodas las fechas 2026 2025 2024 2023 Filtrar esta colección 1 personas · 1 fuentes · 1 opiniones expresadas
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AI-assisted knowledge work evaluation Elige una perspectiva y vuelve a la conversación original.
Evangelos Simoudis 12 sept 2026
The human orchestrator must explain how AI-generated work was produced Leer la fuente de evidencia ↗ EN CONTEXTO AI-assisted knowledge work evaluation 1 opiniones expresadas
01 The human orchestrator must explain how AI-generated work was produced Evangelos Simoudis 2026-09-12 Los sectores iguales orientan la lectura, no indican una clasificación.
01 The human orchestrator must explain how AI-generated work was produced Evangelos Simoudis · 2026-09-12 Perspectivas 1–1 de 1 · Fuentes más recientes primero
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The human orchestrator must explain how AI-generated work was produced In AI-augmented knowledge work, the human acts as an orchestrator who must understand—and be able to explain—how AI-generated outputs were produced; inability to do so signals quality issues.
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Evangelos Simoudis · 12 sept 2026
When Everyone Is 10x More Productive, No One Is Extracto original
Being able to do this, again, to me, is the human as orchestrator. But as orchestrator, you need to be able to understand the connections. Even if the machine doesn’t give you the connections explicitly, you better be able to say, “Here’s how this thing was arrived at.” If you cannot, I think there are issues with the quality of your work. Contexto Yeah.
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