47% of failed AI projects trace back to bad data. Not the model. Not the team. The foundation. Our 2026 State of Data Analysts report explains why ROI stays out of reach. Read it: https://
ow.ly/UiUH50Z1guU
ENTERPRISE AI
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Data Quality as the Foundation for AI Project Success
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Google Launches AI-Powered Information Agents for Real-Time Monitoring
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This is the one that should get your attention.
— God of Prompt (@godofprompt) 20 mai 2026
Google is launching information agents that work in the background 24/7.
You set a question. The agent monitors blogs, news sites, social posts, and real-time data across finance, shopping, and sports. It alerts you when something… https://t.co/K1eqNxIBmMThis is the one that should get your attention. Google is launching information agents that work in the background 24/7. You set a question. The agent monitors blogs, news sites, social posts, and real-time data across finance, shopping, and sports. It alerts you when something
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Closing the industrial data gap for AI operations
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Most industrial AI data was scraped from the internet, not from boats, cars, or plants actually running. That context gap is exactly what MQTT-based platforms like Coreflux are racing to close before AI can act on real operational data. #coreflux_ai pic.twitter.com/6FdXX05yZB
— Lucian Fogoros (@fogoros) 20 mai 2026Most industrial AI data was scraped from the internet, not from boats, cars, or plants actually running. That context gap is exactly what MQTT-based platforms like Coreflux are racing to close before AI can act on real operational data. #coreflux_ai
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The Shift from Monitoring to Action in Enterprise AI
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I agree, the shift from monitoring to action is where enterprise AI starts to create business value. Real-time infrastructure gives teams the speed and context they need.
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Podcast episode on how AI is transforming business
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He publicado un episodio en @ivoox
: "#1133: La IA ya está cambiando tu negocio (aunque todavía no lo quieras ver) #podcast -
30 Agents Every AI Engineer Must Build – production-ready agents
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30 Agents Every AI Engineer Must Build — Build production-ready agent systems using proven architectures and patterns: http://
amzn.to/41ckg6z v/ @PacktDataML —
What you will learn:
Deploy production-ready agent systems that scale securely and reliably
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Major AI platforms converging or diverging: who will win?
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The gap between what you can do on ChatGPT/Codex and Claude/Code/Cowork is closing, as Anthropic & OpenAI converge on a single experience. Google's experiences are diverging: Studio & Gemini & Antigravity & the other Google AI apps are increasingly different. Which will win?
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User critique: Gemini models not ready for enterprise
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I find this continually frustrating. Gemini 3.5 Flash is excellent, as is Gemini 3.1 Pro. But you absolutely cannot use them for any serious purpose right now, especially for any enterprise work. Compare to Claude or ChatGPT: you can understand what the model did & how to correct
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Critique: Gemini hides its thinking traces and provenance
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Google has hidden thinking traces on the Gemini site. You have to use the 3 dot menu to pull up summaries, which are so minimal as to be unusable. Did it do web searches? Did it check results? You can't tell. This makes Gemini unsuitable for any serious work you need correct.
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Google launches Gemini 3.5 Flash, a step toward digital employees
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Google acaba de lanzar Gemini 3.5 Flash.
— Nico (@nicos_ai) 19 mai 2026
Y estamos mucho más cerca de los primeros empleados digitales reales.
→ planifica tareas complejas durante horas
→ divide el trabajo entre subagentes
→ trabaja sobre codebases enormes
→ usa herramientas y ejecuta acciones
→… https://t.co/L2qsKVSqDS pic.twitter.com/wBsqThLNTsGoogle has just launched Gemini 3.5 Flash. And we're much closer to the first truly real digital employees. → plans complex tasks for hours → divides work among subagents → works on massive codebases → uses tools and executes actions → maintains massive context