Anil C Nagalla

With AI adoption and deeper integration into enterprise products, the world moves toward being collectively intelligent. First movers will have a distinct advantage. Fully backward-integrated AI companies are best positioned to win on economics.

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Oracle's Jenny Tsai shares about product innovation across Oracle's database portfolio to support the rapidly growing demand for AI, cloud services and data sovereignty. Read it here: https://lnkd.in/gC2ts6J8

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Salesforce's VP Gary Lerhaupt, VP Product Architecture weighs in on Google's A2A protocol in enabling intelligent communication and collaboration between AI agents.

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One line in this piece tends to surprise people, especially when it comes to system evaluation: “𝘐𝘧 𝘰𝘶𝘳 𝘣𝘦𝘯𝘤𝘩𝘮𝘢𝘳𝘬𝘴 𝘴𝘩𝘰𝘸 𝘮𝘰𝘳𝘦 𝘵𝘩𝘢𝘯 𝘢 50% 𝘴𝘶𝘤𝘤𝘦𝘴𝘴 𝘳𝘢𝘵𝘦, 𝘸𝘦’𝘳𝘦 𝘱𝘳𝘰𝘣𝘢𝘣𝘭𝘺 𝘯𝘰𝘵 𝘣𝘦𝘪𝘯𝘨 𝘢𝘮𝘣𝘪𝘵𝘪𝘰𝘶𝘴 𝘦𝘯𝘰𝘶𝘨𝘩.” That mindset grew out of many small failures and iterations. The point isn’t lowering the bar for quality. It’s raising the bar for how we measure systems and drive real improvements. This article reflects on that journey, from Flash Fill to today’s agentic systems, and why user flow, system evaluation, and human judgment matter in practice. Thanks to Anshika Mathews for capturing this so thoughtfully.

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“San Francisco is the global hub of innovation, technology, and venture capital,” Lurie said in a statement. “And with yet another investment from leading institutions of higher education, we are accelerating our city’s recovery and strengthening our city center as a place where people live, work, play, and learn.” 

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#AIJourneyWithMaheshRaja post #8 its been a while I wrote on my core ( AI ) Most of you know that like in any organization we at Conscendo paving our way to become an AI driven organization on par with Industrial paradigm shift that is happening, We too feel the pressure of "AI FOMO ( Feelingof Missing Out )." We see the headlines and feel we need to implement something immediately. But rushing in without a roadmap often leads to failed POCs and, more importantly, lot of invalid learning and may be a risk-scoring of breach of customer trust Here are my three main takeaways on how to approach AI the right way: 1. Identify Bottlenecks, 2. Plan for Fool proof Trust Layer 3. Nominate an AI focal point in the organization 1) In my experience with AI, The most successful AI implementations don’t start with the technology; they start with the team on the ground, check "Where and What are our bottlenecks", 2.) If AI team can’t guarantee that our proprietary data won’t be used to train public models, the risk to our brand is too high. 3) Appoint an AI Champion AI isn't just an "IT project." It requires a Single Point of Contact (SPOC) who understands both the business goals and the technical limitations. Without a dedicated champion to navigate the "hallucinations" and refine the outputs, projects often stall at the demo stage. Let’s stop racing to be first and start racing to be the most reliable. I’m curious to hear from my network-are you currently testing AI in your workflows? What has been your biggest hurdle so far? #ArtificialIntelligence #SMB #DigitalTransformation #BusinessStrategy #Leadership #AIAdaption #Salesforce #ConscendoTechnologies

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