Karthik Narain

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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Vianai Systems, Inc.'s badass CTO, Navin Budhiraja, doing his thing. Insightful interview on the technological, professional and societal implications of AI and the need for enterprise grade AI technology to truly drive business performance.

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Delighted to share my perspective in this new piece from Karat on how GCCs in India can scale engineering capability with quality and consistency. If you're building or expanding a GCC, this is a timely read.

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Exciting partnership to amplify our Go-To-Market for Intelligent Product Engineering and Design with HCLTech and Siemens Digital Industries Software: Developing a scalable, flexible and intelligent application lifecycle management solution "ALMate" on Amazon Web Services (AWS). Key features: ⚒️ GenAI-powered quality analysis: Utilizing cutting-edge Generative AI technologies and frameworks like Retrieval Augmented Generation [RAG], the solution not only evaluates the quality of requirements against International Council on Systems Engineering (INCOSE) and specific organizational standards but also provides prescriptive recommendations for requirement enhancement directly to the authors 🔅 Automated requirements generation: ALMate speeds up the creation of new requirements, aiding engineers throughout the authoring process while ensuring compliance with industry standards ⚙️Test generation and traceability: Addressing one of the biggest challenges in ALM is ensuring full traceability between requirements and tests. ALMate automates the generation of structured test cases from requirements and ensures that all necessary testing is linked back to the corresponding requirements, maintaining traceability throughout the lifecycle 📒 Intelligent summarization and translation: ALMate can intelligently summarize documents and translate requirements into various languages, ensuring global teams are aligned, which accelerates accurate decision-making and collaboration If interested, reach out to HCL, Siemens or AWS team to learn more! Ashutosh Singhal Chandan Murthy Sunny Billava Rishi Sharma #polarion #siemens #aws #manufacturing #modelingandsimulations #Innovation #DigitalTransformation #MBSE #SystemsEngineering #DigitalThread #DigitalEngineering #RequirementsEngineering #GenerativeAI #AgenticAI https://lnkd.in/gAWwZta8

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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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