Ayush Parashar

At New Relic, during the just concluded AI Innovation Week, Teja Swaroop and Mayur Gupta from the Docs team collaborated with Gaurab Manandhar and Abhinav Tiwari to use AI to bring efficiencies into the documentation process. Out of 75 projects, this one made it into the top 13 (yeah, we're ain't superstitious here). It's not human-or-AI but human+AI that is most exciting.

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ambaricloud: 108 recipes. 🥭 https://lnkd.in/gS6fuAtu Ravi Kiran Gurram Anil Koripelly Bhushan Lakhe Raja Purkayastha When this recipe e-book was first published on January 1, 2025, our goal was to give engineers, architects, and data practitioners a hands-on guide to Apache Iceberg. In the months since, the pace of change has been remarkable. Platforms such as Snowflake, Databricks, Dremio, RisingWave, ClickHouse, Cloudera, Lakekeeper, Trino Software Foundation, and Amazon Web Services (AWS) have delivered significant new integrations, and Apache Iceberg itself has reached version 1.10.0, introducing capabilities that reshape how practitioners interact with the format. To reflect this momentum, we are undertaking a ground-up rewrite. Our priorities include: ✅ Iceberg 1.10.0 alignment and deprecation cleanup – removing outdated recipes that no longer reflect best practices while upgrading all demos, examples, and exercises to incorporate the changes introduced in Iceberg 1.10.0. For example, Snowflake’s support for catalog-linked databases to external catalogs makes earlier object integration recipes obsolete. ✅ Ecosystem validation – testing and refining recipes across Databricks, Snowflake, Dremio, and AWS to ensure seamless interoperability with Iceberg 1.10.0. We expect this rewrite to take two to three months. Once complete, this edition will provide readers with a technically accurate, future-ready reference for Iceberg 1.10.0 and its surrounding ecosystems--Snowflake, Databricks, Dremio, RisingWave, ClickHouse, Cloudera, Lakekeeper, Trino Software Foundation, and Amazon Web Services (AWS) Please 🕺 suggest 🔪 comment 🥃 recommend ✅ Spark Variant ---Iceberg1.10.0 spports now. https://lnkd.in/gBmaNrPH

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System-level issues cause 60–70% of automation downtime. Fixing bots isn't always about the bot—it's about what’s around it. Accelirate Inc. | Mike Booker | Harsh Thakar | Pranav Agrawal | Saatvik Gupta #AutomationFailure #agenticAutomation #BOTs #AI #RPA #AIOps #BotManagement #SystemReliability #DigitalOps #ProcessAutomation #AutomationChallenges #IntelligentAutomation #TechOps

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re:Invent Day 1 is done and it was packed! My day began with a roundtable with some of our best partners talking about how we can better help customers migrate and modernize their AI workloads and use cases. Then Priya Arora and I presented on-stage on how Agentic AI is opening opportunities for partners, from ISVs and SIs, to startups. We shared data from our survey we did with BCG showing the trends in customer adoption of AI, focusing on the industries and use cases with the highest momentum. We also uncovered areas where customers need the most help and support as they roll out their agentic use cases. After that I sat down with 3 key partners, grabbed lunch with a few AWS peers I don't get to see often enough, and had a lot of ad hoc hallway meetings. (It's hard to walk 10 feet at re:Invent without seeing someone you know) But my highlight was launching the new AI Competency and Agentic AI categories for partners. I had a chance to join the AWS OnAir team to talk about it. My team was the driving force behind the launch and I'm proud of what this means for our partner community. We spent months listening to partners tell us they needed a way to stand out in customer conversations around agentic AI. The new AI Competency creates three distinct specialization paths. Agentic AI Applications recognizes partners delivering production-ready autonomous systems. Agentic AI Tools validates partners providing the infrastructure and tooling that makes agent development possible. Agentic AI Consulting Services distinguishes partners with proven expertise helping enterprises design, build, and scale agentic deployments. Each path requires demonstrated technical depth and validated customer outcomes, not just certifications or marketing claims. We launched with 60 partners who achieved the AI specialization. That's the highest number of launch partners in any AWS Competency program so far. Partners like Loka, Anthropic, LangChain, and Mission are already proving their ability to deploy AI systems that handle real business processes autonomously. That validation matters when enterprises are making critical technology decisions. Partners achieving these specializations gain access to funding, co-marketing resources, and priority placement in customer engagements. But what matters most is the market differentiation. When customers are evaluating dozens of partners claiming agentic AI expertise, this competency provides a clear signal about who has actually done the work. For enterprises evaluating partners, this competency provides the differentiation signal you need. These partners have solved the hard problems of moving agents from demo to production, from single use case to enterprise platform. The timing matters. Enterprises are moving past whether to deploy agentic AI and into how to do it at scale. Partners with proven expertise become increasingly valuable as deployment complexity increases. That's what makes this competency so important.

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Analytics India Magazine recently interviewed Rohit Vyas & I, where I reflect upon something we see every day with our customers: AI ambitions are rising fast, but batch data is holding many teams back. What excites me most is seeing AI agents move beyond chat interfaces to operational intelligence: detecting issues, triggering actions, and improving experiences autonomously. That’s the frontier we’re building towards with Confluent Intelligence. Read the full interview here: https://lnkd.in/gxuWWJGs

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Jyoti Bansal joins Mudassar Malik for the Season 4 premiere of The Builders Playbook to share an honest look at scaling without losing quality, speed, or accountability. They dig into Jyoti’s journey from engineer to founder, the investor question that pushed him to go all-in on AppDynamics, and the lessons he brings to building at Harness today. You’ll hear about: ✓ Turning one focused use case into a platform. ✓ Harness’s “startup within a startup” model. ✓ Why small, AI-enabled teams move faster. 🎧 If you’re building or scaling, this one’s packed with practical takeaways: https://lnkd.in/enrHvuU3

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Unpopular opinion: You can run a $1M+ business… And still operate like a hot mess behind the scenes. I see it all the time: → People forget to follow up → Email inbox is a big mess → Too much time spent sending emails by hand It’s not because founders don’t care. It’s because their “systems” are really just duct tape and wishful thinking. Making money doesn’t mean your business runs smoothly. If you grow without good systems, things will break. I talked about this and how automation can help in my US Insider article. Check it out here: https://lnkd.in/dP6q9bk4 p.s.  sounds familiar? Probably time to rethink how your backend runs.

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When leaders who built Silicon Valley and India’s digital backbone talk about AI’s future, it’s a masterclass for the builders of tomorrow. AI: Disrupt or Design? 🚀 Featuring insights from Vinod Khosla and Nandan Nilekani In an era where every engineer is being challenged to rethink the future, getting perspectives from the minds shaping technology itself is not just valuable — it’s essential. I’ve put together a crisp slide deck summarizing contrasting views from two legends: Vinod Khosla: Betting big on AI disruption, massive automation, and Universal Basic Income. Nandan Nilekani: Championing human+AI collaboration, scalable adoption through digital public goods, and responsible innovation. Engineers, technologists, creators — this is your cue. Whether you choose to disrupt or design, the future is yours to shape. #AI #Engineering #TechLeadership #Innovation #FutureOfWork

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