KINESSO

🚀 Amazing turnout for our Data Engineer Things NYC meetup #2! Around 60 data engineers joined us for the NYC chapter. The energy was fantastic great discussions, real-world challenges, and meaningful connections. Huge thanks to Capital One , Michael Lenner , Amanda Yip , Lisa N. Cao , Databricks , Mike Xu , Ryan Boyd 🐤 , MotherDuck , Xinran Waibel , Yaakov Bressler, Ophelia S. , and everyone who helped make this event a success! This is just the beginning. Can't wait to see this community grow! 📈 Get involved: - 📅 Subscribe to our calendar: https://lnkd.in/g-BK2Git - 🌐 Visit www.dataengineerthings.org for photos and more - 📺 Talks coming soon to YouTube: https://lnkd.in/edRHTZxR - 🌐 Join our NYC Slack channel: https://lnkd.in/ejVZcMRq - 🎤 Submit a talk: https://lnkd.in/gw8WJKbz We're planning small summer events and a bigger event this September. Stay tuned! Want to host, partner or have suggestions? DM me on Slack or LinkedIn. #DataEngineering #Community #Meetup #DataEngineerThings

Got tired of repeating the same Google Ads audits every month. So I built a system to do it properly — and consistently. It’s called AdAudit AI. Upload a Google Ads export, and the platform analyses the account across: - wasted spend - account structure - conversion tracking - bid strategy - negative keywords - audience targeting But the key difference isn’t the analysis. It’s what happens after. The system doesn’t just list observations — it prioritizes issues by estimated business impact, with clear reasoning and next-step recommendations, delivered in minutes instead of hours. The most important design decision was around trust. Most AI tools try to generate both metrics and insights. But large language models are not reliable when it comes to producing or inferring precise performance numbers. Even small inconsistencies or assumptions can completely distort analysis. So I separated the system. All calculations (spend changes, CPA shifts, benchmarks, and impact estimates) are computed first using fixed logic. The AI never generates or guesses any numbers. Its role is only to: - interpret verified data - identify meaningful patterns - explain what’s driving performance - suggest what to do next This keeps the analysis grounded and consistent, while still leveraging AI where it’s strongest — reasoning and interpretation. After 7 years in paid media, I realised the real challenge isn’t finding data. It’s consistently identifying what actually matters inside large, messy ad accounts. This product is essentially years of audit experience translated into a repeatable system. Still early. But exciting to finally see something that started as an internal workflow become a real product. Curious: What’s the most repetitive manual process your marketing team still spends hours on every month?

🐶 Despite my very clear instructions to stop aging, my dogs continue to collect white hairs. They’re both rescued mutts, so how can I know what to expect with their lifespans? We completed Wisdom Panel s for them a few years ago, which helped explain some of their behaviors, but my big question still remained - (assuming no freak accidents) how long might my mutts live? 💡 Equipped with their breed mix data, I couldn’t find anything that could help me with my big question, so I built the Mutt Mix dashboard that provides directional answers for expected lifespan, height, and weight ranges. And bonus - you can plug your own mutt’s info into it, too. 🐾 🎾 Play with Mutt Mix here: https://lnkd.in/gDi3hjuQ 📱 Extra bonus - I also made this dashboard mobile-friendly for those with curiosity outside of the medium screen environment. #DataViz #Tableau #Dogs

Great afternoon at the PatientPoint® Upfront yesterday and an honor to share the stage with Linda Ruschau , Sumana Rajagopal , Brittany Blair and Melissa Gordon-Ring . Was also inspiring to hear Olivia Munn's story, and learn more about the need to get the word out for the High Risk Assessment for Breast Cancer, which can help save lives: https://lnkd.in/eWUiBhJG

Presenting at NorthSec next Friday with Max CM . Commit, Push, Compromise: Attacking Modern GitHub Orgs covers the full attack chain through GitHub organizations. Device-code phishing, GITHUB_TOKEN abuse, workflow exploitation, policy bypass, and how attackers stay quiet when telemetry is limited. Useful for both red teams and defenders. Friday, May 15 at 10:00AM EST https://lnkd.in/ezgq2uSB

🏏 From Not Knowing the Rules… to Loving the Game ☀️🍻 A bit of a personal one… Zach, my lad, has absolutely fallen in love with cricket. And I’ll be honest, I know next to nothing about it. As far as I can tell, it’s a game played in the sunshine, with a bar nearby, so I’m fully on board already 😄 But seeing how much he enjoys it, the commitment he’s putting in, and the buzz he gets from being part of a team, it’s brilliant to watch. That’s what it’s all about. Even better, he and a few of his teammates have been selected for the Derbyshire County Cricket Club junior development team this season. Proper proud moment. So yeah, I might not understand LBWs or field placements just yet, but I do understand how much this means to him. Roll on the season, can’t wait to get started 👊🏏

Everyone talks about AI agents. Nobody explains the stack underneath them. Let me fix that. 🔌🧠 I've been using MCP + Skills daily and the mental model finally clicked: 🔌 MCP = the pipes. One standard protocol so AI can talk to Snowflake, Jira, AWS, GitHub. 🧠 Skills = the brains. Reusable logic that decides which tools to call and in what order ⚡ Together = an AI agent that actually ships to production The data flows both ways. That's the part that makes it real-time, not just a fancy wrapper. Swipe to see the full data flow diagram 👇 What's the first thing you'd wire up via MCP? #MCP #AIAgents #ModelContextProtocol #ArtificialIntelligence #DataEngineering #LLM #AIArchitecture #BuildingWithAI #AI

That’s a wrap for the Data Engineering Open Forum! 🎉 Huge thanks to the Program Committee and the Data Engineer Things team for organizing such a fantastic event. Talks will be on our YouTube channel soon. ( https://lnkd.in/eDsgn4un ) Up Next: NYC Event on May 14 🗽 We’re looking for speakers and volunteers! 🗣️ Speak: Apply here: https://lnkd.in/gyBjkrVQ 📅 RSVP: https://luma.com/aqxn7jea 🤝 Volunteer: DM me if interested. Don't miss out—subscribe to the newsletter & meetup group: 📰 DET: https://lnkd.in/etr4cqZU 👥 Meetup: https://lnkd.in/g-BK2Git cc: Xinran Waibel , Amanda Yip , Michael Lenner #DataEngineering #NYCTech

Proud to be featured in Media Marketing discussing a strategic shift brands can no longer ignore: the growing role of alternative platforms in today’s media ecosystem. In a fragmented attention economy, competitive advantage comes from balancing scale with contextual relevance, audience quality and content adaptability. Glad to share this perspective alongside Benjamin BONNET , Bastien Glineur , Arthur Corne . https://lnkd.in/d8Hv8VKW