Dave Moore

"What data is Claude accessing?" Vendia MCP Gateway provides enterprise-grade visibility that legacy integrations can't match: ✅ Connect MCP servers, APIs, SaaS services, and file storages ✅ No servers to maintain or deployments to manage ✅ Real-time visibility into every agent request ✅ Granular permission tracking across data sources Stop treating AI data access like a black box. See how observability-first infrastructure changes the game. 👉 Experience MCP Gateway: https://vendia.fyi/4pZtEou #AIObservability #DataOps #EnterpriseAI #MLOps #AIGovernance #MCP #SecureAI

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Is your "modernization" just a tech refresh? Putting new technologies on an existing design is like strapping a turbocharger onto a horse-drawn carriage - flashy, yes, but you’re still being pulled by the same old horse. I saw teams strap a 50-node Kubernetes cluster onto a legacy monolith and still wrestle with sticky sessions hacks, or platforms that were lifted from RDBMS into NoSQL but still use the same relational pattern, creating massive cost and almost zero upside. Kubernetes, NoSQL, cloud, or other modern technologies can be game-changers when they sit on a solid architecture. Bolt-on approaches, however, rarely deliver real value. Here’s how I’d approach “modernization” differently: 1️⃣ Revisit the foundation Start with your business goals and core workflows. What SLAs really matter? What’s your target time-to-market for new features? Which user journey drives the most revenue or risk? Without that clarity, every tech decision is guesswork. 2️⃣ Rethink your architecture Draw clear service boundaries (bounded contexts), data flows, and resilience patterns. Do you need event sourcing? Circuit breakers for payment retries? Model those first. 3️⃣ Map technologies to your design Now - and only now - pick your tools. Use Kubernetes to orchestrate stateless microservices, message brokers for asynchronous communication, NoSQL for high-throughput event stores, and cloud auto-scaling for bursty traffic, and so on. Each tech becomes a precision tool, not a blunt instrument. When you start with “What do we actually need?” instead of “What’s hot right now?”, you build systems that evolve - and deliver real ROI: faster releases, lower costs, and fewer fires. How have you tackled modernization in your organization? I’d love to hear your stories and any lessons learned! 👇 #ArchitectureFirst #Modernization #Kubernetes #NoSQL #CloudNative #DigitalTransformation #TechStrategy #Azure #AWS #GCP #Kafka

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Key Takeaways: ✅DeltaStream Unifies Streaming and Batch Workloads Into a Single, Serverless Analytics Platform. ✅- Reduce Complexity, Reduce Costs by 50%, and Improve Latency of Pipelines, - Accelerates Time to Insight, - Simplifies Your Stack, ✅- Integrates Seemlessly with Snowflake and Databricks. Hojjat Jafarpour, CEO, Founder, DeltaStream.io  Hojjat's LinkedIn Page:  ✅ https://lnkd.in/gb7m5WqJ  DeltaStream LinkedIn Page:  ✅ https://lnkd.in/gDwXqKuR  DeltaStream Website:  ✅https://lnkd.in/gJdg_Be6 #deltastream #datastreaming #realtimedata #serverless #hojjatjafarpour #datatools #startup #startupceo Walter Bacon, Founder, Walter Bacon, Inc. Recruiting  ✅ Recruiting Firm Specializing in Early Stage AI and Developer Tools Startups.  ✅Helping CEOs and Founders of AI Startups Achieve Their Growth Goals by Recruiting High-Impact Engineering and GTM ICs and Leaders with Domain Expertise. Walter's LinkedIn:  ✅https://lnkd.in/gcWPyjmK  Walter's Website:  ✅https://lnkd.in/gEPW3ywZ  Walter's YouTube Channel: (My AI Startup CEO Interviews)  ✅https://lnkd.in/g8fBNZWj #walterbacon #friendsofwalterbacon #recruitingforaistartups #aistartupjobs #recruiters #recruiting #airecruiting #engineeringrecruitment #engineeeringrecruiter #siliconvalleyrecruiter #startuprecruiter Timestamps:  0:26 - Please Talk About Your Background at Confluent and the Unique Product You Created While There - Built the Stream Processing Platform. ksqlDB 1:30 - Originally Founded DeltaStream as the Cloud Native Version of ksqlDB 1:59 - What Are the Benefits of DeltaSteam Today? - Reduce Complexity, Reduce Costs, and Improve Latency of Pipelines - Cuts Compute Costs by 50% - Accelerates Time to Insight - Simplifies Your Stack - Integrates Seemlessly 4:06 - Can You Talk About Your Real-Time Native Data Streaming Inside of Snowflake and Databricks? 5:40 - Real-Time GenAI Isn't About Faster Models, It's About the Right Architecture 8:21 - Without Real-Time Data the AI Agent Is Blind 12:20 - Who is an Ideal Prospect for You? 13:19 - How Would You Like People to Engage and Learn More About DeltaStream?

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AI is crossing a real line. Not better answers but a shift from assistance to ownership. We’ve entered an era where AI can take a goal, plan the work, operate across systems, and deliver progress. In wealth management, that matters because the constraint has never been insight; it’s coordination and review. Think of AI as a junior operator: prepping, assembling, maintaining, executing. That doesn’t replace judgment. It lets judgment compound. The question isn’t how to automate tasks. It’s how to safely delegate outcomes. The firms that scale will think in leverage. The mindset shift matters more than the tool.

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By 2027, 30% of financial transactions will be initiated by autonomous AI agents. Key takeaway from this Fall's @FDX Summit: Your API specs must be perfectly accurate. AI agents can't adapt like humans—when specs don't match implementation, agents fail. Traditional banks have a trust advantage. The question is whether you'll build agent-ready infrastructure to leverage it. Full insights: https://lnkd.in/g3QV4Jj4 #OpenFinance #AIAgents #APIs Financial Data Exchange Laurent Van Huffel Tyk Cloudflare APIContext David O'Neill

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Your CI/CD bill is not exploding because of “expensive runners,” it is bleeding out through flaky tests, over-parallelized jobs, and slow feedback loops that quietly tax every deploy This piece shows you how to redesign pipelines so you cut compute waste, shrink queues, and speed up developer flow without adding yet another approval gate or YAML religion Full breakdown in the comments. #DevOps #CICD #PlatformEngineering

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Tired of long CI builds and rising compute costs? Coda was too. They trialed Aspect Workflows, saw a 10x improvement in build times and a 67% reduction in compute costs, and decided to roll it out more broadly. "We went from having significant limits in CI and tools to where the limits are now just due to our code." — Neal Norwitz, Software Engineer at Coda Read more about the challenges they faced and the results they saw: https://lnkd.in/eA_pwcDQ

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Scaling your startup on AWS without burning through your budget? Sounds like a dream, but AWS actually hands out credits and runs programs that can save you serious cash - if you know how to grab them. This guide breaks down how startups can tap into the AWS accelerator, snag free credits, and turbocharge growth without sweating over the cloud bill. Spoiler: it’s less complicated than you think, and skipping this means leaving money on the table. #AWS #Startups #CloudComputing #TechGrowth #Entrepreneurship

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Integrating large language models and powerful algorithms into your workflows is a massive undertaking. All that hard work can be undermined if the outputs fall short, quickly eroding stakeholder interest and trust. That's why effectively evaluating LLMs and algorithms is crucial. From initial prototypes to production, and through continuous experimentation and benchmarking, mastering evaluation ensures these advanced tools truly deliver on their promise. #LLM #Algorithms #AI

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Somewhere along the way, “move fast” became “just build it.” Agile was meant to accelerate value, not velocity at any cost. To me it has become the new Microservices conundrum. In many organizations, the pendulum swung too far, they are sprinting past architecture and straight into technical debt. The result? Rework, unclear ownership, brittle integrations, and solutions that miss stakeholder needs entirely. Architecture doesn’t slow delivery, it stabilizes it. It gives teams clarity, alignment, and a framework for transparent technology decisions. When done right, architecture turns speed into sustainable velocity, even though it is often viewed as extra work or documentation for documentations sake. Have you seen the “just build it” culture catch up to an organization before? What was the turning point that brought architecture back into focus?

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Openclaw (formerly Moltbot, formerly Clawdbot) is genuinely impressive — an open-source AI agent you run on your own hardware that can browse the web, send emails, and act autonomously on your behalf. The capabilities are real, and the project deserves every bit of attention it's getting. I mean that. I also don't think I can use it outside of a sandbox. Not because it doesn't work — it does. The problem is trust, and specifically the kind of trust that comes from understanding exactly what a system is going to do on your behalf before it does it. I've been building something similar on my own, and my version is objectively worse — fewer features, less polish, nowhere near ready for anyone else to touch. But I wrote it, so I know what it's going to do and what it isn't. With Openclaw, I'm not there yet. The capabilities are ahead of my ability to predict and contain them, and in a world of unexpected token costs and agents that can take real actions with real consequences, that gap matters. This isn't a knock on Openclaw. It's a statement about where we are as an industry. We're building tools that are more capable than our trust infrastructure can support, and each of us has to figure out where our personal comfort line is. Right now, mine is "I built it and I understand it." That bar will move as tooling and guardrails mature. I'm very much looking forward to what comes next.

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Houston, Texas data engineer Amatullah Kapadia at Amazon Web Services builds secure ETL pipelines and analytics workflows. #tech #innovation https://lnkd.in/gX7-H2Dt

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