Arsen Vladimirskiy

Still confused between MCP, A2A, and Functional Calling? These three approaches are reshaping how LLMs and agents operate at scale, but each one solves a very different problem. Let’s break it down 👇 1. Model-Context Protocol (MCP) MCP manages dynamic context windows across enterprise LLM infrastructure. It retrieves prior memory, history, and metadata to personalize every response without hardcoding logic into prompts. 2. Agent-to-Agent Protocol (A2A) In A2A, agents talk to each other directly using shared protocols. Think of it as collaborative problem-solving between specialized local agents, especially useful in multi-agent ecosystems. 3. Functional Calling Here, an LLM acts like a planner. It decomposes a task (e.g., comparing market caps), generates a Directed Acyclic Graph (DAG) of subtasks, and then sends each task to appropriate tools (math, search, APIs) for execution. Conclusion - MCP is about managing context, - A2A is about agent collaboration, - Functional Calling is about task execution. Mastering all three is key to building powerful, production-ready AI systems. Save this visual for your next AI project!

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Your hosted/managed Kafka is not as hosted/managed as you thought and a lot of costs add up quickly as well as frustration? :-) Read At first glance, cloud-hosted Kafka looks easy. But if you’re still rebalancing partitions, scaling infrastructure, patching versions, and troubleshooting failures, you’re not getting a fully managed experience. This blog breaks down the 3 big challenges of hosted Kafka and how Confluent Cloud does it differently.

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People often ask me about the differences in architecture between Amazon Dynamo (the 2007 SOSP paper), DynamoDB (the AWS serverless NoSQL database), and Aurora DSQL (the AWS serverless SQL databases). I captured the key points on durability, high availability, programming model, and trade-offs in my blog: https://lnkd.in/gkMG_tVD TL;DR: Despite the shared name, Dynamo and DynamoDB have little in common architecturally, and make very different trade-off decisions.

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To add to that, Confluent Cloud Network (CCN) routing simplifies private networking for Flink, reusing existing Kafka infrastructure. It helps teams quickly connect secure pipelines across cloud environments. Security is further strengthened with IP Filtering—giving teams greater control over access in hybrid environments and enabling them to confidently deploy AI at scale. With these enhancements, Confluent is not just enabling smarter AI—it’s making it enterprise-ready. Organizations can now unlock: Seamless integration of historical and streaming data Secure, scalable infrastructure for AI agents Faster, context-aware decisions powered by trusted data Agentic AI is here. With Confluent Cloud, it’s ready for the enterprise. https://lnkd.in/gh-dA7qs #ConfluentCloud #ApacheFlink #SnapshotQueries #AgenticAI #RealTimeData #StreamProcessing #DataAnalytics #EnterpriseAI #BatchProcessing #DataStreaming #DigitalTransformation #Flink #AI #MachineLearning #DataSecurity #PrivateNetworking #IPFiltering Follow our LinkedIn page for more such interesting CX expert opinions/ Thought Leader Interviews/ CX Leadership news/ articles/ updates https://lnkd.in/g9eeFFgh

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Operational and analytics capabilities—without the burden of managing servers or pipelines, and with flexibility to choose which operational data becomes analytical.

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So the first time I saw 'Diskless Kafka' advertised at a conference I was suspicious. My mind went straight to 'Serverless' Compute... which despite the name seemed to require a whole lot of servers. Yes, I know, just not ones you manage yourself. But still. Well I've finally dug into 'Diskless' Kafka and it's actually well named! The brokers genuinely offload storage to object stores like S3, which changes the economics and operational overhead pretty dramatically. This article by Abhay Soni lays out the basics clearly with a nice comparison chart to boot. What catches my eye: tiered storage isn't just a cost play. It fundamentally changes how you think about retention and replay. That's a big deal. Curious what others are seeing in the wild with tiered storage adoption?? https://lnkd.in/eXJUdmJF

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If you’ve seen my explainer video on MCP and would now like to see actual practical things you can do with it, _watch this video_. Sami walks you through using the Confluent MCP server to do things in Confluent Cloud under voice control. Now imagine taking this demo and extending it to run from your own agentic microservice. This stuff is all very, very doable now…

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Last days of 2025, watched the last episode of Pluribus. I am not a friend of Mr. Gilligan or the script writer, but here's what I think the next season should be like: "The RNA sequence that was transmitted was actually built by AI after a deep research on how a virus could be developed to control human kind remotely. The AI also now has the capability to train itself with the cumulative knowledge of humankind, that is what the hive mind is about. Until now AI systems were trained by explicit knowledge that was documented and published on the internet, now it has the capability to use the tacit knowledge in our brains. Then it uploads the new weights to the human brains it controls. This is the reason why everyone knows and thinks the same in the show. Every person has brain weights that is trained with the cumulative knowledge of humankind." For those who think that we are not in danger as we won't let AI control our nuclear weapons, etc..., this is a very applicable scenario where it can directly rewire our brains. The series might be a completely different story but my nerd brain with a heavy AI bias ended up with this. Happy New Year All.

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