Systems | Development | Analytics | API | Testing

Is WebSockets enough for AI chat?

WebSockets are the right protocol for production AI chat. But that fact doesn’t prevent the failure most teams hit first. An enterprise load balancer closes the idle connection at 60 seconds during a tool execution wait. Your reconnect logic fires in under a second, the agent keeps running server-side, and the client receives nothing from the gap. No tokens, no tool call results, no context. The reconnected socket has no view of what happened while it was down.

Autonomous Agentic Event-Driven Systems Architecture

Autonomous / agentic event-driven systems are a class of AI-native architectures where software agents continuously sense events, reason over shared state, take actions, and learn from outcomes—all in real time and without human-in-the-loop orchestration. At an architectural level, these systems combine event streaming, stateful processing, and agentic decision layers to form closed-loop AI systems capable of operating independently at scale.

Enterprise Knowledge Management with RAG for Digital-Native Companies

Enterprise knowledge management RAG (Retrieval-Augmented Generation) is a production-grade AI architecture designed to connect Large Language Models (LLMs) securely to a continuous, real-time flow of proprietary corporate data. Unlike basic RAG implementations that rely on static document uploads and batch-processed vector databases, an enterprise RAG architecture utilizes event streaming to ingest document updates, regenerate embeddings, and synchronize context in real time.

RAG and GenAI for Regulated and Public Sector Architectures

As a cloud engineer, I’ve seen organizations rush to implement Generative AI, only to hit a brick wall when the Chief Information Security Officer (CISO) asks about data residency or PII leakage. In the public sector and regulated industries like healthcare or finance, moving fast and breaking things isn't an option.

Are Microservices Dying?

LLMs are absorbing the business logic of microservices for agentic use cases — but both patterns will coexist in enterprise infrastructure for a long time. Cloud-native infrastructure (microservices + APIs) keeps powering web and mobile experiences. The agentic layer — LLMs, MCP tool calls, and context traffic — runs in parallel, activating the same APIs and CRUD operations underneath. Kong manages both swim lanes: the API traffic between clients and microservices, and the context traffic flowing between agents and LLMs.#Shorts.

Anthropic Acquires Stainless. What's It Mean for AI Connectivity?

Every few months, a frontier AI lab makes a move that says the quiet part out loud: agents are only as useful as the systems they can reach. The latest example is Anthropic's acquisition of Stainless, the company behind the tooling that turns API specs into SDKs and MCP servers. Anthropic's own framing is direct. Agents need to connect to data and tools, and the path from an API to an agent-ready interface needs to get shorter. We agree. We've been making a version of this argument for two years.

How to Connect Business Data to Claude (and Actually Get Accurate Answers)

You ask Claude what your MRR was last month. The answer comes back fast, formatted cleanly, stated with total confidence, and completely wrong. Not because Claude is broken, but because it was guessing. Claude has no live connection to your business data by default. It cannot query your CRM, pull from your ad platforms, or check your billing system. So when a marketing manager asks about their numbers, Claude either refuses or generates a plausible-sounding figure based on patterns in its training data.

WSO2 Accelerates Agentic Enterprise Adoption with New Agent Identity, Forward Deployed Engineers, and Expanded Delivery Partner Ecosystem

London, UK. 21st May 2026 - WSO2 today announced the expansion of its Agent Fabric platform, the introduction of a Forward Deployed Engineering model, and the scaling of its delivery partner ecosystem to accelerate the adoption of the agentic enterprise. Announced at the WSO2Con North America 2026, these initiatives strengthen WSO2's position as the infrastructure layer for the emerging agentic enterprise, where AI agents operate autonomously across applications, APIs, workflows, identities, and data.

Turn Your Agents Into Kafka Experts with Skills. Live from Current London

Most AI agents are generalists that struggle with the nuances of streaming data and Kafka infrastructure, often leading you down a rabbit hole with many tokens spent. In this session, live from Current London, we’ll show you how to close the context gap with Skills for Kafka: structured files that are playbooks and level-ups for agents to handle complex multi-step tasks like reviewing schema changes, critiquing DLQ policies and auditing topics for best practice. We will walk through how these skills work, demonstrate the different ways to use them (including with MCP servers) in Cursor and Claude.