Systems | Development | Analytics | API | Testing

Get Started With LLM Proxy in WSO2 API Platform AI Gateway

Run your first LLM proxy on WSO2 Platform AI Gateway in minutes — no cloud setup required, just Docker. This quickstart walks you through spinning up the WSO2 Platform AI Gateway as a standalone component on your own infrastructure. You'll add an OpenAI provider configuration (including API key auth and access control rules), deploy an LLM proxy that routes through it, and verify live responses end to end. What you'll set up.

Stop vs disconnect - why canceling AI streaming is harder than it looks

You add a stop button to your AI chat app: a customer support agent, a coding assistant, a research tool the user can steer mid-task. A user clicks it mid-response. The frontend stops rendering. Then you check your backend logs and realize the underlying generation is still running, and you’re still paying for every token. This is not a bug.

Your Vercel AI SDK app is missing a session layer

If you have built an AI chat feature with the Vercel AI SDK, you have used its useChat hook. You give it your messages, and it streams the reply into your UI. You may have seen our post on the custom transport we built for the Vercel AI SDK. It swaps useChat's default transport for Ably AI Transport, adding resumable streams, cross-device and multi-user sync, conversation branching, history compaction, and stop-and-approve controls.

How Enterprise Teams Are Keeping Up With AI-Generated Code at Scale | Perforce 2026

When AI Starts Shipping Code: Managing the Collision Between Human and AI-Generated Code AI agents don't wait for reviews. They generate code overnight, work across the same codebase in parallel, and produce more changes than any human team can realistically process — creating a new kind of bottleneck we call the Merge Wall. In this session, Perforce engineering leaders break down what happens when human and AI-generated code collide at scale — and how leading teams are building the visibility, governance, and coordination layers required to keep up.

Moving from Probabilistic Reasoning to Deterministic Execution

Generative AI systems do not fail because models are weak. They fail because architectures are incomplete. Once organizations accept that prompts cannot guarantee reliability, a new challenge emerges: how to design systems that systematically convert successful AI behavior into repeatable, governable, and auditable workflows.

Agentic apps that go beyond chat

You are planning a trip with an AI assistant on your laptop. You are chatting with the agent, and as you progress it is dropping pins on a map, building a day-by-day itinerary, adding up a budget, and streaming its reasoning as it goes. The state of your interactive session is a combination of the chat history, the synthetic UI constructed by the agent during that process, and structured state, the itinerary, arising from the decisions you each make.

Ep 79 | Why Some AI Products Strike a Chord (and Others Don't)

You recognize the tune, but something feels off. That's how Marlon Davis describes many of today's AI initiatives: AI karaoke. Organizations are rushing to add AI to products, but too often they're layering technology onto solutions without fully understanding the customer problems they're trying to solve. In this episode of The AI Forecast, Paul Muller sits down with fractional Chief Product Officer at Devlnio, Marlon Davis, to explore how organizations can move beyond superficial AI efforts and build products that deliver meaningful customer value.