Systems | Development | Analytics | API | Testing

Why AI support fails in production: The infrastructure problem behind every incident

HTTP streaming – the default transport underneath every major agent framework – was never designed for sessions that survive a tab close or hand off cleanly between participants. Two failures surface consistently in production CX products because of this. Both generate support tickets about conversation state and prompt quality. Both trace to the transport layer. The scenario that illustrates them: a customer contacts support about an order that's partially shipped and partially stuck.

Stateful agents, stateless infrastructure: the transport gap AI teams are patching by hand

Every major layer of the AI stack now has a name. Model providers - OpenAI, Anthropic, Google - handle inference. Agent frameworks - Vercel AI SDK, LangGraph, CrewAI - handle orchestration. Durable execution platforms like Temporal make backend workflows crash-proof.

Bringing Real-Time Data and AI to the Enterprise

For our enterprise customers, data isn’t just a resource, it’s the engine for future growth. In this overview, Manuel Calvé (Head of Partnerships at Conduktor) explains why the Cloudera + Conduktor alliance is the "Gold Standard" for the modern data enterprise. By combining Cloudera’s hybrid open data lakehouse with Conduktor’s precision Kafka management, we are enabling industries like Finance and Manufacturing to turn streaming data into a high-trust, revenue-generating asset.

Practical Strategies to Monetize AI APIs in Production

AI APIs don't get enough credit for how much weight they're actually carrying. These AI APIs aren't merely technical connectors. They're, in fact, cost drivers and potential revenue engines. And when something goes sideways, they're ground zero. In production, they behave nothing like the traditional APIs your teams have been running for years; they introduce a whole new set of hurdles around operations, security, and governance that most organizations are still struggling to understand.

This week on The AI Forecast: prevent AI agents from going off the rails #short #tech #fyp

*Does your enterprise have governance over teams of AI agents?* This week, Tatyana Mamut, PhD, joins The AI Forecast to talk about why agentic AI needs to be managed like human teams. This conversation goes beyond technology; Tatyana also reflects on leadership and representation in tech, challenging assumptions about opportunity, and exhibiting why diverse ways of thinking are critical in an AI-driven world.

VASS & Appian AI: Transforming Procurement for a Billion-Dollar Future

Discover how VASS, a global digital transformation leader, partnered with Appian to revolutionize their procurement process with Appian AI. Learn how they achieved a 40% reduction in processing time and a 70% decrease in email communication, streamlining operations and mitigating risks as they work toward their VASS @ 1 billion goal by 2028.

Cloudera Private AI: Bring AI to Your Data Anywhere #AI #Tech #Shorts

Are your AI initiatives stuck in pilot mode? Siloed data, disconnected tools, and compliance a constant headache? Sending sensitive data to the cloud for model training is a non-starter, especially for regulated industries. Cloudera AI changes the game. Cloudera is the only data and AI platform that delivers the secure cloud experience anywhere—public clouds, data centers, and the edge. We provide the foundation you need for real AI, real scale, and real business impact—without ever giving up control.

AI Transport in action: resumable streaming, multi-device sync, and more

How do you deliver token streams, sync conversation state across devices, and let users interrupt an agent mid-response -- without rebuilding your stack every time you switch frameworks? Mike Christensen demonstrates Ably AI Transport in action, walking through the key primitives every production AI application needs and showcasing a multi-agent holiday planning app built on those primitives. Topics covered.