A recent InfoQ webinar examined operational challenges in deploying agentic systems. Key points included issues like semantic and embedding drift, which can lead to significant errors. Experts...

Once AI is in production, code arrives faster than it can be reviewed, token costs rise, evals have to be good enough to act on, and agents need permissions and guardrails. QCon AI New York 2026...

On October 14, InfoQ hosts a free 60-minute panel with five practitioners on running AI in production. They'll discuss agent autonomy and human approval, how to verify AI-generated changes,...

A preview of the 15-track QCon London 2027 program, covering agent evaluation and guardrails, AI-era architecture, distributed-system debugging, modern data platforms, high-performance...

As construction productivity stagnates, companies can stand out by employing granular, achievable rates of production to optimize schedules, improve productivity, and make delivery predictable.

In this article, author discusses his experience with AI agent hallucinations in an inventory recommendation system and how this problem was solved by treating the LLM stack as a platform...

QCon San Francisco 2026 will bring together practitioners from Airbnb, OpenAI, Netflix, Honeycomb, and other engineering organizations to share how they are building, operating, and evolving...

The panelists discuss how production operations are evolving with AI, turning operational data into actionable insights for incident response. They explain how automation and new architectural...

QCon AI New York has confirmed 23 sessions covering agent authorization, production guardrails, shared inference infrastructure, and the evaluation of AI systems after deployment. By Artenisa Chatziou

OpenAI’s Vinoth Govindarajan discusses why production AI agents fail beyond model hallucination. Using real-world case studies like OpenClaw, he explains the key principles of reliable agent...

Grab has implemented LLM-Kit, a framework that standardizes over 500 internal agent services. This system enhances service integration, evaluation, and secret handling, reducing the time to deploy...

Alex Porcelli discusses the critical gap in enterprise AI: non-deterministic output and lack of accountability in high-stakes decisions. He shares how integrating DMN decision models with LLMs,...

Cassie Shum discusses why knowledge graphs serve as a critical foundation for agentic systems. Moving beyond basic RAG, she explains 4 practical architectural patterns: context bundling, decision...

Zhou Yu discusses why AI agents stall in demo phase and shares how simulation-driven testing solves compliance and reliability bottlenecks. Learn how Columbia and Arklex AI use synthetic user...

Ricardo Ferreira discusses moving beyond simple prompt engineering to build production-grade AI applications. He shares practical architectural strategies for integrating long-term and short-term...

On August 13, 2026, PostgreSQL shipped its biggest security release ever: 28 CVEs closed in a single day. The old record was 11. The community has done its job, a phenomenal one at that! If you...

AI workflows have two needs that trade off directly. Running reliably in production requires persisting and distributing every step so it survives crashes, deploys, and restarts. But that same...

JDK 24 removed the monitor-related carrier-thread pinning that stalled Netflix and similar teams on Java 21. What has replaced it on JDK 25 LTS is downstream-resource saturation: The bottleneck...

This article presents a defense-in-depth approach for securing Model Context Protocol (MCP) deployments in production. It outlines four architectural control layers: safe execution, management...

QCon AI New York 2026 (Dec 15-16) has opened registration at The Westin Jersey City Newport. Six tracks on production AI, chaired by Eder Ignatowicz with Faye Zhang and Wes Reisz. First sessions...