analiza aiqbench
This article focuses on the operational challenges of integrating autonomous AI agents into production environments, specifically addressing risk management, guardrails, and the shift from passive code generation to active system interaction. It examines practical engineering strategies for verifying agent outputs and maintaining human oversight in high-stakes workflows involving customer accounts and distributed systems.
Engineering Production Systems for an Agentic Era: QCon San Francisco 2026
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 production systems as AI agents take on a larger role. By Artenisa Chatziou
AI agents are changing more than the way code is written. They are becoming users of production systems, initiating customer actions, querying observability data, and influencing how software is tested and released. That creates practical questions for senior engineers. Which decisions can safely be delegated to an agent? What evidence is needed before agent-generated work reaches production? How should existing systems expose context without expanding risk? Where must experienced engineers retain direct control? QCon San Francisco 2026, taking place November 16–20, brings together practitioners from Airbnb, OpenAI, Netflix, Honeycomb, and other engineering organizations to share how they are answering these questions…
Extras afișat conform termenilor RSS ai publicației · 101 cuvinte · textul integral și figurile sunt pe site-ul publicației
Subiecte conexe
InfoQ Online Cohorts Address AI Security and Coding Agent Verification
InfoQ · 30 sept. 2026
From Agent Authorization to AI Production Evaluation: QCon AI New York 2026
InfoQ · 25 sept. 2026
Production Patterns for Agents, Evals, and LLM Costs: QCon AI New York 2026
InfoQ · 13 oct. 2026
QCon AI Boston: Production AI Moves beyond Prompts to Platforms, Harnesses, and Evals
InfoQ · 17 iul. 2026