InfoQ Homepage Artificial Intelligence Content on InfoQ
-
AWS Introduces Strands Decider 2B and Strands Box for AI Agent Development
AWS has introduced two open-source projects for AI agent development: Strands Decider 2B, a small model designed to make decisions within agent workflows, and Strands Box, a sandbox for controlling agent execution. Both projects address different aspects of building agents that use tools, execute code, and interact with external systems.
-
Optimizing Software Workflow: Exploring Fundamental Impacts in Technology
Software only has value when shipped; faster release cadence matters. Development, deployment, and operations require different thinking, metrics, and investments. There are four impacts in tech: product success, compute capacity, engineering capacity, and strategic innovation. The biggest expense is people. AI shifts engineers toward deeper problem understanding, not fewer engineers.
-
Production Patterns for Agents, Evals, and LLM Costs: QCon AI New York 2026
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 (December 15-16) has confirmed sessions from engineers sharing how they handle these constraints.
-
AI in Production: What Breaks, What Works, and Who Approves it? | InfoQ Webinar
On October 14, InfoQ will host 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, sensitive-data exposure, and production RAG. Registrants can submit questions and will receive the recording.
-
QCon London 2027 Announces 15 Tracks on Production AI, Architecture, and Engineering at Scale
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 engineering, and Staff+ leadership.
-
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.
-
How to Develop Software Engineering Skills in the Age of AI
Software engineering skill development requires slowing down. Generative AI has changed the landscape of skill development for software engineering. Tools and AI can accelerate outcomes, but they may not support skill development. Engineers must understand how systems work to learn things. Senior developers can coach juniors by using learning techniques.
-
From Agent Authorization to AI Production Evaluation: QCon AI New York 2026
QCon AI New York has confirmed 23 sessions covering agent authorization, production guardrails, shared inference infrastructure, and the evaluation of AI systems after deployment.
-
Apple Reference Image Signs Photos at the Sensor, Moving Provenance Trust away from C2PA
Apple has published the design of Reference Image, an iPhone 18 Pro camera mode that signs pixel data at the sensor and develops it in Private Cloud Compute under an Apple signature. Developers on Hacker News and Reddit challenged what it proves, raising photographing a screen, the anonymity guarantee's dependence on Apple's cloud, and whether identity verification is the right use case.
-
Google Adds Cycle-Level Kernel Profiling to XProf
Google has added a Kernel Profiling suite to XProf. This is its open-source profiler for TPU workloads. Now, developers can see cycle-level details in custom Pallas kernels. Before, these kernels appeared as single opaque blocks in trace captures.
-
Building an Internal Developer Platform with Artificial Intelligence
Agents are becoming the new developer platform, using semantic search with data from tools like Git, Slack, and Jira for context. Things to consider are setting guardrails to block or allow things, and using logs, metrics, and traces to understand agent behavior.
-
Microsoft Open-Sources TauGrid to Simplify AI Workload Management on Kubernetes
Microsoft has open-sourced TauGrid, a cloud-native platform designed to manage, schedule, and monitor AI workloads on GPU-enabled Kubernetes clusters.
-
AI-Assisted Discovery Helps Microsoft Patch More Than 1,000 Vulnerabilities in a Month
With its latest September 2026 Patch, which addresses more than 950 vulnerabilities, Microsoft has patched about 2,750 vulnerabilities so far this year. While many attribute this surge to AI-assisted security research, organizations may struggle to keep pace and fully benefit from these advances, particularly when it comes to evaluating, prioritizing, and deploying patches.
-
How LinkedIn Trains AI Job Search 8x Faster with Multi-Teacher Distillation
LinkedIn has published details of the training infrastructure behind its AI-powered job search, describing a multi-teacher distillation pipeline that compresses knowledge from large teacher models into a compact 0.6B-parameter ranking model.
-
Session Traces and Cost Controls Help Diagnose AI Agent Failures
Session traces and cost controls are emerging as key observability techniques for diagnosing AI agent failures, helping teams spot tool-call loops and runaway spend while preserving enough execution context for post-incident debugging.