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InfoQ AI/ML/Data Eng
1 sources

QCon AI New York 2026 Confirms Sessions on Production Patterns for Agents, Evals, and LLM Costs

QCon AI New York 2026, scheduled for December 15-16, has confirmed sessions from engineers sharing how they handle production AI challenges such as code review bottlenecks, rising token costs, actionable evals, and agent permissions and guardrails. The event highlights practical patterns for deploying and managing AI systems at scale.

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InfoQ AI/ML/Data Eng
1 sources

Spotify: AI-assisted development more than doubled monthly code changes

Spotify reports that AI-assisted development more than doubled its monthly merged code changes, prompting a review of quality and reliability controls across its engineering organization. The company is adapting testing, observability, rollback capacity, workload prioritization, and automated maintenance to handle the higher software change volume.

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InfoQ
3 sources

Google Open-Sources AX, a Kubernetes-Style Orchestrator for Autonomous AI Agents

Google has released AX, an open-source orchestrator and declarative runtime under the Apache 2.0 license for executing and scaling autonomous AI agent workloads. AX runs on Agent Substrate, treats agents as stateful actors, supports sub-second pause and resume, and offers four Kubernetes-style primitives: Task, Workspace, Gateway, and Model. The project aims to address resource utilization and cold-start issues caused by long-running, bursty, and idle-waiting agents, while sparking community discussion about operational complexity and security isolation.

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InfoQ AI/ML/Data Eng
1 sources

Context Language Models: Self-Managing Context to Improve Performance and Reduce Compute Costs

Researchers from Meta, MIT, and the University of Washington introduce Context Language Models (CLMs), a new approach that enables language models to manage and edit their own context rather than relying on predefined mechanisms for summarization, compression, and information retrieval. The work reports substantial gains in both performance and computational efficiency.

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InfoQ AI/ML/Data Eng
1 sources

Cloudflare Open Sources Decision Models for AI Agents

Cloudflare announced Clef, a set of open-weight AI models designed to choose between predefined options rather than generate text. The company released 9B- and 27B-parameter models, along with a platform for adapting them to specific decision-making tasks. The move expands open-source AI tooling for agentic decision-making.

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InfoQ AI/ML/Data Eng
1 sources

Survey Finds AI-Generated Code Increases Debugging and Failure Rates and Creates a Comprehension Gap

A survey by independent research firm Coleman Parkes on behalf of Undo found that while AI coding agents have accelerated code generation, they have shifted the primary bottleneck to debugging, code comprehension, and maintenance. The findings highlight increased debugging and failure rates and a comprehension gap from AI-generated code.

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InfoQ AI/ML/Data Eng
1 sources

Akka Tests Spec-Driven AI Delivery Across 65 Open Source Projects

Akka conducted an experiment using 65 open-source projects to examine how specification structure, context, model selection, automated validation, and delivery guardrails affect AI-assisted software porting. The study measured time, token use, code size, test parity, and performance, finding substantial variation across models, effort levels, and project types.

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InfoQ AI/ML/Data Eng
1 sources

Archestra Releases OpenAPPA, Achieving 0% Attack Success Rate on Two Major Security Benchmarks

Archestra has released OpenAPPA, an open-source security engine designed to stop data exfiltration caused by prompt injection or model hallucination. The team reports zero successful attacks on the Bench-Corp and AgentThreatBench security benchmarks, compared to 10% for Claude Code's auto mode and 31% for Microsoft FIDES.

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InfoQ AI/ML/Data Eng
1 sources

Docker Brings Sandbox Kit Specification to CNCF to Standardize AI Agent Permissions

Docker announced it is contributing the Sandbox Kit Specification to the CNCF, aiming to make what an AI agent may access as portable as the agent itself. The specification seeks to package AI agent permissions as OCI images, promoting standardization. This move could enhance interoperability and security in AI agent permission management.

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InfoQ AI/ML/Data Eng
1 sources

TypeSafe AI Releases Jev: A Decision-Only Model That Returns Typed Probabilities Instead of Text

TypeSafe AI, founded by former OpenAI researcher Diogo Almeida, has introduced Jev, a decision-making model that generates typed outputs rather than text. It evaluates inputs in parallel, providing results with probabilistic scores and confidence values. Jev's adoption has been swift, with integrations into platforms like Vercel and Netlify, highlighting its efficiency over traditional models.

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InfoQ AI/ML/Data Eng
1 sources

Agents Refactor 300K Lines in Three Weeks, Practitioners Question What It Proves

CodeScene published a case study in which coding agents refactored 300,000 lines of C over three weeks for roughly $4,000 in tokens, verified by a frame-by-frame replay harness. The agents also built a playbook of codebase-specific recipes. Practitioners have questioned the scope, the metric, and how much of the result depends on the harness.

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