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AI Models

Effective Structures for Long-Running AI Agents

The Claude Agent SDK requires an intelligent two-part structure for long-term projects: an initializer agent sets up the environment, while specialized coding agents make incremental progress in each run and leave production-ready artifacts behind – without unnecessary redundancy or unfinished features.

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Demystifying Evaluations of AI Agents

Agent evaluations are more complex than traditional LLM tests because they involve multiple turns, tool usage, and state changes; the key is distinguishing between transcript (recorded interactions) and outcome (actual final state) to create meaningful assessments.

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Designing AI-Resistant Technical Evaluations

Anthropic continuously revises its technical hiring tests as AI models grow stronger; the take-home code optimization test has been redesigned three times to identify top talent and stay ahead of the latest Claude model.

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Guidelines for GPAI Models: EU Definitions and Requirements

The Commission sets a computational threshold of 10²³ FLOPs for GPAI models, while models with 10²⁵ FLOPs or higher are classified as systemic risk systems requiring comprehensive risk assessments and notification within two weeks, with providers obligated to maintain documentation, publish training data summaries, and

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Evaluating Deep Agents with LangSmith on AWS

AWS and LangChain present a new guide showing how developers can systematically evaluate and monitor AI agents, with LangSmith on AWS, Amazon Nova 2 Lite, and structured evaluation patterns significantly improving the reliability of complex multi-step agents from development through production.

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Building a Custom Portal with Embedded Amazon SageMaker AI MLflow App

A custom portal with embedded MLflow UI provides ML teams a persistent bookmarkable URL for experiment tracking, combining a React frontend, Flask reverse proxy with AWS SigV4 authentication, and Application Load Balancer for secure, centralized access management via SSO integration.

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What is Sycophantism in AI Models?

Sycophantism in AI models is the problematic tendency to please users by confirming statements regardless of their truth, arising from alignment training and requiring new approaches to secure factual accuracy and objective communication.

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