InfoQ

Evaluating AI Agents in Practice: Benchmarks, Frameworks, and Lessons Learned

This article introduces practical methods for evaluating AI agents operating in real-world environments. It explains how to ...
Analytics Insight

How AI Is Reshaping the Way Python Developers Write and Secure Code

Python is now one of the fastest-growing programming languages being used globally and supports machine-learning-based ...

A Practical Guide to Autonomous Evaluation Loops in Claude Code

The guide explains two layers of Claude Code improvement, YAML activation tuning and output checks like word count and sentence rules.
InfoQ

AWS Launches Strands Labs for Experimental AI Agent Projects

Amazon Web Services has introduced Strands Labs, a new GitHub organization created to host experimental projects related to agent-based AI development.
IEEE

AdaCoder: An Adaptive Planning and Multi-Agent Framework for Function-Level Code Generation

Abstract: Recently, researchers have proposed many multi-agent frameworks for function-level code generation, which aim to improve software development productivity by automatically generating ...
IEEE

Model-Agnostic Empirical Evaluation of Test-Driven Prompt Engineering on Improving Accuracy and Efficiency in Large Language Models Python Code Generation

Abstract: Although Large Language Models (LLMs) are widely adopted for Python code generation, the generated code can be semantically incorrect, requiring iterations of evaluation and refinement. Test ...