In a demo for its Agentforce AI Agent Builder, the company showed how imposing logical rules on customer service agents could improve consistent outcomes.

While AI delivers greater speed and scale, it can also produce biased or inaccurate recommendations if the underlying data, model design or oversight systems fall short.

Andrej Karpathy is pioneering autonomous loop” AI systems—especially coding agents and self-improving research agents—while advancing AI-native education ...

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

Karpathy's autoresearch and the cognitive labor displacement thesis converge on the same conclusion: the scientific method is ...

Neo4j Aura Agent is an end-to-end platform for creating agents, connecting them to knowledge graphs, and deploying to ...

OpenAI on Thursday announced the acquisition of Astral, the developer of open source Python tools that include uv, Ruff and ...

Karpathy's 'autoresearch' agent did not improve its own code, but it points towards systems that could as well as towards way ...

A practical offline AI setup for daily work.

Overview AI agents enable autonomous workflows, making them essential skills for future-ready tech professionalsChoosing hands-on Udemy courses helps build real ...

In the pre-large language model (LLM) Stack Overflow era, the challenge was discerning which code snippets to adopt and adapt effectively. Now, while generating code has become trivially easy, the ...

Key Takeaways LLM workflows are now essential for AI jobs in 2026, with employers expecting hands-on, practical skills.Rather than courses that intensively cove ...