16 related articles

A Google DeepMind engineer reveals that over 50,000 AI agent skills come with almost no evals. This guide covers skill descriptions, test design, eval harnesses, and retirement strategies.

A Google DeepMind engineer reveals that over 50,000 AI agent skills come with almost no evals. Learn how to write skill evaluations, from description tuning to test design.

An in-depth analysis of the five core dimensions of AI Agent testing: command safety, tool-calling accuracy, task planning, output consistency, and error self-repair. Master automated testing methods and the transition path for test engineers.

In-depth analysis of the five core dimensions of AI Agent testing: command safety, tool-calling accuracy, task planning, output consistency, and error self-repair. Master automated testing and the transition path for test engineers.

A deep dive into AI Agent Loops: from single loops to multi-agent collaboration. Master goal definition, validation mechanisms, and stop conditions to avoid blindly building agent fleets.

Google DeepMind engineer Philip reveals: almost everyone uses coding agent Skills, yet almost no one writes evals for them. A deep dive into Skill evaluation methods, 8 actionable tips, and a real Gemini API case study.

A deep dive into Looping Engineering — covering the five core loop elements (Trigger, Goal, Judgment, Feedback, Memory), when to use loops, and a step-by-step guide to building a topic-selection loop with Claude Code.

OpenAI's GPT-5.6 launches as three models: SO, TERA, and LUNA. The flagship SO autonomously completed LUNA's post-training, marking a new era of AI-trained AI. Deep dive into pricing, Programmatic Tool Calling, METR safety findings, and government oversight.

No technical background? Learn how to rigorously evaluate AI translation accuracy and reproducibility. A practical hybrid scoring framework for NGOs and non-technical evaluators.

An in-depth look at the seven core components for building long-running AI agents: Goal, Evaluator, Verifier, Outer Loop, Orchestration, Observability, and Memory. Master this control system for reliable autonomous agents.

Matt Pocock's 4-step framework for AI Agent Skill design: Trigger, Structure, Steering, Pruning. Escape skill hell and learn to write high-quality skills.

Matt Pocock's 4-step framework for AI Agent Skill design: Trigger, Structure, Steering, Pruning. Escape skill hell, tell good skills from bad, and master leading words to make Agents follow your intent.

Andrew Ng's AI Prompting for Everyone course reveals four key gaps between AI beginners and power users: deep thinking tasks, context, neutral prompting, and iterative workflows.
GPT-5.5 Instant's Medical Q&A Capabili…
OpenAI announces GPT-5.5 Instant matches frontier Thinking models in health Q&A, with major improvements in emergency recognition, follow-up questioning, uncertainty expression, and plain-language explanations — free for all users.

Based on Andrew Ng's latest AI prompting tutorial, learn the core gaps between beginners and experts: providing context, overcoming sycophancy, iterative workflows, and four key principles.
TutorialsA detailed guide to the four-stage universal AI prompt system for mathematical modeling, covering problem analysis, innovative model construction, data processing, and model solving for competitions.