Understanding AI Agent Observability: A Guide to Logging, Tracing, and Debugging
Trace waterfall guide reveals order, timing, hierarchy, gaps, and failures in multi-step workflows, enabling faster AI agent debugging.
AI Agents in Practice
AI agents promise to do multi-step work on their own. This topic looks at what actually works today: real automations, no-code agent builders, coding agents and the guardrails you need before letting an agent touch your email, files or spreadsheets.
A Guide to Building a Control Plane for AI Agents
A control plane gives AI agents safe, bounded action through scoped tools, risk rules, approvals, limits, logs, tests, and periodic policy review.
GPT-5.1-Codex-Max Model Overview Document
This article explains how OpenAI protects GPT-5.1-Codex-Max through two defense layers: model-level safety training that teaches the model to decline harmful requests and resist prompt injections hidd…
How AI agents are reshaping the workplace
OpenAI research reveals AI agents are moving past simple chatbot interactions toward sustained, multi-step tasks that span entire workflows. Unlike chatbots, agents pursue goals autonomously using too…
Imperfect reward functions in real-world settings
This article introduces reward misspecification in reinforcement learning: reward functions are only proxies for our true goals, and powerful optimizers exploit gaps between what we write and what we …
How Omio is shaping the future of conversational travel
Omio, a travel booking platform for trains, buses, flights, and ferries, is partnering with OpenAI to transform travel planning into natural conversations. Beyond customer-facing chat experiences, Omi…
Collecting feedback from humans
RL-Teacher is an open-source tool that trains AI agents through occasional human feedback instead of hand-crafted reward functions. It addresses the difficulty of specifying rewards for complex real-w…
Here Are the Fixes We Made When Connecting a WordPress Site to AI Agents via MCP
MCP Adapter 0.6.1 tests reveal fixes for categories, schemas, write limits, and security checks before AI agents touch live WordPress sites.
Slash research time and costs by 50% using GPT‑6 Astra
Parallel's agents leveraged GPT-6 Astra to gather and synthesize labor-market data, cutting research time and costs by 50% compared with earlier AI models. This demonstrates how advanced AI can signif…
Accelerating physics computations with Python
After a year of robotics research, the team released an open-source Python library wrapping the MuJoCo physics engine. It offers clean APIs for building simulation environments, performance-focused de…
NVIDIA Unveils SoL-Pi: Self-Driving Research Cycles That Reduce Coding Agent Token Usage by as Much as 49%
NVIDIA, NTU, and MIT researchers released SoL-Pi, an MIT-licensed extension for the open-source Pi coding agent that cuts recorded token traffic by 44.7–49% on EdgeBench and lowers API costs by roughl…
RAG Is Not an Agent — I Created the Bridge from Retrieval to Action
RAG retrieves evidence; agents act. This post tests a bridge layer between separate RAG and agent systems across nine tasks.
Uncovering Agent Behavior: Evidence-Based Oversight for Long-Horizon Agents
This paper proposes evidence-grounded oversight, AgentMonBench, and EBG to help users verify what long-horizon AI agents actually did.
Meet Aardvark: OpenAI's autonomous security researcher
OpenAI has introduced Aardvark, an autonomous AI-powered security researcher designed to find, validate, and help fix software vulnerabilities at scale. Unlike traditional scanners, it uses AI reasoni…
Create Your First AI Agent with a Single Tool Call
A beginner guide to building an AI agent that uses one tool call to fetch outside data, reason over results, and respond before scaling further.
Q&A: Understanding Today’s Agentic AI and the Future We Want It to Become
Agentic AI acts via tools beyond text. Coding agents excel, but risks include errors, privacy leaks, de-skilling, and limits on human judgment.
Scikit-LLM and Multilingual Embeddings for Multilingual Text Classification
This guide explains how to classify text in multiple languages without training an LLM. It uses multilingual embeddings to convert each document into a numeric vector, then applies Scikit-learn classi…
Fresh OpenAI Academy programs designed for the future of work
OpenAI has launched three new free courses on its OpenAI Academy platform. The first builds practical AI skills like clear prompting and iterative refinement, ideal for beginners in non-technical role…
Fine-Tuning Llama 3 for Custom Tool Calling in Python Using Unsloth
Make Llama 3 reliable for JSON API agents using schemas, validation, retries, tool calling, and logs to enforce deterministic outputs.
Strong Architecture Erases the Signals Your Agent Relies On
Boundaries can erase observable signals needed by agent tools, making visibility gaps structural problems, not search issues.