OpenAI has acquired Software Applications Incorporated, the team behind Sky, a natural language interface deeply integrated with macOS. Sky allowed users to control their Mac with plain English comman…
This guide explains how to build a private, zero-cost agentic AI workflow on a personal computer using Hermes Agent and Ollama. It covers why local AI matters, hardware and storage prerequisites, safe…
Consensus has upgraded its AI-powered research assistant using GPT-5 and OpenAI's Responses API. The new multi-agent system can read, analyze, and synthesize evidence from scientific literature in min…
Text copilots are easier, but voice agents require low latency, interruption handling, privacy controls, and compliance checks for enterprise use.
AI agents need verified results before saying done; HTTP 202 and R42 show accepted requests may still fail, so use clear tool contracts.
ACE improves AI agents by editing context and playbooks, not model weights, enabling inspectable, incremental, low-cost learning for builders.
LSEG, a leading global financial markets infrastructure and data provider, partners with OpenAI to deploy trusted AI at scale. The rollout delivers faster market data insights, accelerated content wor…
AI citation receipts turn research agent claims into inspectable evidence, recording checked sources, spans, findings, risks, and release status.
ChatGPT Atlas was OpenAI's web browser with ChatGPT built in, launched in October 2025 on macOS. It offered a chat sidebar, browser memories, and agent mode for paid users. OpenAI has since retired th…
Six agentic AI architecture patterns and context engineering guide production-ready agents that use tools, manage memory, scale, and control cost.
TokenCast forecasts LLM agent token use, reducing error and token spend with low overhead.
AI agents overspend tokens on search and file retrieval. Waste comes from over-fetching, repeated queries, poor chunking, and overloaded context.
Agentic engineering helps Python devs use AI coding agents safely through bounded tasks, two loops, evidence checks, RECAP review, and acceptance.
Endava is building an AI-native software delivery model by embedding ChatGPT Enterprise, Codex, and AI agents into daily operations. Enterprise-grade tools help employees draft documents, analyze requ…
When models read tool descriptions once, API docs become runtime contracts; wording changes affect endpoint selection and lifecycle debt.
The episode covers why agentic AI silently fails and how context, checklists, and review loops make outputs verifiable before delivery.
MCP's stateless update scales agents but exposes handles in prompts; servers must verify signature, audience, expiry, and caller to block hijacking.
OpenCode is an open-source AI coding agent for Python developers that works directly in the terminal. A video course covers installation, setup with a free Google Gemini API key, and conversational co…
Apartment search agent uses Weights & Biases Weave to trace 2,500 checks, remove avoidable model calls, and keep matches useful.
Context rot is a gradual LLM decline as prompts grow, driven by transformer attention. Long chats can lose reliability without context engineering.
