
AI agent security: what to check before connecting your accounts
A practical permissions checklist for AI agents: separate reading from sending, review sensitive actions, and learn how to stop scheduled work.
Building, running and supervising AI agents.

A practical permissions checklist for AI agents: separate reading from sending, review sensitive actions, and learn how to stop scheduled work.

Compare October 2026 subscription prices and working styles, then use a simple task trial to choose an AI for writing, research, spreadsheets, or coding.

A beginner’s guide to dots and Muse: access conditions, useful first tasks, permission settings, and a practical way to evaluate your first week.

Evaluate coding agents with the same task, acceptance criteria, review time, and cost per successful result. Includes a reusable task prompt and recording table.

Collect recent news, remove duplicates, retrieve original sources, and save a reviewable blog draft. A practical guide with prompts, failure handling, and cost controls.

Three days after launch, a second look at Gemini 4 Argon from an operator's seat. Where it leads and trails by type of work, what a task really costs, what a 1M-token output and a guardrail-free tier mean for how you run agents, and what you can prepare before the API opens.

A tour of the endue console, from the home board to approval cards, the Studio canvas and Spaces. Why the interface of an agent product is a control surface, how many minutes a fixed layout saves, and how often other AI apps rearranged their screens over the last four months, with dates.

Google's first Gemini 4 model leads 12 of the 18 benchmarks in its own table, and the public leaderboards mostly agree. This post goes through who ran which test, how many tokens Argon spends per task, what a 1M-token response costs, and why only cyber defenders can use it today.

Three days after launch, a systems view of Dots. It covers the cloud computer each one runs on, how a goal turns into actions, the checks that sit in between, what OpenAI's own tests say about where it slips, what changed since DevDay, and what you would need to build the same thing yourself.

An engineer's look at ChatGPT Space three days after launch. How spaces, pages and files fit together, how access is inherited, what each person's agent can see, what the Compliance API exports, and what is still missing, from export to version history.

OpenAI launched Dots a day after holding back GPT-6.1 Astra and apologizing to Australia. What its own safety numbers and privacy FAQ say, how the first day went (stalled demos, a five-hour outage), and a checklist built from OpenAI's help articles.

Dots, OpenAI's headline DevDay launch, are agents with their own cloud computer that stay on in ChatGPT, Slack and Teams and keep working between conversations. What they can do, who gets them, and how permissions and approvals work.

OpenAI launched Space, a shared workspace inside ChatGPT, and Pages, a document type built for people and agents. What they do, what ships now and later, team tasks and Slack and Teams, and the permission and privacy details worth knowing.

At DevDay 2026, OpenAI reworked Codex with shared cloud environments, a CLI with voice and an agents view, code review in the ChatGPT desktop app, and Codex Security Cloud for GitHub repositories. What changed, who can use it, and what to check first.

At DevDay, OpenAI previewed a Decisions API built on Luna that picks one answer from options you define and accepts images. What OpenAI has shared, the first head-to-head tests, how it differs from Jev, and what is still unannounced.

TypeSafe's Jev picks one answer from options you define, in under half a second. How to use it as a router that cuts LLM costs, as the reflexes of a 3D character and as a guardrail, with diagrams and the limits to know first.

Claude Sonnet 5.5 scored above Opus 5.5 on one benchmark at half the token price. At some settings it still costs more per task. The published numbers, the independent ones, and an order for choosing models for your own work.

Adding agents does not make work faster by itself. Six principles from Anthropic, Cognition and recent research, and how endue organizes agents around them.

OpenAI's new model edits Unity scenes, plays the build and fixes what breaks. What the first examples show, where the gains come from, and what to set up before you try it.