2026-10-03 OpenAI Dots - always-on agents, with a memory you can't inspect
On Tuesday (29 September), at DevDay, OpenAI launched Dots): always-on agents that live inside ChatGPT and keep working when you close the window.
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On Tuesday (29 September), at DevDay, OpenAI launched Dots): always-on agents that live inside ChatGPT and keep working when you close the window.
On 29 September 2026, OpenAI added a third Pro tier to ChatGPT: ChatGPT Pro 500. It costs $500 a month, has the highest included usage of the Pro plans, and is the only Pro plan with GPT-6 Astra Ultrafast in ChatGPT Work and Codex.
On 22 September 2026, OpenAI released GPT-6 Sol and GPT-6 Luna, the faster and cheaper siblings of GPT-6 Astra. It landed about an hour after Anthropic shipped Claude Opus 5.5. Simon Willison covered both releases in one write-up, calling it "a new price war".
I've released two updates of the Life Tracker plugin for Obsidian today: 3.1.0 and 3.2.0. Most changes are quality of life things that some of you asked for in the Knowii Community.
OpenHarness (the app itself is just called "Harness") is an open-source command center for coding agents, built by Autonomous (autonomous.ai). Their tagline: "The ultimate harness for coding agents and beyond. All your agents. All your machines. One command center."
GPT-6.1 Sol is the middle model of OpenAI's GPT-6 family, between GPT-6 Luna and GPT-6 Astra. OpenAI released it on 29 September 2026, at DevDay, exactly one week after GPT-6 Sol. It replaces GPT-6 Sol as "the newer Sol model" in the API docs, so GPT-6 Sol had the shortest run as OpenAI's current So
Before you type anything, a Claude Code session already loads the system prompt, tools, MCP servers, agents, memory files and skills. All of it takes space in the same Context Window, and all of it is sent with every request.
I just shipped Obsidian Starter Kit 5.0.1. After v5.0.0 went out on September 25, some of you told me that the daily note template wasn't always applied. You were right, and the cause was a change in Templater.
RLCD is how TypeSafe AI says it trains Jev. The name stands for Reinforcement Learning for Calibrated Decisions, and the pitch fits in one line from their docs: RLCD "trains TypeSafe to return decisions and calibrated probabilities instead of generated text."
I just released a new plugin: Agentic Resource Discovery Server plugin for Obsidian. It turns your vault into a local registry for your AI skills and agents. Your AI assistant searches that registry when it needs something, and fetches only that.
A decision model (DM) is an AI model whose output is a decision, not text. You give it an input and a bounded set of possible answers, and it gives you back numbers: which option, how likely yes is, what score. It's the category Jev belongs to, and I think it deserves its own name next to Large Lang
A System One model is TypeSafe AI's name for a general-purpose decision model). It takes context and a set of typed questions and returns probabilities: which option, yes or no, what score. It doesn't generate text. The name comes from Daniel Kahneman's two systems in Thinking, Fast and Slow): Syste
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