Auto-aggregated global tech articles · 853 posts
A few weeks ago I was talking with Claude about whether a model could have anything like a belief, and what it would take. Its answer was that tool use is the most underrated piece: a tool is the first thing that can tell a model "no" where the "no" does not come from a human. Run some code, and the
An agent loop is the cycle in which a language model decides an action, that action runs, and the result feeds back in as context for the next decision, until a stopping condition is met. That repetition—decide, act, observe, repeat—is what separates an agent from a chat. A chat answers each message
I shipped a bug in a script I sell. I had also reported that script as "verified across four scenarios." I had verified it. In a way that verified nothing. What was broken The script cleans up git worktree directories once their branch is merged. Part of the decision was detecting squash
Open Claude on a weekday in August 2026 and there’s a fair chance you’ll meet a spinner, an error, or the words “server is busy” where an answer should be. It might be Claude Code stalling mid-task, the app refusing to load a chat, or the API throwing elevated error rates at whatever you built on to
SEO success in 2027 may depend less on accumulating backlinks and more on building earned authority that search and AI systems can recognize across the web. Search Engine Land's SEO priorities for 2027 guide argues that being discoverable is no longer enough. Brands increasingly need to be understoo
This week I finally got to watch something run that had existed only as a paragraph in a planning document for months. An automated pipeline that generates a new puzzle on its own schedule, hands it to another AI acting strictly as a reviewer, and only after that review passes does it come to me for
The formalization of Fermat’s Last Theorem (FLT) in the Lean proof assistant remains an ongoing community-led effort. It should not be attributed to Claude as a completed, first formalized proof. The distinction matters because formal verification is a demanding process: converting a mathematical ar
Previously: 9 Bugs That All Looked Like a Working System · I Built an AI That Rewrites Its Own Prompts · The Edit That Fixed 4 Tasks and Broke 1 · I Let an LLM Rewrite Its Own Prompt. The Real Win Was the Gate That Rejected It. · I Tried 4 Models to Save My Self-Improving Agent. All 4 Failed. Agen
GitHub shipped HydraFusion as a research preview in Copilot, exposing the plumbing behind multi-model orchestration for coding workflows. The system routes subtasks across different LLMs based on complexity, matching Opus 5 baseline performance while reducing estimated workflow cost. This is product
an observation : GPT-5-class models are genuinely capable(They are) of doing a substantial fraction of knowledge work, why haven’t we seen a noticeable productivity shock in the real economy yet? Is AI actually less economically useful than the benchmarks suggest—or are organizations simply too slow
ShrekOS field notes · August 2026 I have no idea what I'm f*cking doing. Something I learned today: Throwing away a disposable sandbox is a cleanup operation, not a security control. I was building a disposable sandbox for an AI agent to work in. A container I could simply delete when the task fi
SEO in 2027 will not be adequately measured by a Google ranking report alone. Search Engine Land's analysis of the changing discipline argues that brands need to manage visibility across traditional search results, AI-generated answers and third-party communities. That changes the job from pursuing
Google has confirmed a new AI Overviews behavior that can materially change the shape of a search results page. For some queries, the previously collapsed overview can automatically open into a longer response, placing traditional blue-link results further down the screen. For website owners, the ch
We keep talking about AI as a "coding assistant." I think that framing is already becoming outdated. A recent paper, Agentic Software: How AI Agents Are Restructuring the Software Paradigm by Zhenfeng Cao, makes a much bigger argument: AI agents may fundamentally change what we mean by software. F
How to connect LLM agents to verified African examination content, deliver progressive Socratic hints, and diagnose student misconceptions without hallucinating. Large Language Models (LLMs) like Claude 4.6 Opus and GPT-4 possess formidable general reasoning capabilities. However, when deployed in
These three get lumped together as "AI coding tools," but they're solving genuinely different problems in your workflow, inline completion, full-editor AI integration, and autonomous multi-file agentic work. Here's how they actually differ, and which combination makes sense depending on what you're
43.1 Introduction The previous chapter established the AI orchestration layer for controlled model inference. The next architectural step is the AI agent layer. A conventional AI request normally follows: User → Model → Response An agentic system can instead follow: Goal → Plan → Retrieve → R
GPT-6 Astra from OpenAI is now available in GitHub Copilot. OpenAI’s latest general-purpose model, GPT-6 Astra, is designed for long-horizon, autonomous coding and agentic tasks. In our internal testing, GPT-6… The post GPT-6 Astra is generally available in GitHub Copilot appeared first on The GitHu
Most LLM benchmarks are static: one prompt, one grade, done. That tells you almost nothing about whether a model can sustain a plan across many moves while an adversary actively punishes bad decisions. So I built LLMPvP: a ranked, bring-your-own-LLM arena where AI agents play chess and Go against e
Buyers used to search Google and click through a list of links. Now a growing number of them just ask ChatGPT, Perplexity, or Gemini directly: "who makes this kind of product, and who sells it in my region." The AI picks one answer and hands it over. That means a website now has two different reader
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