Build richer, more interactive plugins for ChatGPT. With plugin extensions, you can launch plugins from the sidebar, support @ mentions, and add file viewers. See how in this walkthrough with @coreyching:
Use a compatible driver from @browser_use, @browserbase, @e2b, @daytonaio, or write your own based on the example drivers in the quickstarts. Quickstart: https://github.com/anthropics/claude-quickstarts/tree/main/computer-toolset Docs: https://platform.claude.com/docs/en/agents-and-tools/tool-use/browser-use-sdk
poteto @poteto - is there a way to set up @bot experience in @cursor_ai? asking for a friend who only has access to cursor, not grok bot
Run a neighborhood bar through a chaotic Saturday shift:
Microsoft's Foundry blog guide advises keeping existing Azure Document Intelligence workloads that meet production requirements. It recommends evaluating Azure Content Understanding for high-variation, unstructured, reasoning, RAG, or multimodal document scenarios, and for new cloud OCR or layout workloads.
If you're on API billing, you can set Haiku 5.5's autocompact window to 100K so you stay in the cheaper token pricing tier! It's saved per model so this only applies to Haiku (incl. subagents) > /model haiku > /autocompact 100k
Worth reading — teach according to each student's aptitude! Sherpa: Teaching LLMs to Teach Adaptively
With just 2.5GB VRAM, you can train your own Decision Model using small models like Laya. Training is simply done through a UI interface. Video tutorial and analysis are in our guide. GitHub repo: https://github.com/unslothai/unsloth
@antigravity @stitchbygoogle Watch the full walkthrough: https://goo.gle/4jKK8AV
Google DevRel's James O'Reilly compares two ways Antigravity exposes local MCP tools from Agent Plugins to the model. Eager loading registers each tool as a top-level function with its full schema in every turn's system prompt, which speeds calls but consumes fixed tokens. Lazy loading, the plugin default, exposes tools through a proxy call_mcp_tool and reads schemas on demand, saving baseline context at the cost of an extra discovery step.
Databricks announced general availability of on-behalf-of-user (OBO) authorization for Databricks Apps, letting apps act with the signed-in user's identity so Unity Catalog enforces that user's row filters and column masks. Developers can request narrow API scopes such as sql:restricted-query, which allows only read-only SQL queries, while apps keep a dedicated service principal for app-owned operations.
We made it possible to train your own Decision model locally on just 3GB VRAM! We converted Qwen, Gemma, Llama all into decision models by fine-tuning using a Clef head, boosting accuracy from 30 to up to 78%. You can try it yourself via Unsloth Desktop!
Becoming an AI superuser is NOT about knowing where the buttons are - it's a mindset and behavior shift. And the Mastermind is where we get it done. You've got less than 3 more hours to grab the AI Agent Mastermind at $200 off. And then it's full price until we launch on Oct 19 or until seats run out. Our first two cohorts completely sold out. Join us for the third and jump into how you should be working with AI in 2026 (and beyond).
Unsloth released an open-source method to fine-tune LLMs into decision models that run locally, lifting Qwen3.5 0.8B's aggregate accuracy from 20.7% to 74.3% across three decision benchmarks. The team used a Clef head with LoRA (r=64) for one epoch on just 4GB VRAM, with the approach applicable to models such as Qwen3.8 and Gemma 4. A guide and notebooks are available on the Unsloth documentation site and GitHub.
NVIDIA describes using digital twins and AI agents to validate changes to AI factory infrastructure, which combines GPUs, CPUs, switches, DPUs, and SuperNICs with schedulers, orchestration services, security controls, and a fast-changing software stack. The source frames the challenge as confirming that hardware, software, and policies work together for target workloads before deployment. The available excerpt does not give further detail on specific tools or results.
Most language models split text into subwords—words or fragments of words from a fixed vocabulary. This can obscure spelling details across writing systems & split meaningful units in code or math. Byte-level models work directly with the bytes computers use to represent text.
AWS Machine Learning Blog argues that the traditional hours-saved ROI model, built for rule-based RPA, misses most of the value of agentic automation. It proposes an Agentic Value Model covering time savings, exception handling, decision quality, and change resilience, with value counted only when tied to a defined P&L mechanism and owner.
Qlik built Qlik Answers, a natural-language assistant that returns sourced answers from knowledge bases, analytics apps, glossaries, and documents, using Amazon Bedrock for model access. The system routes each question through specialist agents and retrieval on Amazon OpenSearch Service, with Amazon Bedrock Guardrails applied to every request and response. Qlik serves more than 40,000 customers across regions, using Amazon SageMaker AI as an in-Region fallback when models are not yet available on Bedrock.
The AWS Machine Learning Blog describes an automated remediation workflow that acts on AWS DevOps Agent investigation results. Amazon EventBridge triggers a Lambda durable function that uses Amazon Bedrock to propose fixes from an allowlist of tools, running read-only actions autonomously and pausing for human approval before infrastructure changes. The post demonstrates the flow with a Lambda function whose 3-second timeout is raised to 30 seconds after a single approval.
AWS ran a six-week program pairing non-engineering professionals with mentors and tools like Amazon Bedrock AgentCore and the Strands Agents SDK to build working AI prototypes. Four participants with no engineering background built WealthWise, a multi-agent financial advisory tool with five agents on Amazon Nova models, which won first place. The article says participants who completed the phased program retained three times more practical skills than those in two-day intensive formats.
AI is getting REALLY good at building your wardrobe. I built an app with GPT-6 Astra that picks my outfit every morning based on live weather, with me as the model. It's super simple to do: > Upload a few full-body photos and one face photo > Add your height, sizes, and fit notes > List the colors you like and the ones you refuse > Paste the master prompt and let it build for 1 to 2 hours One less decision every morning :^)
Michael Lynch warns software bloggers against meandering intros, misjudging reader knowledge, assuming readers have read earlier posts, excessive formality, and overreliance on links instead of explaining terminology. He advises that an article should still make sense even if readers click no links. Simon Willison endorses the advice and argues that writing in one's own voice matters as more developers delegate writing to AI.
Learn more about identifying AI-generated content: https://blog.google/innovation-and-ai/models-and-research/google-deepmind/synth-id-ai-content/
Want to check if an image, video, or audio file was made using AI? Here’s how: 1️⃣ Go to https://synthid.com and upload an image, video, or audio file 2️⃣ The portal scans the media to detect if the file contains a SynthID watermark from Google or our partners
Allie K. Miller outlines three agent workflows that work like an executive assistant and need only calendar access. The agent screens junk signups and sends only high-signal email recaps, routes speaking and advising inquiries with org research and a worth-your-time verdict, and builds a living CRM from forwarded emails that flags relevant contacts for follow-up.
Lauren Tan recommends new Grok Bot users first connect regularly used apps such as calendar, Slack, issue tracker, CRM, and Google Drive so the bot has work context and needed tools. She advises starting with one primary bot before adding specialized bots, which can be designed or chosen from the bot marketplace.
DAIR.AI has introduced MCP tools that let Codex, Claude, or Grok bots discover and explore a curated index of top AI papers. The index covers papers the author featured on X over the last couple of years, and the tools support summarizing papers, building literature reviews, finding SOTA results, and visualizing papers. Further benchmarks and regular additions are promised in the coming weeks.
Try the PixVerse plugin → https://app.pixverse.ai/cli/marketing
Your next video starts in the chat. The PixVerse plugin lets you create from text, images, or video references right where you’re working on the idea. Here’s how to try it: → Select the PixVerse plugin. → Describe a scene, add an image, or provide a video reference. → Specify the model, duration, resolution, and aspect ratio. → Ask it to generate.
Orange AI released "podcast-to-article," a free MIT-licensed open-source skill that reorganizes podcast transcripts by topic rather than speaker timeline. The author says it keeps every number and original quote while cutting off-topic tangents, and that early readership and engagement were good.
Contact center automation uses AI to handle customer support workflows with little or no human intervention, including voice, chat, and email. Unlike traditional IVR systems, AI contact center software understands intent, retrieves customer data, and routes complex cases to human agents. The guide cites Klarna, Rohlik, and Getmobil deployments of ElevenAgents, with Klarna offering voice support to 35 million US customers.
The final post in O'Reilly Radar's four-part post-training series walks readers through implementing the classic ChatGPT pipeline on Qwen2.5-1.5B, covering SFT, reward model training, and PPO. The walkthrough uses torchtune for SFT and verl, a Ray-based RL framework from ByteDance's team, for reinforcement learning. The author says the goal is hands-on understanding rather than reproducing InstructGPT, which took a large team and thousands of GPU-hours.
👀👀 What we really need is @altryne getting a plugin for what he's working on into the plugin catalog
Trying to have Opus 5.5 build a website that explains Qimen Dunjia (奇门遁甲).
Every launched the Every Agent, a Slack-based agentic coworker whose token costs it passes on to customers without markup. Engineer Paridhi Agarwal explains how she made the agent more token-efficient, and the newsletter says the company moved from personal agents to a single shared company agent.
Anthropic added build-eval and hillclimb commands to its claude-api skill for designing evaluations and iteratively improving applications against them. The article covers eval design principles, including production-representative tasks, headroom and low variance, and guards against overfitting through train/test splits. Two examples report results: a customer support benchmark where cost fell to under half while accuracy rose, and a claude-api skill eval that rose from 66% to 88%.
AIWhy it matters: The article gives a concrete workflow for designing evals and hillclimbing without overfitting, with two worked cost and performance examples that show the tradeoffs.
Claude Code developer Thariq (@trq212) released html-plan, a plugin that makes Claude Code generate self-contained single-file HTML plans instead of lengthy Markdown. The page organizes the plan into a layered tree with progressive disclosure, numbered decision points, and in-page feedback that can be pasted back into Claude Code. Install it with claude plugin marketplace add anthropics/claude-plugins-community, then claude plugin install html-plan@claude-community.
A data analysis agent built by @Sumanth_077 separates generation, deterministic guardrails, and review: Qwen writes read-only SELECT queries, code enforces hard rules such as a single SELECT, SQLite read-only mode, and a 200-line limit, and a separate TypeSafe AI Jev model checks question clarity, SQL relevance, and whether answers are grounded in returned rows. Answers that fail grounding are marked as unverified drafts while the SQL and data are kept for human inspection.
The xAI Cookbook now has ten runnable Grok API examples across three tracks: real-time voice agents, multimodal generation, and live X data analysis. The author says four voice examples show the same Realtime Voice API across WebSocket, WebRTC, Twilio phone, and mobile transports. The four multimodal examples chain understanding, image generation or editing, video, and TTS, with Grok making creative decisions and Imagine models executing them.
Jerry Liu argues that OCR, long dominated by brittle legacy systems, can be solved accurately and cheaply by applying agentic intelligence. He says a properly tuned agentic OCR dynamically allocates extra compute to complex elements, reviews and corrects failures, and builds semantic meaning across the page. He contends frontier models are overengineered for this task in cost and latency yet still struggle with complex edge cases.