ChatGPT just got its own version of Google Business Profiles. OpenAI launched “Businesses in ChatGPT” in beta. Companies can now claim their profile inside ChatGPT, fix their info and see how often the AI mentions them. - Free to claim with a regular ChatGPT account. You verify by phone, text or DNS - The Business Hub dashboard tracks mentions, website clicks and the top topics people find you through - You can upload product feeds with prices and stock levels, and Shopify stores can connect directly - Business Agents: a branded chat agent built on your products and policies. Only US ecommerce and online service businesses can build one for now - Agents can be sponsored and used as the landing spot for ChatGPT Ads, which now run in 89 countries with 100K+ advertisers - Reality check: one live dashboard showed 690 mentions and only 24 clicks over 28 days (about 3.5%) - OpenAI hasn’t said claiming a profile gets you recommended more often - This comes after OpenAI killed in-chat checkout in March, when Walmart saw it convert 3x worse than sending people to its own site To me this looks like local SEO all over again. If customers are finding businesses through ChatGPT, someone has to set up and manage that profile, and you guys are already the people clients call for that kind of thing. Are you claiming profiles for yourself or your clients yet? Read more: https://openai.com/index/introducing-businesses-chatgpt/

Claude now has its own spreadsheets, whiteboards and data dashboards, plus partner apps that run right inside the chat. - New artifact types: Claude Sheets (formulas, multiple tabs), Whiteboards, and Claude Data (formerly Dashboards) - Claude Data connects to sources like Snowflake and Salesforce to build dashboards and data stories - Interactive connectors embed partner apps like Adobe and Atlassian directly in Claude - Plugins from Salesforce (beta), NetSuite and Workday (beta) ship with built-in skills for sales prep, finance analysis and HR tasks - Auto-connect (beta) on eligible Team and Enterprise plans: an admin sets up an app once and employees connect on first use - Enterprise admins can limit which users get which connectors and restrict what each connector can do - Claude Meetings (notes and doc updates during calls) is coming soon, no date yet Which parts of your stack would you keep in Make or n8n, and which would you move into Claude now that it can build sheets and dashboards on your data? I see myself using the whiteboards feature for brainstorming sessions. Read more: https://claude.com/resources/articles/sheets-whiteboards-data

Anthropic dropped a new top-tier model yesterday, and the cost per task is the part I'd look at first. Claude Fable 5.2 is live on the API now, and Anthropic says it beats Opus 5.5 on most of their evals while often costing less per task at lower effort settings. - Model ID claude-fable-5-2, available on the Claude Platform, AWS, Google Cloud and Azure - $8 input and $40 output per million tokens, fast mode is $16 and $80 - Up to 30% faster output than Fable 5.1, per Anthropic - At High effort it roughly matches Opus 5.5 at Max on FrontierCode 2.0 for about half the cost per task - AutomationBench (business workflows): 51.4% vs 42.5% for Opus 5.5, but Gemini 4 Carbon still leads at 53.9% - Mythos 5.2 is the same model with fewer safeguards, only for vetted orgs - Preserved thinking now applies to all API accounts, so check your integrations - Anthropic still calls Opus 5.5 the daily driver and Fable the pick for the hardest work Are you guys going to route your hardest agent steps to Fable 5.2, or is Opus 5.5 still enough for what you're building? For me, Opus 5.5 is plenty for what I need. Read more: https://www.anthropic.com/claude-fable-and-mythos-5-2

Google just opened up Gemini Notebook to developers, and it ships with an MCP server. The short version: you can now create notebooks and push sources into them from your own code or straight from Claude Code, no clicking around the UI. - REST API plus a remote MCP server, both in Public Preview - 7 MCP tools: create, get, list and update notebooks, plus create, get and list sources - Sources: web pages, YouTube videos, plain text and Markdown - Setup docs for Claude Code and Cursor, and it works with any Streamable HTTP MCP client - Free during the preview, with a limit of 20 new sources per minute per user - Up to 500,000 words per source, 50 sources per notebook on the free tier - Personal Google accounts only for now, Workspace accounts aren't supported yet - Pre-GA, so expect breaking changes The use case I keep coming back to: an agent that watches a client's site, YouTube channel or docs and keeps a research notebook current without anyone touching it. What would you pipe into a notebook automatically if you could? Drop your idea below. Read more: https://developers.google.com/notebook/docs

Another open-weight model just showed up near the top of the leaderboards, and this one is worth a look if you run agents all day. Moonshot shipped Kimi K3.1 Pro on its API, with weights promised by Nov 4, and Artificial Analysis says that would make it the top open-weights model. - Scored 55 on the Artificial Analysis Intelligence Index, 4th of 215 models (independent eval) - $2 per 1M input tokens, $10 per 1M output on Kimi's API - 1M token context window - Slow and chatty: about 51 tokens per second, and 150M output tokens to run the index vs an 87M median - Terminal-Bench 4.0: 65.7% vs Claude Opus 5.5 at 66.4% (Kimi's own numbers) - API IDs: kimi-k3.1-pro and kimi-k3.1-pro-highspeed (Kimi claims 2 to 3x faster) - Weights due by Nov 4, license not stated yet Would you move any of your agent workflows to an open model at this level, or is speed still the dealbreaker? Read more: https://www.kimi.ai/blog/kimi-k3-1-pro