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Claude Blog: Building intelligent apps for Apple platforms with Claude in the Foundation Models framework
Today we're releasing Foundation Models framework support for Claude through a new Swift package that lets Apple developers use Apple's Foundation Models framework to call Claude for more complex workflows. Apple’s Foundation Models framework gives developers access to tap into models natively from Swift. It is very easy to use and can return typed Swift values through guided generation in as few as three lines of code. Developers can use this to tap into Apple’s on-device models for fast, local tasks like summarization or extraction. Developers can now use Apple’s Foundation Models framework to hand off to Claude when a request calls for multi-step reasoning, code generation, and more. Claude can also search the web for current information and execute code for data analysis. Stream Claude's response back into the same view. Because Apple's framework returns typed Swift values from @Gene...
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Thibault Sottiaux: 2026 is the year companies start seriously caring about model efficiency and ...
2026 is the year companies start seriously caring about model efficiency and reliability as it becomes critical infrastructure|@thsottiaux · 热度 6193 · 2026-08-23
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Guillermo Rauch: Our philosophy on extending 𝚏𝚡: open protocols
Our philosophy on extending 𝚏𝚡: open protocols. ∙ MCP (modelcontextprotocol.io) ∙ Skills (agentskills.io) ∙ Plugins (agent-plugins.org) And the best one, Unix: ① Small programs that do one thing well and compose by calling other programs. ② 𝚕𝚒𝚋𝚏𝚡 that enables embeddability into more complex programs. You should be able to build your own CLI, background agent, software factory. Local or cloud.|@rauchg · 热度 819 · 2026-08-23
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Garry Tan: Prediction: systems of record will need to become AI harnesses or face replac...
Prediction: systems of record will need to become AI harnesses or face replacement by agents|@garrytan · 热度 726 · 2026-08-24
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Guillermo Rauch: Intelligence is getting cheaper
Intelligence is getting cheaper. @OpenAI Sol's price reductions & discounts on Vercel AI Gateway have made Sol our fastest-growing frontier model. This shows ① that the demand for intelligence is highly elastic: as inference costs fall, usage grows rapidly. ② If you're not using a gateway, you're missing out on this incredible price volatility, which lowers your operating costs and increases your margins. It's no wonder the router space has heated up… gateways are inevitable.|@rauchg · 热度 392 · 2026-08-23
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Madhu Guru: How to build great evals - part 7
How to build great evals - part 7. The Goldilocks principle for eval construction. Your evals should measure at the level of the various jobs to be done, not just the final answer. E.g. consider a financial analysis agent. It's ultimate output is a stock recommendation. The most common mistake I see is teams create a golden set of right answers and check if the agent recommended the "right” stock. The problem here is that there are probably a bunch of meaningful jobs that happened before this recommendation. E.g. 1/ Understanding the client: their portfolio, risk tolerance, investment horizon, goals, constraints 2/ Gather evidence: latest data points on the different stock stocks, the sectors, macro environment, Fed policy, recent and upcoming news events 3/ Analyze the data: revenue growth, valuation guidance, growth projections and produce a narrower number of candidate stocks 4/ Make a recommendation: stock ticker name, bid/sell price, timeframe Each of these is a stage and produces an intermittent output. Each of them can (and maybe should have) their own eval so you can diagnose issues. If the final recommendation is wrong, a well designed eval set would tell you: Client understanding : 92%, Evidence extraction : 92%, Data analysis: 70% Recommendation: 75% Now you know where to go dig. And you might go, man the data analysis step is too complex and I need to break it down into a set of jobs to be done, and construct eval sets for them. Not too granular. Not too coarse. Just right. Make your eval set as granular as you need to diagnose and act. Drop your eval questions in the comments and I will answer in future posts. Share this with your teammates! See you tomorrow.|@realmadhuguru · 热度 129 · 2026-08-24