Taylor Farms stirred confusion on FDA test and provided a vague recall list.
Sila's fresh $300 million round will help it make enough of its silicon-carbon anode material to power more than 100,000 EVs.
Substack will now help users determine whether what they're reading may have been written by AI. A new tool coming to the platform can scan posts, notes, replies, and comments to provide an estimate of how much text could be AI-generated or written with AI assistance, according to a blog post published on Tuesday. The […]
The company donated more than $3.6 million to conservative groups between 2020 and 2025, including $1 million to the MAGA Inc. super PAC.
Pat Gelsinger wants to pave the way to ever more powerful artificial intelligence using tiny beams of light.
The latest release of Android Studio, Quail 2, now stable, expands Gemini/AI Agent Mode inside the IDE by enabling multiple AI conversations in parallel and further advancing Google's push to integrate AI-powered workflows directly into Android Studio. It also enhances debugging and profiling capabilities and makes it easier to explore experimental features. By Sergio De Simone
With code coming in faster and faster, we've been losing track of context, what's out of date, the source of truth, etc. Also with individuals spending less and less time on any one problem, finding an expert to answer questions has become challenging. People don't have that single domain of expertise like we used to. There's too much surface area to cover. Are we the only ones dealing with this? How's everyone else handling it?
Substack is partnering with Pangram to add an AI detection feature.
Apple reportedly fixed the Hide My Email vulnerability that left iCloud+ users' emails not especially hidden.
Einride agreed to buy Flipturn for $38 million in stock.
Most "AI agent" libraries fall into one of two buckets. Either they're a big framework you spend an afternoon configuring, or they're a tiny toy that drops the one feature you actually need in production: the ability to stop and ask a human before the agent does something you can't undo. I wanted the middle. So I wrote yieldagent : a small agent loop you can read end to end, with human-in-the-loop pause/resume built in, and no runtime dependencies. This post walks through how it works and why it's built the way it is. What an agent loop actually is Strip away the branding and an "agent" is a loop: Send the conversation to the model, along with the tools it's allowed to call. If the model asks to call a tool, run it and append the result. Repeat until the model answers without asking for a tool. That's it. The model decides the control flow at runtime; your job is to run the tools and feed the results back. Here's the core, lightly trimmed: for ( let step = 0 ; step < maxSteps ; step ++ ) { const reply = await call ( messages , toolSpecs ); messages . push ( reply ); if ( ! reply . tool_calls ?. length ) { yield { type : " final " , text : reply . content , messages }; return ; } for ( const tc of reply . tool_calls ) { const args = JSON . parse ( tc . function . arguments ); const result = await tools [ tc . function . name ]. run ( args ); messages . push ({ role : " tool " , tool_call_id : tc . id , content : JSON . stringify ( result ) }); } } Everything else in the library is in service of making this loop observable, testable, and safe to run against the real world. Why an async generator Notice the yield . The loop is an async generator, so the caller drives it: for await ( const step of agent ({ call , tools , messages })) { if ( step . type === " tool-start " ) console . log ( " -> " , step . tool , step . args ); if ( step . type === " final " ) console . log ( step . text ); } Every step (each tool call, each result, and the final answer) is handed back to