The partnership will see TCS creating a business unit focused on deploying Anthropic's AI models to its customers.

Anthropic has apologized for stealthily throttling its new AI model, Claude Fable 5, with hidden guardrails that undermine both researchers and rivals using it to develop competing systems. The company says it is reversing course and will be more transparent about when the restrictions kick in, even if that means Fable refuses more queries. Fable […]

Good system. One addition that moved the needle for me: ​ I track "capacity conversion" -- when AI saves me 3 hours on a task what do those 3 hours actually become? ​ Most people save time with AI and then fill it with more busywork. The ROI only materializes when you deliberately redirect saved time toward higher-value activities. ​ I keep a simple log: "AI saved X hours on [task]. Redirected to [activity]. Value of redirected time: [$amount]." ​ After 6 months, my actual ROI was 4x higher than the "time saved" metric suggested because of where the saved time went. ​ submitted by /u/JaredSanborn [link] [留言]

These WIRED-tested ebook readers let you take your library anywhere.

Summer is almost here, and that means getting outside, having fun in the sun, and touching grass. But if you need to cool down for a bit, allow me to sing the praises of the library. If your local library system is anything like mine, it probably offers a lot of great things for you […]

The most powerful AI employee, now in Microsoft Teams Discussion | Link

When a platform started with total developer autonomy, teams felt overwhelmed and ended up solving the same problems in completely different ways. The company shifted to enablement over support, working together with teams intensively, and helping teams feel confident and capable, turning the right way into being the easiest way. By Ben Linders

Disclaimer: yeah, I work in AI visibility, so I'm definitely biased on this. But what I want to get into actually cuts against what my own industry sells, so I figure it has a place here. Back in mid-May Google put out its first real guide on how to show up in AI answers (AI Overviews, AI Mode). I saw a bunch of write-ups on it and it was always the same song, structure your headings, add Schema, the usual blah. Except there's a "mythbusting" section in the doc I haven't seen anyone pick up on, and it's the most interesting part. Google says in plain terms that the famous llms.txt file does nothing, that you should stop obsessing over Schema.org, and that chunking is smoke and mirrors. Made me smile a bit since that's basically the package some "GEO" agencies are charging for right now. What they push instead is honestly kind of obvious. They talk about "commodity" vs "non-commodity" content. Like, if an AI can write your article on its own, it'll never cite you, makes sense, it already has the answer, why would it go looking for you. What gets cited is content with something the model doesn't have. A number you actually measured, a test you really ran, lived experience basically. The example that stuck with me (not in Google's guide, somewhere else) is a small blog specialized in robot vacuums, garbage domain authority, and it outranks the New York Times in AI answers. The NYT has a domain like 3x stronger. Except the NYT puts out an affiliate listicle anyone could copy, and the blog guy films his actual tests with real measurements. Guess who gets cited. And this is where it gets useful for you I think. It means for the most part you need neither a tool nor an agency. Take your most generic page, just ask yourself "could anyone write exactly this", and if the answer is yes, add something only you know. You don't even need data. A simple "the first question every client asks me is this" and you're already standing out. It's free and it weighs more than all the tech

Bluesky is launching a communities feature this year, according to its head of product.

Anthropic's usage analytics dashboard is only available to Team and Enterprise org admins. On a Pro or Max plan all you get is /usage and the claude.ai usage page, which show where you stand right now but not where you're heading. I looked at various open-source projects but none quite matched what I had in mind: an all-round control panel for Claude Code that's also a single binary, with no dependencies and no install steps. The other thing I cared about was forecasting the usage limits. Existi

Your voice-supported AI financial planning partner Discussion | Link

The surveillance company Leonardo wants more data : A surveillance company plans to add sensors to automatic license plate readers (ALPRs) that would mean the devices, as well as capture the license plate of passing vehicles, would also sweep up unique identifiers of mobile phones, wearables, and other Bluetooth-enabled devices in those cars, potentially letting law enforcement identify specific drivers or passengers. The technology, called SignalTrace, would turn ALPR cameras from devices focused on tracking cars to ones that can more readily track the location of particular people. ALPR cameras have become a commonly deployed technology all across the U.S.; SignalTrace would make some of those cameras capable of collecting much more data...

Google DeepMind is funding research into the potential dangers of situations where millions of different AI agents interact with each other online. According to Rohin Shah, who directs the company’s AGI safety and alignment research, the mass-market arrival of agents that can carry out tasks without human oversight and follow instructions given to them by other…

TL;DR - Getting an app to run is now the easy part. AI is very good at producing something that...

AI aside, Golden Gate includes a bunch of subtle-but-helpful improvements.

If you're someone who needs to (or likes to) take their work on the go, a portable monitor will make a huge difference. These are my favorite that I tested.