| | | Hey, AI Enthusiast! | Welcome back to the #1 AI newsletter on the planet! | Hereâs what we have today: | OpenAI shares the four parts of a good ask. The internet scored AIâs old goalposts. Audiobook characters start talking back. Neuralinkâs implants go weeks without a reset.
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| | | Prompting | OpenAIâs Four-Part Prompt Recipe | | When you ask AI for something, itâs easy to leave out important details without realizing it. | But the AI fills them in anyway, with guesses. | OpenAI has a fix, and you can find it in the companyâs newest model guide. | What they say is to give the model enough direction so it never has to guess at the decisions that matter most. | The guide doesnât stop there, though. | It walks you through exactly what that direction looks like. | They break it down into four parts: | The result you want. Who itâs for. The context and limits that apply. What counts as done.
| Letâs take a look at a simple example: | âWrite a toast for my sisterâs wedding.â | That covers the result and youâll get something decent, but the AI is going to invent the rest: | | Each of those is a decision that matters. Leave them out, and the AI is going to make every one of them for you. | Now you might think the fix is writing more (hint: it isnât). | OpenAI pushes back on that, as well. | One of its own devs says models read nuance so well now that piling on instructions drags results down. | The four parts beat the word count by a long shot. | Go look at the last thing you typed into a chatbot, and count how many of those parts you included. | Knowing the four parts is easy. Making sure you type all four of them, every time, is where it all falls apart. | Our take: A vague answer is easy to blame on the AI. But every blank you leave becomes a choice the model makes for you, and it has no idea what youâd have picked. The details that feel too obvious to mention are the ones it needs most. |
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| | | Together with Wispr Flow | The Ask Nobody Has Time to Type | | The result, who itâs for, the context, and what done looks like. | It all lives in your head. But when you start typing out what you want, those are the important details you leave out. | Thatâs where Flowâs Transforms can help. | Prompt Engineer turns your rough thoughts into the full ask. | It works in every AI chat app you use. | All you have to do is say what you want, the way it comes out. | â3 day trip. Kids are 6 and 9. Nothing before 9AM. We hate museums.â | Highlight it and hit one shortcut. Flow rebuilds it in place as a structured prompt with a title, role, task, context, and format. | It gets the same rambling sentence from you. The AI gets the whole assignment. | The prompt lands where you type, before you send it, that way you can edit it first. | |
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| | | AI Progress | The Internet Scored AIâs Old Goalposts | | For ten years, people on Hacker News have been setting challenges for AI in the comments. | Things like passing a Turing test or driving a car in the snow. | Someone went back through all those old threads and pulled every challenge onto one page. | Then they let people vote on which ones AI has met. | In two days, 9,694 people cast 100,590 votes. | You can look through them, but here are a few highlights. | Writing working code from a few plain sentences (from 2020). 87% say AI does it now. | Full self-driving in every condition imaginable (from 2019). 78% say no. | A robot that cleans a toilet (from 2023). 69% say it hasnât happened yet. | Notice a pattern? | Anything that happens on a screen is falling fast. Anything with wheels or a mop, not so much. | Our take: The challenges that sounded the hardest, like writing code, fell first. The ones that sounded easy, like cleaning a bathroom, are still standing. AI learned to code by reading code. A cleaning video, on the other hand, shows a toilet getting scrubbed, but not how hard to press or how to hold the brush, and no two bathrooms look the same. | The catch: The voters are Hacker News readers who chose to show up, not a scientific sample. |
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| | | Books | Audiobook Characters Talk Back | | For a lot of people, theyâd rather listen to a book rather than sitting down to read it. | Normally, only one narrator voices every character in a book. | But if you have a full cast narrating multiple characters, it gets hard to keep track of whoâs talking. | Audible is adding AI to help with that, and itâs going to take things one step further. | Its new character guide shows whoâs talking right on the player itself as you listen. | Plus, it has spoiler-free cards for each character. | Thatâs not the most interesting part, though. | Itâs Interactive Stories. | Instead of only listening, youâll get to talk to characters from the book, and theyâll answer back in real time. | The first one puts you in a conversation with Renfield, Draculaâs servant. | In November, a new one will arrive along with a new Audible original. | Our take: Audiobooks have always talked at you. This is the first time the story stops and waits for your answer. Itâs a bonus on a couple of titles for now, but if listeners take to it, books that only talk at you might start to feel a little one-sided. |
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| | | Coming in Hot | AI Tools of the Day | â
 todo.is takes any to-do you text it on WhatsApp or Slack, then researches, browses, and messages you when itâs done. đ kdpbook.io writes, illustrates, and formats a print-ready Amazon book from one sentence, cover and Kindle file included. đĄď¸ Daxeon guards your Discord server from scams, deleting bad links in seconds and blocking anyone posing as your staff. đ Basquio reads your brief, data files, and notes, then builds the matching deck, written report, and Excel workbook. đ OpenKnowledge turns any notes folder into a Google Doc-style editor your AI works in, free and open source on GitHub.
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| | | Brain Implants | Neuralink Goes Weeks Without a Reset | | Neuralink is one of those inventions that makes you go âWOWâ the first time you see it in action. | If youâve never seen someone move a cursor with their brain, head over to YouTube and check it out. | The cool part is how it works. | The implant picks up electrical signals from the part of the brain that controls movement. Then software, called a decoder, turns those signals into cursor moves. | But thereâs a problem many people donât know about. | Brain signals donât stay the same. The implantâs tiny threads shift a little over time, and the neurons themselves change. | That means a decoder trained on yesterdayâs signals slowly stops matching todayâs, and the cursor gets less accurate. | To fix it, users go through a recalibration, where the software relearns their signals. | For some Neuralink users, thatâs been about 10 minutes, every single day. | Neuralink has found a way around it using something its patients made without even trying. | Every hour they spent using the implant added to a pile of their own brain data. | Over two years, that pile grew to over 50,000 hours. | So, Neuralink trained AI on all of it, and now the software recognizes each personâs signals even as they shift. | Decoders built this way kept working for weeks instead of days. For some participants, calibration dropped to about 10 minutes a week. | Our take: Picture your phone needing 10 minutes of setup every morning before it worked right. Youâd stop using it. Brain implants make headlines for what they let people do, but going weeks without a reset is what makes one feel less like an experiment and more like a device people rely on. |
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| | | Interesting AI | Metaâs AI Wants Out of Your Phone | | At some point in your life, maybe even today, youâve gone digging through the cushions in your couch to find your TV remote. | Well, Meta wants to put a stop to that. | They built Home Link, a small USB-C plug that sits near your router and connects its AI, Muse, to your home network. | From there, Muse talks to your TV and speakers, plus other smart gear on your network that supports it. | People have already built add-ons for things like Philips Hue lights and Samsung TVs. | Plus, Meta opened up the code for anyone who wants to build their own Muse gadget. | Losing the remote might finally stop mattering. |
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| | | Learning | A Free Course on Why AI Gets It Wrong | | When you use AI enough, you start to notice it gets things wrong in weird ways. | If you donât know why it happens, itâs hard to tell which answers to trust. | Anthropic has a free course that explains it. | Itâs part of Claude Academy, the companyâs free learning site, built partly on the way it trains its own staff. | The course, AI Capabilities and Limitations, walks you through why AI misfires in 13 lessons. | It covers where AI is strong, like popular, well-covered topics, and where it slips, like anything rare or recent. | It also explains why a long chat starts losing track of what you said earlier, and why a new chat doesnât remember the last one. | You donât need a technical background or any prior AI experience to take it. | There are also separate tracks for each Claude product, from everyday chat to Claude Code. | Our take: A wrong AI answer feels random until you know why it happened. This course turns those misses into a few limits youâll start to recognize, and once you spot which one you hit, you know when to trust an answer and when to check it yourself. |
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| | | Prompt of the Day | Do My Job in 1985 | Important Note: Youâll need to click the button to get the complete prompt. | | This prompt sits you across the desk from an old-timer who did your exact job in 1985, before the inbox ran your morning or a phone came home with you at night. You leave knowing the part of your job youâre paid for, how many hours a week sit in the path of AI, and three moves to double down on this month. |
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| | | Thatâs all for Saturday! | | How did we do today?Rate this issue, then tell us what you thought. We value your input and will use it to make TAAFT better for you. | | | Thanks for reading, | â Thereâs An AI For That |
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