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There’s a mysterious new piece of hardware trying to steal your iPhone's spot on the nightstand, and it’s coming from the last place you would ever expect: a literal rocket company.
Here’s the tea: The Wall Street Journal dropped a massive report revealing that SpaceX secretly showed off a prototype of a "handset-like" AI device to wealthy investors right before the company's historic public offering.
Translation? It might be a phone, or at least a phone-adjacent gadget, though nobody is totally sure just yet.
The anonymous sources claim this mystery device is remarkably slim, even thinner than a standard iPhone, sitting somewhere in the design realm between a miniature touchscreen device and a dedicated AI assistant like the Rabbit R1. SpaceX apparently told investors that the hardware aesthetics are still in the early stages, so we shouldn't get too attached to the current look.
But of course, we can't have a tech rumor without an absolute plot twist. Elon Musk immediately took to X to call the entire media report "utterly false." So, are we looking at a top-secret gadget or an incredibly elaborate rumor? I guess we’ll find out soon.
But in the meantime, here’s what this mystery gadget is said to comes with:
According to the report from Engadget, this pocket-sized device packs a high-performance Qualcomm Snapdragon chip, and runs on an independent, custom-built operating system. The whole point? Giving you a direct, unmonitored portal to xAI services like Grok without needing a standard smartphone.
Granted, nobody is entirely sure if SpaceX actually intends to mass-produce this thing for the public, but the strategic reasoning behind building your own hardware is incredibly obvious.
Think about the roadblocks of running an AI app on someone else's turf:
The App Store Tax: Right now, if you subscribe to Grok through an iPhone, SpaceX has to hand over a massive cut of that revenue directly to Apple.
The Gatekeeper Problem: Third-party developers are entirely at the mercy of Apple and Google’s strict app store regulations.
The Escape Route: Building proprietary hardware is exactly how tech giants like Meta are trying to break free from the iOS and Android duopoly.
Elon Musk has historically dragged his feet when it comes to entering the brutal smartphone market, but the foundation is already laid. Thanks to SpaceX’s existing partnership with T-Mobile, which brought Starlink satellite connectivity straight to standard cell phones, the company already has the exact cellular network access needed to make a standalone AI device highly functional.
Then again, given Elon’s track record, it’s always best to take these hardware leaks with a massive grain of salt. While SpaceX usually delivers on its technical promises far more reliably than Tesla, there’s a very high probability this prototype was cooked up simply to dazzle Wall Street investors before the IPO rather than kick off a brand-new consumer electronics division.
But to refresh your memory, OpenAI is currently building its own highly secretive AI gadget alongside Apple’s legendary former design chief, Jony Ive. OpenAI CEO Sam Altman teased that their upcoming device will feel "more peaceful and calm" than a disruptive iPhone. To speed up production, OpenAI just successfully poached Apple's Vice President of Vision Pro Hardware Engineering, Paul Meade, to lead the charge.
The tech world is clearly racing to build the next big thing. Let's just hope these tech titans remember that early pioneers like Humane and Rabbit tried to replace the smartphone with AI pins and orange walkie-talkies, and well, that did not go great.
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👩💻 AI Layoffs Are Backfiring: Companies Are Quietly Rehiring the Humans They Fired
It turns out that swapping your entire human workforce for shiny new robots isn't the absolute corporate flex companies thought it would be, and now executives are paying out the nose, literally, to completely undo it.
Remember back in 2024 and 2025 when corporate boards got a little too intoxicated by the AI hype cycle? They started firing talented people left and right, bragging to shareholders about replacing them with cheap, automated chatbots. Yeah, about that, it’s officially not going great.
Across multiple major industries, businesses are currently crawling back to the exact employees they laid off in the name of automation, quietly offering them their old jobs back. Now, it’s not because these CEOs suddenly had a change of heart or felt bad about the holiday layoffs. It’s simply because the robots are completely failing to cut it in the real world.
The absolute juiciest example of this corporate backtracking is happening right now over at Ford Motor Company. Ford went all-in on automation, deploying over 900 AI-powered camera systems to take over manufacturing quality control.
The result? Mass recalls, tanking quality metrics, and billions of dollars in losses.
To save the brand, Ford had to scramble and rehire over 350 veteran, retired engineers. Inside the company, these legendary specialists are affectionately called the "gray beards." Why? Because they carry decades of unwritten, human manufacturing intuition that an algorithm simply cannot replicate.
Ford’s Vice President of Hardware Engineering, Charles Poon, openly confessed that the company "mistakenly" assumed advanced software could replace human judgment. Once the gray beards came back to manually hunt for failure points, Ford immediately shot up to the top spot in the J.D. Power Initial Quality Survey for the first time in 16 years. Talk about a massive win for team humans!
And Ford isn't the only one suffering from extreme AI buyer's remorse:
The Customer Support Crash: Commonwealth Bank of Australia cut dozens of customer service roles to deploy an AI voice bot. The bot completely buckled under the workload, creating a total customer service nightmare and forcing the bank to quickly reverse the redundancies.
The HR Limits: IBM attempted to offload its human resources workflows to automated systems. The AI managed to solve about 94% of standard requests, but the remaining 6% required complex ethical judgment and human empathy. The machine completely stalled, prompting IBM to massively ramp up its human entry-level hiring pipeline for 2026.
The Creative Backlash: Marketing departments everywhere are aggressively rehiring professional writers after discovering that generic, AI-generated content sounds exactly like a robot wrote it, because, well, it did.
Here’s the part of the gossip that really stings corporate bank accounts: this little automation experiment is costing companies a fortune.
First, businesses paid out massive severance packages to lay people off. Then, they spent millions licensing enterprise AI tools and retraining workflows. Now, they’re spending even more capital on recruiters to lure talent back.
And the ultimate kicker? They’re having to hire these professionals back at significantly higher salaries! Experienced workers don't just sit around waiting to be un-fired; the top-tier talent was instantly snapped up by savvier competitors.
The Ultimate Reality Check:
This isn't just standard AI doom and gloom; it’s a vital corporate reality check. The world is finally realizing that large language models are incredible at narrow, predictable tasks, but they completely lack baseline common sense and the ability to read the room.
Even tech gatekeepers like Microsoft and Google are rapidly shifting their official marketing terminology. You'll notice they don't say "AI will replace your staff" anymore; now the buzzword is all about how "AI is your collaborative co-pilot."
The ultimate winners of this era won't be the companies that fire everyone the fastest to automate. The winners will be the smart operators who figure out how human intuition and machine intelligence actually work together as a team.
Lesson of the day: Artificial intelligence is a deeply powerful tool, but it’s not magic. Do not fire your best people just to find that out the hard way.
How Much Is Your Billing Lag Actually Costing You?
Most SaaS finance teams know their billing process isn't perfect. Few know what it's actually costing them.
Answer 5 quick questions — contracts signed per month, ACV, days to first invoice, error rate, DSO — and the Tabs Billing Lag Calculator gives you a dollar figure benchmarked against top SaaS companies.
It takes two minutes. The number might surprise you.
Calculate your billing lag and see where you stand.
🧱 Around The AI Block
👉 How to create AI avatar virtual tour guide videos for national parks & adventure brands with Pippit.
🤑 Meta, like SpaceX, looks to turn excess AI compute into cash.
🫢 Meta puts rate limits on its smart glasses' Conversation Focus feature.
🦾 Cloudflare forces AI frms to split crawlers or face blocks.
💁♀️ Rapid spread of AI may worsen global inequality, UN warns.
😓 UN report says policymakers are struggling to keep up with pace of AI development.
🛠️ Trending Tools
For the Lifelong Learners: Math AI is a private tutor. You snap a photo of any problem—from basic arithmetic to high-level calculus—and it provides a step-by-step breakdown. Instead of just giving you the answer, it explains the why behind every move, making it perfect for mastering complex subjects on the fly.
For the Visual Stylists: Sketch To converts photos into various sketch styles (pencil, watercolor, comic) or does the reverse: turning a simple drawing into a hyper-realistic image. The "Professional Mode" offers high-res renderings that are ready for print or web.
For the Instant Founders: AnyLogoGenerator lets you type in a few keywords of your style and vibe, and get dozens of professional, high-quality variations. It handles the color theory and layout for you, so you can grab a version that fits your brand.
For the Content Creators: Qwen3-TTS is an open-source model that can clone any voice with just a 3-second sample and generate natural speech in 10 languages. The best part? You can actually command the emotion via text (e.g., "[Speak with excitement]") and it responds with a near-zero latency of 97ms.
🤖 AI Workout Of The Day: Come Up With Engaging and Insightful Interview Questions
Engaging and insightful questions during any kind of interview are very important.
It makes sure your interviews are not only entertaining but also full of valuable content for your listeners.
💡 Prompts to try:
Generate a list of questions for a podcast interview with an expert on [topic]. You'll complete this task as follows:
1. Research the expert's previous work, publications, and any recent interviews to understand their perspective and area of expertise. Identify key themes and topics that the expert is known for within the [topic] area.
2. Divide the interview into sections based on different aspects of [topic] or the expert's work. Consider including questions that delve into current trends, controversial issues, or future developments in the field.
3. For each section, generate a list of initial questions that are open-ended and encourage detailed responses. Ensure that questions are respectful, relevant, and tailored to the specific expertise of the interviewee.
4. Evaluate the questions to check for duplication, ensure a logical flow, and confirm that they collectively provide a comprehensive view of the [topic]. Make adjustments to prioritize the most crucial inquiries while maintaining a balance of depth and breadth in coverage.
5. Provide a finalized list of questions, organized by section, ready for use in the podcast interview.Is this your AI Workout of the Week (WoW)? Cast your vote!
That's all we've got for you today.
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