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- This Prompt Obliterated My Distractions (and Tripled My Output)
This Prompt Obliterated My Distractions (and Tripled My Output)
Answer 5 questions, get a custom plan to stay focused and get more done
🥯 Today on Bagel Bots:
🤯 AI Is Growing Faster Than Anyone Expected—And It’s About to Get Wild
⚡️ Cool Tech: China’s $5B Robot Just Declared War on Tesla
🔥 Featured Tool: Generate High-Performing Ad Creatives in Seconds
🤖 Cool new apps for you to check out
đź“° Gen Z Ditches Degrees, Quantum OS Debuts, and the U.S. Goes All-In on AI Education
🧠Today’s Free Prompt: This Free AI Prompt Helped Me Crush My Workday—No Willpower Needed
🤔 Can you guess which image is real and which one is AI? Go vote!
🤯 One Big Story: AI Is Growing Faster Than Anyone Expected—And It’s About to Get Wild
Just a few years ago, AI supercomputers (aka GPU clusters or data centers) were mostly research tools. Today, they’re industrial-grade monsters powering the most advanced models on the planet—and they’re growing at a mind-blowing pace.
According to new data, the raw power of top AI supercomputers has doubled every 9 months over the last six years. We’re talking clusters with over 100,000 chips, $7 billion hardware price tags, and energy demands equal to a quarter-million households. And if current trends hold, the biggest systems by 2030 will require 2 million chips, cost $200 billion, and draw more power than nine nuclear reactors.
What’s driving all of this? One simple loop: Bigger supercomputers lead to more capable models, which attract more investment, which funds even bigger supercomputers. It’s a feedback loop on steroids—and it’s reshaping who controls the future of AI.
🔑 Key Takeaways:
AI supercomputer performance has doubled every 9 months, driven by more chips and better hardware
Hardware costs and power consumption are also doubling yearly, pushing systems into nuclear-scale energy use
80% of AI compute power is now controlled by private companies, with the U.S. dominating global capacity
If growth continues, decentralized training will be necessary just to meet power demands
đź’¬ My Take:
This is what exponential progress actually looks like—and it’s wild. These machines aren’t just supporting AI development, they are the future of AI. And if you’re not paying attention to who’s building them (and where), you’re missing the bigger picture.

👉 So much more in the full report—read it here
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⚡️ Cool Tech: China’s $5B Robot Just Declared War on Tesla
We’re officially entering the I, Robot and Terminator timeline—with XPeng’s founder He Xiaopeng announcing plans to begin mass production of humanoid robots as early as next year. Dubbed “Iron”, the 178cm-tall, 70kg robot is equipped with 62 degrees of freedom and learns entirely from human behavior—powered by XPeng’s in-house Turing AI chipset capable of running 30 billion parameters simultaneously.
Xiaopeng envisions Iron working alongside human laborers in factories by 2025, pushing toward Level 3 autonomy as a baseline for production. While the robot isn’t quite ready to fold your laundry, XPeng is already inviting factory owners to assess its potential for real-world use. With over £5 billion invested in the company’s AI ecosystem—spanning robots, flying cars, and autonomous vehicles—XPeng is gearing up for a future where Iron doesn’t just coexist with humans... but might also compete with Tesla’s Optimus in the ultimate robo-showdown.
🔑 Key Takeaways:
XPeng's humanoid robot Iron is slated for mass production starting in 2025
Designed with 62 active joints and full-body mobility, powered by a custom Turing AI chipset
Aims for L3 autonomy and industrial collaboration with human workers
Part of XPeng’s £5B AI push into robots, flying cars, and autonomous tech
Positioned to compete with Tesla’s Optimus as humanoid robotics moves toward mainstream
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🔑 Key Takeaways:
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Fresh Apps
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Today’s Free Tip: This Prompt Obliterated My Distractions (and Tripled My Output)
Getting work done shouldn’t feel like a constant battle—but between Slack pings, emails, calls, and the urge to check my phone every 12 minutes, it often does. Like many of you, I don’t struggle with laziness—I struggle with distraction. I sit down with good intentions, and before I know it, an hour’s gone and I haven’t done the one thing I set out to do.
That’s why I built this Productivity Coach Mega-Prompt—and I’m not exaggerating when I say it’s completely changed the way I work. I’ve been using it to reset my focus and create weekly strategies that help me get into flow and actually stay there. It’s helped me cut through noise, block distractions, and bang out more meaningful work in less time than ever. If you’ve been feeling scattered, reactive, or like your days keep getting away from you, this prompt is a reset button.
All you have to do is plug in a few quick details about how you work, and ChatGPT will generate a custom 5-question productivity audit—then deliver a personalized action plan designed to fit your brain, your goals, and your schedule. Whether you’re building something big or just trying to stop checking your inbox every 8 minutes, this will help you get control of your time again—and finally get sh*t done.
🔹 1. Clear Ask
You are a world-class productivity coach. I want you to ask me 5 highly focused questions about my current work habits, routines, and environment. After I answer, create a custom, actionable productivity strategy to help me get more done in less time.
🔹 2. Context & Purpose
This strategy will help me become more focused, eliminate wasted time, and create systems that align with my personal goals and daily responsibilities. It should be realistic, specific, and tailored to my exact situation, so I can apply it immediately and see results without completely overhauling my life.
🔹 3. Detailed Input Requirements
Before generating the questions, please take into account the following information about me:
My primary goal right now: [e.g., Finish a writing project, scale my business, reduce burnout]
Typical work environment: [e.g., Home office, open workspace, hybrid]
Biggest struggle with productivity: [e.g., Procrastination, distractions, poor planning]
Available working hours per day: [e.g., 6 hours, flexible schedule, evenings only]
Preferred tone of advice: [e.g., Friendly, strict, motivational, tactical]
âś… Format your five questions clearly and make sure they are tailored to uncover key blockers and habits.
🔹 4. Additional Instructions
Once I respond to your five questions, please return a strategy that includes:
A short summary of my current habits and limitations
A step-by-step action plan (3–5 steps max) I can start implementing immediately
At least one specific time-blocking or prioritization method suited to my situation
A quick list of tools, techniques, or systems I should test
Use clear headings, bullet points, and make the language easy to follow
Ensure tone matches the preference I selected above
Avoid generic advice—make it personal and direct
🔹 5. Perfect Output Every Time
Ask only what you need to build a fully customized productivity system, based on my actual work style and goals. Assume I want to take action immediately and your job is to deliver a no-fluff, zero-confusion roadmap.
đź“° Interesting News
đź§ Nearly half of Gen Z job seekers now believe their college degrees were a waste of time and money as AI tools like ChatGPT reshape the job market faster than traditional education can keep up.
🖥️ Scientists have unveiled QNodeOS, the world’s first operating system for quantum computers, designed to connect different types of quantum machines and potentially serve as the backbone of a future quantum internet.
🇺🇸 The White House just launched a sweeping national initiative to bring AI education to every level of the U.S. education system—from K–12 to workforce training—aimed at building the next generation of AI-ready Americans.
🤔 Which image is real?
One of these images is real, and one was created with AI. Vote for which one you think is real, and tell us why you voted that way. My only goal is to choose such good photos that the majority of votes are wrong.

Which image is the real one? |

The last edition’s results—78% were wrong!
Did you vote in the poll from April 23rd? The bottom image was real! Go back and see the photos here. So what do you think? Are you getting better at spotting AI vs. not?
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