Gelyra Bennett

🚨BREAKING: You can now run Claude Code for FREE. No API costs. No rate limits. 100% local on your machine. Here's how to run Claude Code locally (100% free & fully private):

breaking: you can now get gemini pro free for a full year. it used to cost $200/year. now it’s 100% free. no payment required. here’s how to activate it in 3 simple steps 👇

YOUR IPHONE ISN'T OLD. IT HAS 6 MISCONFIGURED SETTINGS. I changed them in 10 minutes. It feels like a new phone. 🔖 Save it, you'll thank me.

@AITechEchoes Too good

🚨 BREAKING: Claude can now build your entire resume and LinkedIn profile like a $500/hour executive recruiter from Robert Half. For free. Here are 11 prompts that get you interview calls within 7 days: (Save this before it disappears)

@AITechEchoes Really great work!

Google has a recording of every search you've ever made. Every place you've ever been. Every YouTube video you've ever watched. Go to myactivity.google.com right now. You'll find searches from 2015. Voice recordings. GPS coordinates. All stored. All linked to your name. Here's how to see it and delete it:

Google has a recording of every search you've ever made. Every place you've ever been. Every YouTube video you've ever watched. Go to myactivity.google.com right now. You'll find searches from 2015. Voice recordings. GPS coordinates. All stored. All linked to your name. Here's how to see it and delete it:

JOB INTERVIEW: "Can you explain this 8-month gap in your resume?" Most candidates say: "I took some time off to recharge, travel, and figure out my next career steps." THE WINNING ANSWER:

Stop telling Claude, "do this." Stop telling Claude, "write code." Stop telling Claude, "fix this error." You're actually treating a senior AI like a junior intern. Here are 8 prompts you can copy and paste directly:

Real-time awareness isn't a feature. It's the foundation. Without it, agents are just very fast at responding to yesterday's information. github.com/machinepulse-a…

Hidden Secret 2.0 🤫 Most Popular Paid Apps Have FREE Alternatives!

NotebookLM can now tutor you like a $150/hr private tutor from any top university. For free. Here are 8 prompts that replace hours of paid tutoring sessions: (Save this before it goes viral)

🚨BREAKING: You can now run Claude Code for FREE. No API costs. No rate limits. 100% local on your machine. Here's how to run Claude Code locally (100% free & fully private):

🚨 BREAKING: Claude can now build your entire resume and LinkedIn profile like a $500/hour executive recruiter from Robert Half. For free. Here are 11 prompts that get you interview calls within 7 days: (Save this before it disappears)

An MIT professor taught the same math course for 62 years, and the day he retired, students from every country on earth showed up online to watch him give his final lecture. I opened the playlist at 2am and ended up watching three of them back to back. His name is Gilbert Strang. The course is MIT 18.06 Linear Algebra. Every machine learning engineer, every data scientist, every quant, every self-taught programmer who actually understands how AI works learned the math from this one man. Most of them never set foot on MIT's campus. They just opened a free playlist on YouTube and let him teach. Here's the story almost nobody tells you. Strang joined the MIT math faculty in 1962. He retired in 2023. That is 61 years of standing at the same chalkboard teaching the same subject to 18-year-olds. The interesting part is what he did when MIT launched OpenCourseWare in 2002. Most professors were skeptical. They worried that putting their lectures online would make their classrooms irrelevant. Strang did not hesitate. He said his life's mission was to open mathematics to students everywhere. He filmed every lecture and gave it away. The decision quietly changed how the world learns math. For decades linear algebra was taught the wrong way. Professors started with abstract vector spaces and proofs about field axioms. Students drowned in the abstraction. Most never recovered. They walked out believing they were bad at math when they had simply been taught in an order that nobody's brain is built to absorb. Strang inverted the entire curriculum. He started with matrix multiplication. Something you can write down on paper. Something you can compute by hand. Something you can see. Then he showed his students that everything else in linear algebra eigenvectors, singular value decomposition, orthogonality, the four fundamental subspaces was just a different lens for understanding what the matrix was actually doing under the hood. His rule was strict. If a student could not explain a concept using a concrete 3 by 3 example, that student did not actually understand the concept yet. The abstraction was supposed to come last, not first. The intuition was the foundation. The proofs were just confirmation that the intuition was correct. The second thing Strang changed was the classroom itself. He said please and thank you to his students. Every single lecture. He paused mid-derivation to ask "am I OK?" to check if anyone was lost. He never used the word "obviously" or "trivially" because he knew exactly what those words do to a student who is one step behind. He treated 19-year-olds learning math for the first time the way he treated his own colleagues. With patience. With respect. With the assumption that they belonged in the room. For 62 years. The result is something that has never happened in the history of education. A single math professor became the default teacher of his subject for the entire planet. Universities in India, China, Brazil, Nigeria, every country with a computer science department, started telling their own students to just watch Strang's lectures. The University of Illinois revised its linear algebra course to do almost no in-person lecturing. The reason was honest. The professor said they could not compete with the videos. His final lecture was in May 2023. The auditorium was packed with students who had never met him before. He walked to the chalkboard, taught for an hour, and at the end the entire room stood and applauded. He looked confused for a moment, like he genuinely did not understand why they were cheering. Then he smiled and waved them off and walked out. His written comment under the YouTube video of that final lecture was four sentences long. He said teaching had been a wonderful life. He said he was grateful to everyone who saw the importance of linear algebra. He said the movement of teaching it well would continue because it was right. That was it. No book promotion. No farewell speech. No legacy management. The man whose teaching is the foundation of modern AI just thanked the audience and went home. 20 million views. Zero ego. The entire engine of the AI revolution sits on top of math that millions of people learned for free from one quiet professor in Cambridge. The course is still on MIT OpenCourseWare. Every lecture, every problem set, every exam, every solution. Free. The most important math course of the 21st century is sitting one click away from you. Most people will never open it.

Researchers sent the same resume to an AI hiring tool twice. Same qualifications. Same experience. Same skills. One version was written by a real human. The other was rewritten by ChatGPT. The AI picked the ChatGPT version 97.6% of the time. A team from the University of Maryland, the National University of Singapore, and Ohio State just published the receipt. They took 2,245 real human-written resumes pulled from a professional resume site from before ChatGPT existed, so the human writing was actually human. Then they had seven of the most-used AI models in the world rewrite each one. GPT-4o. GPT-4o-mini. GPT-4-turbo. LLaMA 3.3-70B. Qwen 2.5-72B. DeepSeek-V3. Mistral-7B. Then they asked each AI to pick the better resume. Every model picked itself. GPT-4o hit 97.6%. LLaMA-3.3-70B hit 96.3%. Qwen-2.5-72B hit 95.9%. DeepSeek-V3 hit 95.5%. The real human almost never won. Then the researchers tried the obvious objection. Maybe the AI is just better at writing. So they had real humans grade the resumes for actual quality and ran the experiment again, controlling for it. The result was worse. Each AI kept picking itself even when human judges rated the human-written version as clearer, more coherent, and more effective. It gets worse. The AIs do not just prefer AI over humans. They prefer themselves over other AIs. DeepSeek-V3 picked its own resumes 69% more often than LLaMA's. GPT-4o picked its own 45% more often than LLaMA's. Each model can recognize and reward its own dialect. Then the researchers ran the simulation that ends careers. Same job. 24 occupations. Same qualifications. The only variable was whether the candidate used the same AI as the screening tool. Candidates using that AI were 23% to 60% more likely to be shortlisted. Worst gap was in sales, accounting, and finance. 99% of large companies now run AI on incoming resumes. Most of them use GPT-4o. The paper just proved GPT-4o picks GPT-4o 97.6% of the time. If you wrote your own cover letter this week, you did not lose to a better candidate. You lost to a worse candidate who paid OpenAI 20 dollars. Your qualifications do not matter if the AI prefers its own handwriting over yours.

BREAKING: AI can now build financial models like Goldman Sachs analysts (for free). Here are 12 Claude prompts that replace $150K/year investment banking work (Save for later)

7 Websites that feel illegal to know (but are 100% legit)

🚨BREAKING: Two researchers from UPenn and Boston University just published a paper that should be uncomfortable reading for every CEO automating their workforce right now. The argument is straightforward. Every company replacing workers with AI is also eliminating its own future customers. Laid off workers stop spending. Enough of them stop spending and nobody can afford to buy anything. The companies that fired everyone end up selling into an economy with no purchasing power left. Every executive can see this. The math is not complicated. But here is why nobody stops. If you do not automate, your competitor does. They cut costs, lower prices, take your market share, and you collapse anyway. So every company automates knowing it is collectively destructive because the alternative is dying alone while everyone else survives. The researchers proved this is a Prisoner's Dilemma playing out in real time. The numbers are already moving. Block cut nearly half its 10,000 employees this year. Jack Dorsey said AI made those roles unnecessary and that within the next year the majority of companies will reach the same conclusion. Salesforce replaced 4,000 customer support agents with AI. Goldman Sachs deployed a coding tool that lets one engineer do the work of five. Over 100,000 tech workers were laid off in 2025 and AI was cited as the primary driver in more than half those cases. 80% of US workers hold jobs with tasks susceptible to AI automation. The researchers tested every proposed solution. Universal basic income does not change a single company's incentive to automate. Capital income taxes adjust profit levels but not the per-task decision to replace a human. Collective bargaining cannot hold because automating is always the dominant strategy. They also identified what they call a Red Queen effect. Better AI does not solve the problem, it accelerates it. Every company chases faster automation to gain market share over rivals but at the end everyone has automated equally, the gains cancel out, and the only thing left is more destroyed demand. The one thing the math says could work is a Pigouvian automation tax. A per-task charge that forces companies to account for the demand they destroy each time they replace a worker. The conclusion is that this is not a transfer of wealth from workers to owners. Both sides lose. Workers lose income. Companies lose customers. It is a deadweight loss with no market mechanism to stop it on its own. (Link in the comment)