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// YOUR AI EDGE
GM FIRED 600 IT WORKERS AND IMMEDIATELY HIRED REPLACEMENTS WITH AI SKILLS
Plus: Meta posts $27 billion in profit while 8,000 employees pack boxes, OpenAI puts Codex in everyone's pocket, Cerebras IPOs at a $66 billion valuation, and ArXiv bans AI-generated research papers.
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// TODAY'S SIGNAL
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THE SKILLS SWAP JUST WENT FROM THEORY TO PAYROLL
General Motors cut 600 IT workers last week and started backfilling the same roles with a very specific shopping list: AI-native development, prompt engineering, agent and model development, data engineering. Not "people who can use ChatGPT at their desk." People who can build with AI from the ground up. This wasn’t a restructuring buried in a quarterly filing. GM confirmed the layoffs to TechCrunch, framed them as "positioning the company for the future," and kept hiring. Same department. Different skills. The automaker has been trimming white-collar staff for months. But this round is different because the quiet part is loud: the job you have today and the job GM needs tomorrow are two different jobs, and GM decided not to wait for you to catch up.
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// CAREER MATH
The gap between "uses AI tools" and "builds AI systems" just became a pay grade. Pick one skill from GM’s wish list (prompt engineering is the lowest barrier to entry) and build something with it this month. A portfolio project beats a certification every time.
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// SHORTCUT
Copy, paste, go:
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"I need to update my LinkedIn headline and summary to signal AI fluency without overpromising. My current role is [YOUR CURRENT TITLE] at [COMPANY] in [INDUSTRY]. I want to attract recruiters looking for people who can work alongside AI tools, not just use them casually. Rewrite my headline (under 120 characters) and a 3-sentence summary that positions me as someone actively building AI into my workflow. Keep it specific, not buzzy."
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META MADE $27 BILLION LAST QUARTER. MORALE HAS NEVER BEEN LOWER.
Meta reported nearly $27 billion in quarterly profit, then told roughly 8,000 employees (about 10% of the workforce) they’re out. Internal morale is, by multiple accounts, at an all-time low. Zuckerberg told staff the layoffs aren’t about AI. The company’s capex guidance tells a different story: $125 to $145 billion in 2026, almost all of it pointed at AI infrastructure. Compensation for remaining employees dropped 10%. The company that once competed for talent with free sushi and nap pods is now competing for survival metrics. The pattern is clear across big tech: record revenue, record layoffs, record spending on machines.
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// THE REAL STORY
Profitability and headcount are decoupling. Companies can grow revenue while shrinking payroll. If leadership starts talking about "efficiency" and "AI transformation" in the same earnings call, that’s the signal to start building leverage they can’t automate.
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OPENAI CODEX JUST SHOWED UP ON 100 MILLION PHONES
OpenAI dropped Codex into the ChatGPT mobile app on iOS and Android. Codex started as a desktop coding agent, the kind of tool developers used to spin up entire projects from a text prompt. Now it’s in everyone’s pocket. The mobile version lets you kick off Codex tasks from your phone, then check results later when you’re back at a computer. Think of it as a remote control for an AI employee that works while you commute. OpenAI is racing against Anthropic’s Claude Code and Google’s Gemini to own the "AI does the work while you do other things" category. Mobile access means the starting gun just got louder.
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// THE MOVE
Download the ChatGPT app update and try Codex on one repetitive task you’d normally put off: a spreadsheet formula, a data cleanup script, a first draft of meeting notes. The learning curve is the task itself.
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CEREBRAS JUST HAD THE BIGGEST TECH IPO IN A YEAR
Cerebras Systems priced its IPO at $185 a share, raised $5.5 billion, then watched the stock pop 108% on day one to close at $311. That’s a $66 billion valuation for a company most people have never heard of. Cerebras makes AI chips. Specifically, it makes the largest computer chip ever built, a single wafer-scale processor designed to train AI models faster than anything Nvidia offers. The IPO was oversubscribed before the price was even set. The AI gold rush has a new public scoreboard. And if you’re wondering where all that corporate AI spending is going, a good chunk of it just went here.
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// CONNECT THE DOTS
GM is laying off IT workers. Meta is spending $145 billion on AI infrastructure. Cerebras just went public at $66 billion. The money is moving in one direction. Follow it.
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ARXIV WILL BAN RESEARCHERS FOR A YEAR IF AI WROTE THEIR PAPER
ArXiv, the preprint repository where most AI and computer science research lands first, just announced it will ban authors for up to a year if they submit papers primarily generated by large language models. The site has already been flooded with low-quality, AI-generated submissions. Some papers included obvious tells: fake citations, hallucinated data, and prose that reads like a ChatGPT fever dream. ArXiv’s new policy requires authors to certify that human intellectual effort drove the work. The irony is thick: the field building AI is now building walls to keep AI’s output out.
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// STEP BACK
ArXiv isn’t anti-AI. It’s anti-autopilot. The same standard applies in any knowledge job: using AI as a tool is an advantage. Letting AI do your thinking is a liability. The people who treat AI as a collaborator (not a ghostwriter) will stand out in both academic and corporate settings.
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// THE TOOLBOX
TLDV
tl;dv is Otter.ai’s cooler, more generous cousin. It joins your Google Meet or Zoom calls, records, transcribes, and produces AI summaries with timestamps and action items. The free tier gives you unlimited recordings and transcriptions (no 300-minute cap). It also integrates with Notion, HubSpot, and Slack, so your meeting notes land where you actually work.
The caveat: The AI summaries can miss nuance in fast-paced conversations. Treat them as a first draft, not a transcript of record.
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// WAIT... DOES THIS ACTUALLY WORK?
THE OBSCURE PROMPT OF THE DAY
prompts nobody asked for. results nobody expected. try it anyway.
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"You are a corporate buzzword translator. I’m going to paste an email from leadership and you will rewrite it in plain English, then add a section called ‘What They Actually Mean’ that decodes every piece of corporate speak into honest, blunt language. Be funny but accurate."
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// OUR VERDICT
Fed it an actual all-hands recap email. The "What They Actually Mean" section decoded "rightsizing our operational footprint" as "layoffs" and "leaning into synergies" as "two teams are merging and one manager is losing their job." Genuinely useful for anyone who reads company emails and thinks, "what did that even say?"
SURPRISINGLY PRACTICAL: ★★★★★
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// YOUR EDGE
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01
Learn this: Prompt engineering fundamentals. GM is hiring for it. ArXiv is policing against it being used lazily. The skill is learning how to direct AI precisely, not just ask it questions. Start with OpenAI’s prompt engineering guide (free).
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02
Watch this: Cerebras IPO coverage, specifically analyst takes on whether the AI chip market has room for a second player behind Nvidia. The answer shapes which companies survive the next 18 months.
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03
Say this: "GM isn’t cutting IT jobs because of budget. They’re replacing the skill set. The question isn’t whether AI changes what companies hire for. It’s how fast."
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