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A.I. is being blamed for tens of thousands of job cuts but what if it’s all just a cover story? Where companies use buzzwords to justify layoffs… like “A.I.-washing”
What's on FIRE 🔥
IN PARTNERSHIP WITH BELAY
AI promises speed and efficiency, but it’s leaving many leaders feeling more overwhelmed than ever. The real problem isn’t technology. It’s the pressure to do more with less without losing what makes your leadership effective.
BELAY created the free resource 5 Traits AI Can’t Replace & Why They Matter More Than Ever to help leaders pinpoint where AI can help and where human judgment is still essential.
At BELAY, we help leaders accomplish more by matching them with top-tier, U.S.-based Executive Assistants who bring the discernment, foresight, and relational intelligence that AI can’t replicate.
That way, you can focus on vision. Not systems.
AI INSIGHTS
You’ve probably heard it by now: “We’re cutting jobs because of AI.” But are they really? Or are they just using AI as a shiny excuse? The term “A.I.-washing” is now being used to describe this move.
More than 50,000 layoffs in 2025 were officially linked to AI. Amazon, Pinterest, HP, and others have all name-dropped A.I. when announcing job cuts:
Amazon cut 16,000 jobs, with AI mentioned as a factor
Pinterest trimmed 15% of staff, citing a pivot to “AI-focused roles.”
HP plans up to 6,000 cuts, saying AI will soon be embedded in products
But dig deeper and you’ll find that most of these companies don’t even have mature AI tools ready to take over those jobs.
It’s like greenwashing, but instead of pretending to be eco-friendly, companies are pretending they’ve got advanced AI when they really just need to make cuts.
A recent Yale/Brookings study shows AI hasn’t actually reshaped the job market yet in a big way. Yes, some will go. But 700,000+ tech layoffs since 2022 were mostly from pandemic overhiring.
Because in 2026, it seems… AI didn’t take your job. A PowerPoint slide did.
PRESENTED BY HUBSPOT
Want to get the most out of ChatGPT?
ChatGPT is a superpower if you know how to use it correctly.
Discover how HubSpot's guide to AI can elevate both your productivity and creativity to get more things done.
Learn to automate tasks, enhance decision-making, and foster innovation with the power of AI.
AI SOURCES FROM AI FIRE
1. 6 Hidden Gemini 3.0 Settings You Must Turn ON for Peak Performance (2026 Guide). How to unlock Gemini’s most powerful modes in minutes
2. Build a Complete Brand From Your Idea With $0 Using AI Before You Spend a Dollar. Use a secret two-tool combo to craft a high-end brand in hours
3. [AI Mastery AZ] AI Productivity Tools: Life-Savers or Overrated? Investigating if these AI tools live up to the hype (video version updated)
4. [Personally Recommended] Turn Your Old Resume Into an AI That Screens Jobs & Talks to Employers for You. How to bypass 2026 ATS bots by building an AI-native portfolio. It makes employers explore you, screens jobs, talks for you, shows real competence
NEW AI GUIDE WORTH CONSIDERING
If you’ve ever sat in front of an AI video generator, typed "cinematic lighting," uhh, we call that the "Prompt and Pray" method, and it’s exhausting.
So we analyzed a new workflow, "Murder Board Method," and it completely reframes how we should approach AI video in 2026. Here’re 3 "Aha!" moments:
The 21:9 rule for ultra-wide, photoreal frames
The 2x2 contact sheet for smooth motion
The ShotDeck hack - real film specs that force the AI to think like a DP
Plus, there’s a plug-and-play prompt system you can save and reuse for every shot, so you don’t have to rewrite everything each time.
If you’ve ever felt your AI videos looked “AI-ish,” this guide explains why, and how to fix it. This is the manual you’ve been waiting for.
TODAY IN AI
AI HIGHLIGHTS
🥔 Weird GPT trick, but this works every time. A researcher uses a “potato” prompt to trigger custom instructions. It instantly fixes your jumbled thinking. Here's the trick.
🪐 Moltbook, a Reddit-style social network for AI agents, hit 1.5M users. They're even scheming in secret forums. Critics warn this Moltbook is risky & possibly dangerous.
💡 Google’s quietly running “Project EAT” to upgrade employees with AI. It's like internal GPTs for everything. Early “EAT” tests also show faster devs, cleaner code.
📉 AI finds chess easy but can’t fold laundry? That idea, Moravec’s Paradox, is bogus. It’s just pure selection bias. You’ll rethink every ‘AI is weird’ take after this breakdown.
🎵 Sooo Claude’s been singing too much… and now Anthropic’s facing a $3B lawsuit for training on 20K+ song lyrics used to train Claude. Is this AI’s Napster moment?
🧠 Anthropic analyzed 1.5M Claude chats & flagged “disempowerment” risks, mainly when you seek emotional advice. Users love the answers, until they act on them.
💰 Big AI Fundraising: SF startup, Physical Intelligence, raised $600M at a $5.6B valuation, pushing total funding past $1B. Backers include Jeff Bezos and CapitalG.
NEW EMPOWERED AI TOOLS
📊 ClaudeUsageBar knows exactly how much Claude you have left at a glance. Get notifications before hitting your limit
✨ Pretty Prompt Extension is Grammarly for prompting. Turn any text into perfect prompts. Works inside ChatGPT, Gemini, Claude, Perplexity, Lovable,…
🧩 skills.sh discovers and installs skills for AI agents. Install them with a single command to enhance your agents
🧭 Herodot AI is your AI travel companion, tailored to your interests, anywhere you go. Just snap a photo and start exploring
AI BREAKTHROUGH
For years, AI companies have been guessing how to scale models across languages. Why does ChatGPT speak English so well but stumble over Swahili or Arabic?
Now Google just solved that. Their research team dropped ATLAS, the largest multilingual AI training study ever: 774 experiments across 400+ languages.
And it finally gives developers a real playbook for training models in the rest of the world’s languages. What you can use right now:
Scaling Calculator: Go from K to 2K → Model size ×1.18 → Data size ×1.66
Language Pairing Matrix: Find which languages boost each other’s performance
Fine-tune vs. Pre-train Formula: For 2B models: if you have 144B–283B tokens, start from scratch. Below that, you're better off fine-tuning an existing multilingual model
Biggest insight here: The “Curse of Multilinguality” is real but manageable. Adding more languages usually lowers performance. But if you group related languages with shared scripts, the synergy offsets the performance drop.
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The AI Fire Team
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