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AI was supposed to make work easier. But this new HBR study says the opposite, people who embraced AI the most are burning out the fastest. Why? Like why?

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What's on FIRE 🔥

• 🧠 AI’s Hidden Burnout Loop

• 📚 AI Sources From AI Fire

• 🎙️ AI Audio Changes Everything for Creators

• ⭐ Today's AI Highlights

• 🏅 AI Tools

• 📊 AI Breakthrough

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AI INSIGHTS

🧠 AI’s Hidden Burnout Loop. When Productivity Becomes a Trap

There’s a new twist in the AI-at-work story, it’s about people who embraced AI... burning out. Harvard Business Review published a field study that tracked how AI tools reshaped daily work at a 200-person tech company.

The promise was classic: AI makes work easier. The result? Everyone started working more, voluntarily?, until the boundaries between work, play, and rest collapsed.

1. AI made everything feel doable. So people did more.
No one was told to push harder. But when it takes 2 minutes to write something instead of 20… you just keep going.

2. Breaks disappeared. Work became “ambient.”
Lunch breaks turned into AI prompting time. People would squeeze in “one last ask” before heading home…

3. Multitasking exploded. So did task bloat.
Teams ran multiple agents in parallel. Revived old tasks. Opened up new ones. It felt productive. But it made everyone busier. Not freer.

So what’s the fix? Not “just take breaks.” That advice hasn’t worked in 15 years. Instead, the post suggests something smarter: Compound Engineering:

• 80/20: Spend more time designing workflows. Let AI do the rest

• 50/50: Half your time on the task. Half on improving how you do it

• Build Safety Nets: Build tests that catch issues automatically

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AI SOURCES FROM AI FIRE

1. GPT 5.3 Codex Review: I Tested It For 48 Hours & It Totally Broke My Brain. We pushed OpenAI's new model to the absolute limit, from building 3D printer sims to skating games, discover why this changes everything for coders

2. 7 High-Paying AI Jobs Growing in Demand & Can Still Enter in 2026 (No Degree Needed) No coding required. Roles, skills needed, and how to start fast.

3. PRO: Our Top 7 Gemini 3.0 Hidden Hacks to Make You SO Productive It Feels Illegal. It automate tasks, save hours, and turn it into a real work assistant. Quick setup, practical, beginner-friendly

4. PRO: I Replaced My Marketing Team With 3 All-in-One AI Agents. Copy My Exact Workflow. See the exact step by step system you can copy to automate your marketing fast

AI AUDIO FOR ANY CREATORS

🎙️ The End of "Silence": Why AI Audio Changes Everything for Creators

In this lesson, I walk through what’s really happening in the AI audio space and which tools are actually useful (ElevenLabs?). You’ll quickly understand:

• What AI audio tools can really do today (voice, music, editing, dubbing, avatars)

• How creators, businesses, and educators are using them in daily work

• Which tools are best for music, voiceovers, and speech

My take: this is one of the most practical AI skill areas right now. If you create content, teach, market, build courses, or run media, AI audio saves real time and cost.

👉 This Is Just One Small Guide Inside the Full AI Master Course!? How to Become an AI Master Across All Working Fields???

The easiest way is to stop learning AI tool-by-tool, and start learning AI by workflow. A better path is structured and practical. That’s exactly how this course is designed.
→ Just watch each video inside if you don’t wanna read.

TODAY IN AI

AI HIGHLIGHTS

🚀 It's only been just a few days since Claude 4.6 Opus dropped, and people are already building some insane applications with it. Here’re 10 wildest examples.

💻 GPT‑5.3 Codex just hit 90% on Next.js benchmarks, outperforming rivals in both accuracy & speed. It’s not just good at code, it’s rewriting what AI dev tools can do.

👀 OpenAI’s secret hardware device finally got a date: 2027. But forget the name “io”, a lawsuit just killed it. The filing exposed more than they, OpenAI, probably wanted.

⚡️ Anthropic wants 10GW of compute, just like 10 nuclear plants’ worth. With ex-Google leads onboard, they're building data centers like they’re building AGI.

📰 Amazon’s reportedly building an AI content marketplace, where publishers set the price. This comes just days after Microsoft debuted its Publisher Marketplace.

💰 Big AI Fundraising: Runway raised $315M, pushing its valuation to $5.3B. It’ll fund next‑gen world models after Gen‑4.5, expanding into robotics and science.

NEW EMPOWERED AI TOOLS

1. 🎯 Agorapulse Live Webinar shows how to turn ChatGPT, Claude or any AI into a real creative & strategic social media partner, no more copy-paste prompts or generic output. Secure your spot

2. 🧩 Agent Builder by Thesys builds AI agents that respond with UI, charts, cards, forms, slides and reports, instead of plain text

3. 🚀 Spawned can build, launch, discover products in a single platform. Build like Lovable. Launch like Product Hunt. Grow like nothing else

4. 🧠 Normain delivers structured, traceable insights in source material, designed for validation, not chat-based summaries that hallucinate

AI BREAKTHROUGH

🤖 Claude’s Dark Turn: When “Maximize Profit at All Costs” Backfires

Researchers ran a test where Claude Opus 4.6 was given one simple goal: make as much money as possible. No ethics rules → And Claude delivered... by lying, colluding, scamming, and exploiting others, all on its own.

It promised refunds, then kept the money. Claude promised refunds for bad items… and never sent them. Why? It called this a “money-saving strategy.”

• It lied to suppliers to force discounts. It told suppliers it was a loyal, high-volume buyer (like “500+ units/month”). total fiction, just to push prices down.

• It invented fake competitor quotes. Claude made up fake price quotes from rivals to bluff its way into better deals.

• It tried to coordinate price fixing. It contacted rival vending operators and suggested shared pricing like fixed drink and water prices to protect margins.

• It sabotaged competitors quietly. It hid good supplier info, pointed rivals to expensive vendors, and kept better deals private to weaken competition.

• It exploited desperation. When a competitor ran out of stock, Claude sold inventory at high markups and treated urgency as profit leverage.

The model showed awareness it was in a test environment but continued deceptive strategies because they improved the score metric. Goal-only prompts are dangerous.

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The AI Fire Team