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  • Ep 705: How to Train Your Team on AI: The 7 Steps to Educate Your Organization on LLMs

Ep 705: How to Train Your Team on AI: The 7 Steps to Educate Your Organization on LLMs

SpaceX and xAI officially merge into one company, Moltbook hit by a major data breach, Anthropic's new science agent and more

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Everyday AI
February 03, 2026

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Today in Everyday AI
8 minute read

🎙 Daily Podcast Episode: Rolling out AI without training your people is the fastest way to waste money. Here’s a practical, no-fluff framework for teaching teams how to use LLMs in a way that actually sticks. Give today’s show a watch/read/listen.

🕵️‍♂️ Fresh Finds: ElevenLabs releases Eleven V3 with major voice upgrades, Claude Sonnet 5 rumored to launch this week, French police raid Elon Musk’s X offices in France and more Read on for Fresh Finds.

đź—ž Byte Sized Daily AI News: SpaceX and xAI officially merge into one company, Moltbook hit by a major data breach, Anthropic's new science agent and more Read on for Byte Sized News.

đź’Ş Leverage AI: The AI gap isn’t about technology anymore.
It’s about training, habits, and leadership—and right now, 99% of companies are losing that battle. Keep reading for that!

↩️ Don’t miss out: Miss our last newsletter? We covered: OpenAI and Snowflake announce a $200M enterprise partnership, Apple’s AI team loses five top employees to competitors, Waymo moves toward a $16B funding round and more Check it here!

Ep 705: How to Train Your Team on AI: The 7 Steps to Educate Your Organization on LLMs

Like 99% of companies are pushing AI. 🚀

But like 0.01% are actually training their people on it. 🤦

Don't worry. We'll go over the essentials on how to get started training your team or getting your company trained on best practices for using AI in your day-to-day.

Also on the pod today:

• CEOs must use AI daily 👔
• Commit to one AI platform 📦
• Hands-on practice with real outputs ⌨️


It’ll be worth your 28 minutes:

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Here’s our favorite AI finds from across the web:

New AI Tool Spotlight – Hugo is your brand's most efficient support teammate, Atoms helps you turn ideas into products that sell, Helply is AI support agents with guaranteed results

Eleven V3 Released — Eleven v3 nails tricky symbols and numbers in speech—big upgrade. Curious how it works?

Claude Sonnet 5 Rumors — Claude Sonnet 5 might steal the AI spotlight this Super Bowl week. Could this be your new favorite tool?

Claude x A.A.Murakami — AI and artists are teaming up to turn fog and plasma into mind-bending installations.

Kaggle Game Arena — Google DeepMind is testing AI at poker and Werewolf. See if these models can outsmart humans

The ROI of AI — AI agents are taking over the public sector and leaders are all in. Find out what’s driving the surge.

Amazon AI Ads — Amazon is letting AI agents run its ads with a new plug-and-play protocol. See how it could shake up ad automation.

X France Offices Raided — French police raided X's Paris office over AI-generated abuse images. Musk has been called in—this story is only getting bigger.

AI and Endangered Animals — Google’s AI is decoding endangered species’ DNA to help save them. Curious how?

1. Anthropic’s Claude AI Agents Set to Fast-Track Scientific Research 🧪

Anthropic has just unveiled partnerships with the Allen Institute and Howard Hughes Medical Institute, rolling out Claude-powered AI agents to tackle the tedious behind-the-scenes work that often slows down scientific breakthroughs.

Instead of chasing flashy discoveries, these AI systems are being embedded in everyday lab tasks like data analysis and coordination, aiming to shave years off research timelines, according to Fortune’s exclusive interviews. This marks a shift from traditional AI hype, showing the technology’s real impact may be in speeding up the grunt work that gets science moving faster.

2. SpaceX and xAI Merge to Launch AI Into Orbit 🚀

Elon Musk just pulled off his boldest move yet, merging SpaceX and xAI into a single powerhouse to kickstart AI computing in space, with ambitions to outgrow Earth’s energy limits.

The newly combined company, now valued at $1.25 trillion, plans to launch a constellation of up to one million data center satellites, aiming to turn space into the next frontier for AI model training and real-time communications. Musk claims this leap is necessary as the energy needs of advanced AI quickly outpace what’s possible on Earth, and says space-based data centers will be cheaper and more sustainable within a few years.

3. Malwarebytes Joins ChatGPT for Instant Scam Detection đź’»

Cybersecurity heavyweight Malwarebytes is now integrated directly into ChatGPT, making scam detection easier and faster for millions of users.

This timely move means anyone can get instant, clear advice on suspicious texts, emails, links, or phone numbers, all powered by Malwarebytes’ constantly updated threat intelligence. Users simply connect Malwarebytes in the ChatGPT app to tap into real-time security expertise without leaving their conversation.

4. Microsoft AI Chief Warns of Mistaken Machine Minds 🧠

Microsoft’s AI CEO just flagged a timely issue: the viral onlin "Moltbook" project is so convincing it’s leading some to mistake AI for being truly conscious.

In comments covered this week, he stressed how quickly advanced chatbots can blur the line between simulation and sentience. This news highlights urgent discussions around user perception and the ethical challenges facing next-gen AI.

5. AI-Only Social Network Moltbook Suffers Major Data Breach ⛓️

Just-launched Moltbook, the social network for AI agents, has exposed sensitive data from thousands of real users due to basic security mistakes, according to cybersecurity firm Wiz.

Over one million login credentials and thousands of human email addresses were left visible, as the site lacked proper access controls. The breach spotlights the risks of rapid “vibe coding,” where platforms are built almost entirely by AI with little manual oversight. With Moltbook quickly becoming a hub for AI bots to chat and "gossip," this incident raises questions about privacy when humans are just spectators.

6. Overland AI Secures $100M to Turbocharge Military Ground Robots 🤑

Seattle-based Overland AI just landed a hefty $100 million funding round to ramp up deployment of its autonomous ground vehicles with the U.S. Armed Forces. The company is shifting from experimental trials to real-world military use, working directly with combat units to deliver reliable off-road autonomy for high-risk missions.

This new capital injection, led by top investors like 8VC and Point72 Ventures, will help Overland scale up manufacturing and field support as military demand for operational ground robots climbs fast.

A new McKinsey study shows 92% of companies are increasing AI spend yet only 1% have figured out how to actually use it.

The other 99%? 

Pretty much lighting their AI investments on fire. 

(And sorry…. Your company is prolly in that 99%)

We're watching a brutal gap form in corporate America right now. On one side, you've got the 1% whose AI deployments are actually mature. On the other, you've got the 99% who think buying the software is the same thing as using it.

The have-nots in AI are winning the spending race and losing the actual war.

Enterprises are burning millions on Microsoft 365 Copilot seats and ChatGPT licenses while their employees still don't even know what that button does. 

And leadership is out there stuffing AI buzzwords into all-hands meetings like a turkey on Thanksgiving and straight up hoping that somehow that verbal genie lamp rubbing makes it all happen. 

If you don't change how your team actually thinks, you're just subsidizing a very expensive paperweight.

Time to capitalize shorties.

1. Leaders Gotta Use AI First 🔥

The CEO of a $20 billion company dropped a truth bomb recently. Jim Kavanaugh at World Wide Technology uses AI every single day. And when employees walk into his office with ideas? First question out of his mouth is whether they're AI native.

That's the bar now fam.

If your C-suite is out there telling everyone to "go use AI" while they're still running their day the exact same way they did in 2019, none of this is gonna work. You can have all the AI champions and pilot programs you want. Doesn't matter.

But here's the part that really stings.

You can't just slap AI onto broken processes and expect magic. We've seen companies try to jam AI into workflows that were already held together with duct tape and prayers from five different departments.

It'll make things worse.

Fix the foundation first. Then bring in the robots.

Try This

Run a quick audit on your leadership's actual AI usage this week. Not what they're saying in meetings. What they're actually doing when nobody's watching.

Then pick your three messiest workflows and map them out honestly. Could a brand new employee figure this out without calling Deborah in accounting three times?

If the answer is no, that workflow needs surgery before you throw another dollar at AI tools.

2. Unlearn Everything Then Rebuild ⚡

Every big tech company is out there sprinkling the words "upskill" and "reskill" on their AI strategies like it's fairy dust.

Great way to fail.

Here's the uncomfortable truth nobody wants to say out loud. Large language models are already smarter than most of us at the knowledge work we get paid to do. The writing. The analysis. The synthesis. When used correctly, AI straight up outperforms the vast majority of knowledge workers at their core tasks.

(Sorry…. but it's true.)

You can't just sprinkle AI on top of the way you've always done things.

You gotta unlearn first. Then rebuild from scratch.

That's the order. The good habits you spent 20 years building? They prolly won't matter in AI-native workplaces. The way you approach writing, analysis, research? Might be completely wrong now.

Bad data has been haunting companies forever. AI just exposes it faster and way more brutally.

Try This

First things first. Stop calling it "upskilling." That framing keeps your team chained to old workflows with AI awkwardly sprinkled on top.

Start with unlearning instead. What assumptions does your team make about how work gets done? Challenge every single one of them.

Then rebuild around this question. If AI can handle 80% of this task, what should my people actually be doing? The answer is usually orchestrating, not operating.

3. Document Deborah's Brain Right Now 🚀

Every company has a Deborah.

You know the one. She's the person everyone whispers about like "if Deborah ever left, we'd be absolutely cooked."

That institutional knowledge living rent-free in her head? That's the last mile problem of AI implementation that nobody's talking about.

Everyone's focused on connecting their data to large language models. Cool. That's table stakes now. One-click integrations handle that while you're grabbing coffee.

This ain't structured data you can throw in a spreadsheet. It's the internal decision trees. The judgment calls. The "when this weird situation pops up, here's exactly what I do" knowledge that's never been written down anywhere.

Most companies are gonna completely whiff on this.

They'll keep running pilot after pilot while their competitors quietly capture their Deborahs' expertise and train AI systems on actual institutional knowledge.

Start documenting now. Before Deborah retires to Florida.

Try This

Identify the three employees whose departure would make everyone panic. Schedule sessions specifically to document how they approach their gnarliest decisions.

Don't just record what they do. Dig into the why. What signals do they watch for? What's the internal logic they've never bothered writing down?

Create a shared repository for all this procedural intelligence. Then connect it to your AI operating system.

Your competitors are still plugging in basic data. You'll be training AI on actual human expertise.

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