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Hi AI Futurists,
If you've been anywhere near AI X this week, you've probably seen the viral article making the rounds about the impact of AI on society. Essentially, the gap between what the public thinks AI can do and what it actually does right now is the widest it's ever been. What does this mean for you?
Let’s take a look.
Our agenda.
Top AI news
The true impact of AI
Top 3 selected AI tools
AI in the wild
AI Investment Report
Best,
Lex Sokolin
P.S. We just released our premium AI encyclopedia report. Be sure to check it out.
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Ecosystem: AI Venture Fund | Fintech Research | Lex Linkedin / Twitter
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Top AI news
10:28 AM
🍺 Heineken Slashes 6,000 Jobs, Credits AI Beer sales are down, productivity expectations are up, and 7% of the workforce is out. The stock rallied. Cheers?
💑 Man Lets AI Replace Him as Husband. Wife Approves Immediately. After 46 years of marriage, one essayist handed the reins to ChatGPT and says it's producing "quantifiable tranquility." We have questions, but also respect.
💼 AI Makes Workers More Productive, Then Burns Them Out Eight-month study finds AI boosted output but employees quietly worked more hours, took on more tasks, and never clocked off. Researchers are calling for corporate "AI guardrails" before the gains eat themselves.
🎓 Incoming Freshman Still Betting on a CS Degree Despite AI Fears 70% of CS seniors are pessimistic about their careers. One student is making the contrarian bet that understanding systems still matters, even when AI writes the code.
🏫 UT Dallas Gets $4M to Build AI Literacy Starting in High School Part of a $51M federal push. The play: train students AND teachers on AI from 10th grade through college. If it scales, the model goes national.
🌐 Your Website Was Built for Google. It Needs to Be Built for AI Now. AI assistants are becoming the new front door for customers, and most brands are still optimizing for 2015. Experts say this shift is as big as the move from AOL to search.
🏥 Jack Ma's Ant Group Bets Its Future on AI Healthcare Ant elevated its health unit to the same level as Alipay and is training AI "Doctor Agents" to reach 1.4 billion people. From fintech to health tech, this is one of the biggest pivots in Chinese AI.
🧠 Seattle Nonprofit Writes the Rulebook for AI Therapy Tools PATH is helping South African regulators build a safety framework for AI mental health apps. The goal: make it an international model before the chatbot therapy boom outruns oversight entirely.
⚕️ AI in Healthcare Jumps From 3% to 22% Adoption in Two Years $1.4 billion is now flowing into healthcare AI, mostly targeting documentation and billing. Where there's thin margins and staff shortages, AI is moving fast.
🔬 Healthcare Has 1,000+ FDA-Cleared AI Tools. Most Aren't Using Them. The gap between what's available and what's actually deployed is staggering. The winners will be orgs that stop experimenting and start embedding.
The real impact of AI
A viral article tore through AI X this week highlighting that the gap between what the public thinks AI can do and what it actually does right now has never been wider.
The piece, written by someone deep in the AI space, lays out a blunt case that most people are still judging AI based on their experience with free ChatGPT in 2023, while the actual frontier has quietly leapt years ahead. It touches on everything from the pace of capability gains to why knowledge workers specifically are exposed, and it resonated because it skips the sci-fi debate and focuses on what's already happening. Let's break it down.
Matt Shumer put it best when he described the moment his "technical work" stopped being work. He now describes what he wants built, walks away, and comes back to a fully designed, coded, and tested product. Not a rough draft. Not a starting point. A finished thing. That's not a future prediction, that's his Tuesday.
And the pace is what makes this genuinely disorienting. Dario Amodei keeps saying capability is doubling on the order of months, and if you've used the latest paid models (GPT-5.3 Codex, Claude Opus 4.6) you feel it. These aren't incremental upgrades from the ChatGPT you messed around with in 2023. They feel like they skipped several generations overnight. METR's evaluations are showing AIs completing multi-hour expert tasks end-to-end, and when OpenAI casually drops that GPT-5.3 helped build itself, that's not a flex. It's a signal that AI has crossed from "tool" to "accelerating system."
The viral piece resonated because it skipped the AGI debate entirely and went straight to the uncomfortable practical point: most knowledge work happens on screens, and anything that happens on screens is now on the table. This isn't about robots taking your job in 2035. It's about what happens when your industry still treats AI as an optional experiment while the top performers in your field are quietly turning three days of work into one hour.
The career takeaway is blunt: adaptation speed is the new competitive moat. The people learning to orchestrate AI right now aren't just more productive. They're building compounding advantages that will be really hard to catch up to once everyone else finally notices.
Takeaways at a Glance:
The public is roughly two years behind where AI actually is
Paid models have leapt dramatically ahead, making 2023-era judgments outdated
Coders got hit first because labs optimized AI to build more AI
AI is now handling multi-hour expert tasks autonomously, improving faster than any tech curve in history
Knowledge work is broadly exposed because it's digital, legible, and easy for models to replicate
The new edge: learn fast, adopt early, hand off more than feels comfortable
What We Think About It:
The biggest miss in the public conversation is timeline. People are mentally modeling years of gradual change. Insiders are watching month-scale jumps that rewrite what's possible before most people even update their assumptions.
Most workers underestimate how quickly AI becomes "good enough" for tasks they consider specialized. You don't need perfect to be disruptive. You need fast, cheap, and 80% as good, and we're already past that bar for a lot of knowledge work.
The early adopters aren't just ahead. They're compounding that lead every single day. The gap between "using AI" and "not using AI" is starting to look less like a productivity edge and more like a career-defining fork in the road.
What You Can Do Right Now:
Pay for the best models. Free-tier AI is a completely different experience from Claude Pro, ChatGPT Plus, or API access. The gap is massive and widening. If you're judging AI by the free version, you're not seeing what it actually does.
Pick one real workflow and automate it this week. Don't "explore AI." Give it an actual task you do repeatedly: drafting, research, data cleanup, first-pass analysis. Measure the time difference.
Learn to prompt like you manage. The skill isn't typing questions. It's giving clear context, constraints, and examples, the same way you'd brief a smart new hire. Get good at this and everything else compounds.
Follow the builders, not the commentators. People like Matt Shumer, Ethan Mollick, and others working hands-on with these tools will tell you what's real months before the mainstream picks it up.
Get comfortable handing off more than feels safe. The instinct to double-check everything will slow you down. Start trusting AI with low-stakes tasks, then gradually raise the ceiling as you calibrate its strengths and limits.
Talk to your team about it openly. The biggest organizational risk isn't AI itself. It's half your team quietly using it while the other half pretends it doesn't exist. Get it out in the open.
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AI In the Wild
AI Investment Report
This 158-page research report provides the first comprehensive taxonomy of public companies, private ventures, and tokenized protocols building the infrastructure for autonomous AI systems. Compiled by Lex Sokolin, former Chief Economist at ConsenSys, fintech strategist at Autonomous Research, and current Managing Partner at Generative Ventures, this report delivers institutional-grade analysis of 100+ companies across 14 critical infrastructure layers. Learn more here.
AI & Robotics Industry Encyclopedia
In this 158 page report, we collate all the meaningful companies across public equities, private equity, and digital assets related to the machine economy. There are 13 sections of company types, a...
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