🔥Two New Models, Three New Agents. What to Actually Use???Plus: The AI Autocrat and how Automating Power Creates a New Point of Failure
Greetings Everyone, I just got back from a mastermind in Tampa, where I had the privilege of spending time with a small group of sharp, resourceful entrepreneurs and business owners. We talked tech, the world, and family, and traded the tools and systems that are working in our daily lives and businesses. I follow tech and AI closely, but in that room I was easily one of the novices. I shared a few tools I use, but mostly I listened and absorbed what these minds are building. Here’s what stuck with me: 1. AI multiplies you, so pay attention to which you. Look closely at what you delegate and how you use it. Make sure the tech multiplies your strengths and assets, not your bad habits. 2. Build a system that’s fluid and expandable, then stick with it. New tools and shinier ways to run agents will launch every day. Jumping between them is taxing on your time and your brain, and it shows up in your bottom line. Pick a foundation you can grow, and make it work for you. 3. Get familiar with local models now. If something breaks, whether that’s an outage, a policy change, or a price hike, you’ll still have a model running at home or in your office. If you serve clients, you can keep serving them. I also expect cloud AI to get more expensive over time, and if the bubble pops, that dependency could slowly choke your business. That’s my opinion, not a certainty, but it’s worth having a backup plan. I brought back a lot of tools and tricks, and I’ll share them with you gradually. If you want to talk through any of it for your own business, get in touch. I look forward to hearing from you. In today’s issue:
📰 AI News and Trends
Two New Models, Three New Agents -What to Actually UseOpenAI’s GPT-6.1 Sol launched September 29 at $2 per million input tokens, $0.10 cached input, and $10 output. Anthropic’s Claude Sonnet 5.5 shipped a day earlier at the same $2/$10 list price. Its cache reads cost $0.20, double Sol’s, though Anthropic says it uses fewer tokens per task and costs up to 30% less than Sonnet 5. The headline claims favor different strengths. OpenAI says Sol beats Claude Opus 5.5 by 2.2 points on AutomationBench at about a third of the cost, which is a vendor-reported result against Opus, not Sonnet. Anthropic reports Sonnet 5.5 at 70.6% on Terminal-Bench 4.0, up from 10.3% for Sonnet 5. On one independent index at max effort, Sonnet 5.5 scored 56 while Sol scored 51.8. I would use Sol for high-volume automations with a long, fixed system prompt, since it is cheaper. Sonnet for coding and terminal-style agents. But effort settings can swing your bill more than the model choice does, so run your own 20 real tasks on both at medium effort and track cost per successful task. Agents: Dots vs. Grok Bot vs. Muse.The new race is chatbots becoming coworkers with their own computers. Dots is OpenAI’s always-on agent, announced at DevDay on September 29. It runs on GPT-6 Astra from $100/mo and promises background research with read-only defaults, plus a home in ChatGPT, Slack, and Teams. Grok Bot is the only one of the three that lets you run several named agents today, and starts at $20/mo for individual accounts. The tradeoff is that it signs in to your apps as you, with your full permissions. Muse is Meta’s free option, best for errands and shopping, and you can text it on WhatsApp. The bigger story is governance. These agents reach employees through personal subscriptions instead of a security review, so before pointing one at client accounts, scope its credentials and keep a human on the exceptions. 🧰 AI Tools of The DayThe Agents Moved Into Your StackOpenAI DevDay, Meta’s small-business push, and a Sonnet refresh all landed within 72 hours. This week’s theme is agents that plug into tools you already pay for. Here are five you can put to work today. 1. Meta Muse for Small Business - Meta’s agent, launched Sep 29 and hit #1 on both US app stores, with 2.5M downloads in 13 days, now connects to HighLevel, Klaviyo, Shopify, Stripe, QuickBooks, and Canva, as well as your Instagram, Facebook Pages, and Meta ad accounts. For an SMB, that’s an ops assistant that already knows your ad data, and it’s free to start. You can use it by connecting Klaviyo (or other accounts) and your Meta ad account, then ask: “Which flows drove revenue in the last 30 days, and where did ad spend leak?” Muse won’t publish, send, or spend without your approval (as of now). 2. Clueso MCP - Create and edit product videos from inside Claude, ChatGPT, Gemini, or Cursor. It turns a raw screen recording into a polished demo with voiceover, captions, and zooms, all through chat. It was the #1 product in the Product Hunt AI digest on Sep 24 (531 votes) and reached 586 for the week. MCP access is included on the free plan. 3. Databox MCP Connectors - Pulls context from HubSpot, Slack, Notion, Semrush, Klaviyo, and Ahrefs. When you ask “why did leads drop?”, the answer includes the CRM notes, not just a chart. Agencies can connect HubSpot and Semrush, then draft each client’s monthly performance narrative with one prompt. The connectors need a Team plan. The AI Autocrat and how Automating Power Creates a New Point of FailureIn a Foreign Affairs piece published October 1, political scientist Seva Gunitsky and security technologist Bruce Schneier (both University of Toronto) argue that AI gives dictators a tempting fix for an old problem: they need subordinates to run the state, but subordinates can leak, steal, shirk, or plot. AI offers two escapes. It can monitor officials in real time, flagging changes in an official’s spending or schedule without human informants. It can also replace human intermediaries outright, from censors to bureaucrats. China is furthest ahead, with algorithmic oversight of local officials and bots replacing paid online commentators. Russia scans huge volumes of images for banned content, runs facial recognition across Moscow, and has even fielded AI-generated news anchors. The UAE is using AI to draft laws and plans to hand a large share of government operations to AI agents. The authors’ counterpoint is that a self-running state is an illusion. Every AI system depends on a small group of engineers who build and maintain it, and rulers can’t evaluate their work. Those engineers decide what the ruler sees, what gets flagged, and who gets targeted. They are also hard to replace and far fewer in number than the generals or officials they displace. AI may help autocracies in the near term, but the more a regime depends on it, the more it depends on the people running it. Additionally, delegating the use of atomic weapons or any weapon that can damage innocent humans as well as autonomous weapons that can go rogue is not something to take lightly. Automating an inbox, mat not kill someone, but automating a bomb is completely different. Automating your operations doesn’t remove the need to trust people. It concentrates that trust in whoever builds and maintains the system, so know who they are and keep documentation and access under your control. 🐈⬛ GitHub repos of the weekToday’s GitHub Trending reads like an agent parts list.
The agent stack is going modular. Voice, memory, and security are becoming open, swappable layers. Builders who wire them together win the next 12 months. 🚀 Showcase Your Innovation in the Premier Tech and AI Newsletter (link) As a vanguard in the realm of technology and artificial intelligence, we pride ourselves in delivering cutting-edge insights, AI tools, and in-depth coverage of emerging technologies to over 55,000+ tech CEOs, managers, programmers, entrepreneurs, and enthusiasts. Our readers represent the brightest minds from industry giants such as Tesla, OpenAI, Samsung, IBM, NVIDIA, and countless others. Explore sponsorship possibilities and elevate your brand's presence in the world of tech and AI. Learn more about partnering with us. You’re a free subscriber to Yaro’s Newsletter. For the full experience, become a paying subscriber. Disclaimer: We do not give financial advice. Everything we share is the result of our research and our opinions. Please do your own research and make conscious decisions.
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🔥Two New Models, Three New Agents. What to Actually Use???
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Thursday, September 24, 2026
🎓 The Third Revolution - Education After AI
🎓 The Third Revolution - Education After AIPlus: China just overtook the U.S. as the top address for elite AI talent
Education is changing fast, and it should be, the world isn’t remotely the same as it was 100 years ago, but the classroom mostly is. Companies and individuals are stepping into that gap with alternatives. Some are genuinely trying to fix it. Others are building “education” that quietly optimizes for their own pipeline, training the next generation of workers for them, or grooming the next founder to grow their portfolio. A new wave of investors is throwing money at schools and campuses for the same reason they fund startups: hoping to get in early on the next great researcher or entrepreneur before anyone else does. Whatever the motive, the shift is real. YouTube was built so anyone could post a video for anyone to watch, and it’s quietly become a university on steroids, where you can learn almost anything for free, on demand, from whoever’s actually good at it. Anyone ready to learn now can learn. The catch: the skill that matters most isn’t absorbing information anymore, it’s learning how to learn, and knowing exactly what’s worth learning in the first place. Information overload and algorithms built to hold your attention make it harder than ever to see past the noise and find what you, or your kids, actually need. But doing that work is worth more now than at any point before. Today we share how and why education is being rebuilt from the ground up, how AI-driven algorithms are quietly built to find and exploit the weakest users instead of protecting them, and how China just overtook the U.S. in the race for top AI talent. Let’s dive in. In today’s issue:
📰 AI News and Trends
Yaro on AI and Tech Trends | Your Top AI Newsletter is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber. The Third Revolution - Education After AIEvery hundred years, we redesign how humans learn, because we redesign what humans need to do. Agriculture taught us land management. Industry built the modern school which left us with desks in rows, bells between periods, a design borrowed straight from the factory floor. That system hasn’t changed much in a century. We’re now at the start of a third redesign and this time it’s questioning whether the classroom itself survives. The proof-of-concept has been live. Youtube is basically a place where you can learn anything and everything, if you really want to learn. Duolingo has brought a new language to millions and is expanding into other subjects. Udemy, Maven, and many other platforms have been helping us learn on the go. Andreessen Horowitz just announced a full college alternative, the Horowitz Andreessen Academy. Fifty students, one year, tuition-free, no tests, just real products built from day one, taught by working entrepreneurs (AI CEOs and researchers among them), backed by $42M from Anthropic, Google, Meta, OpenAI, Nvidia, and Palantir. “The training that worked for the Industrial Revolution isn’t going to map onto the AI revolution” shared Co-founder Ben Horowitz It’s not alone. Alpha School compresses core academics into two AI-tutored hours a day, Geoffrey Hinton has publicly praised the model, with the rest spent on projects and life skills, for about $40K/year. Duolingo used to take years per language course; AI now lets it ship 148 new courses in one year, and it’s expanded into math and music. Add Maven, Udemy, and YouTube-as-university, and “go learn it yourself from whoever’s best” is now the default on-ramp for a whole generation. The real debate is, What school is for? On a recent podcast, Replit’s Amjad Masad and a16z Academy’s Gagan Biyani argued the most valuable trait young people bring is willingness to question assumptions, something grade-and-credential optimization trains out of people. Masad even calls early startup-founding a form of “premature optimization”: kids professionalizing before they’ve built the judgment to know what’s worth building. AI can accelerate skill acquisition. It can’t accelerate character. The earliest, best-resourced versions of this shift go to kids already near the money and the network, which are a16z’s 50 San Francisco slots, $40K private tuition. Everyone else gets the free app version, which helps, but isn’t the same bet. The most exposed are the credential-dependent middle, if hiring shifts toward demonstrated projects over diplomas, the economics of the traditional four-year degree get shaky fast, especially for families who took on debt believing the old deal still held. The main point here is that AI isn’t replacing teachers so much as replacing the credential with proof of work. The question every one of these experiments is really asking is that once learning gets radically faster and cheaper, what’s actually worth teaching, and who learns it first? That second half is the part the funding announcements never lead with. DraftKings built an AI to find its best “investment” — a problem gamblerDraftKings spent since 2023 building a machine-learning model that scores users by play frequency, balance, and loss-to-wager ratio, an internal “elasticity” score predicting who’ll lose the most after a free bet. Per a 40-source NYT investigation, one ex-analyst put it plainly: “the best investment would be a problem gambler.” A parallel model to flag at-risk users for help was fully built, then shelved in 2025, hours before it was set to be presented to the company’s own responsible-gaming chief. DraftKings disputes the framing. DraftKings isn’t the outlier, it’s the industry default. Turns out “score your most exploitable customer” is a well-worn AI playbook, not a gambling-specific sin:
The model isn’t the ethics problem. The business incentive is. Any company sitting on rich behavioral data has both versions sitting right there, which one gets funded is a leadership decision, not a technical one. China just overtook the U.S. as the top address for elite AI talentNew Carnegie China data tracked 25,677 researchers from NeurIPS 2025, the field’s top conference, and found China now hosts 40.6% of elite AI researchers vs. the U.S.’s 34.2%. In 2022, it was the reverse: 46.4% U.S. to 27.1% China. Full flip in three years. In terms of where researchers earned their undergrad degree, China accounts for 57% of the world’s elite AI talent, the U.S. just 13%. China is clearly out-producing everyone. The U.S. is still winning the import game, but the margin is shrinking fast America remains a net importer of AI talent (+2,145 researchers in 2025 vs. China’s -1,729), and the flow is still lopsided: 30 Chinese-origin researchers work in the U.S. for every 1 U.S.-origin researcher in China. But that ratio was 46:1 in 2022 — narrowing hard. China’s AI industry got genuinely competitive, and U.S. visa rules tightened for Chinese STEM grads. Which resulted in China’s talent retention jumping from 57% to 69% in three years (still trails the U.S.’s 89%, for now). Carnegie tracked 100 elite Chinese-origin researchers in the U.S. as of 2019. 87 stayed, but the 10 who left were disproportionately senior: two startup founders, two tech execs, five professors. To prove the point: Yao Shunyu left OpenAI for Tencent and was named chief AI scientist within three months. Yang Zhilin left a CMU PhD track to found Moonshot AI. Princeton separately counted ~50 tenure-track Chinese-origin scholars leaving U.S. universities in just the first half of 2025. South Korea (KAIST now #3 globally) and Singapore (NUS/NTU both cracked the top 20) are quietly climbing. Peking University dethroned Google as the #1 talent-producing institution, but surprisingly Europe and India are both fading. 🚀 Showcase Your Innovation in the Premier Tech and AI Newsletter (link) As a vanguard in the realm of technology and artificial intelligence, we pride ourselves in delivering cutting-edge insights, AI tools, and in-depth coverage of emerging technologies to over 55,000+ tech CEOs, managers, programmers, entrepreneurs, and enthusiasts. Our readers represent the brightest minds from industry giants such as Tesla, OpenAI, Samsung, IBM, NVIDIA, and countless others. Explore sponsorship possibilities and elevate your brand's presence in the world of tech and AI. Learn more about partnering with us. You’re a free subscriber to Yaro’s Newsletter. For the full experience, become a paying subscriber. Disclaimer: We do not give financial advice. Everything we share is the result of our research and our opinions. Please do your own research and make conscious decisions.
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