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🚀 Be featured in our next issue. 👉 work with us here
Hey fam 👋 Luis & Rui here with your Monday AI coffee break.
Anthropic is lining up what could be the biggest IPO ever recorded, OpenAI quietly slashed API prices by more than 20%, and NVIDIA built an agent that just aced the hardest benchmark in the field.
Grab your coffee!
(3-minute coffee break ☕)
AI News around the world 🌍
📈 Anthropic is preparing to file publicly for an IPO that could match or beat SpaceX’s record $86 billion raise. (continue reading)
💸 OpenAI cut GPT-5.6 Sol API pricing by over 20% for three months, dropping input tokens to $4 per million. (continue reading)
🧠 NVIDIA’s new AVO agent architecture scored a perfect 100% on ARC-AGI-3, clearing all 183 levels across 25 environments. (continue reading)
🤖 Anthropic made Computer Use, the Skills API, and the Files API generally available, plus a new browser tool for agents. (continue reading)
📰 Google launched a Preferred Sources button publishers can embed, letting readers favorite a site and see it far more often. (continue reading)
Trending AI Tools 🛠
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Tutorials 📝
Career & Capital 💼
AI Job Board
🍎 Apple: Senior AI Software Engineer, App Intelligence – $184,700 to $324,800 (view job)
🧠 Ethos AI: Remote AI Trainer – $70 to $100 an hour (view job)
📈 Practice Flow: Performance Marketing Manager, Healthcare AI (Remote) – $65,000 to $90,000 (view job)
Investments in AI
⚡ Etched, the AI inference chip startup, raised $700 million at a $21 billion valuation led by Jane Street, with Kleiner Perkins, Sequoia, a16z, and Tiger Global joining. (link)
🎬 Higgsfield raised a $400 million Series B at a $5.4 billion valuation led by DST Global, with Goldman Sachs Alternatives, Intel Capital and Tribe Capital. (link)
🎙 Wispr raised a $280 million Series B at a $2 billion valuation led by Menlo Ventures, with NEA, 8VC, Forerunner, and Goodwater joining. (link)
🚀 Claude Code for Beginners. Free Masterclass.
We created a full masterclass on Claude Code for beginners. No slides. No theory. Just us opening Claude Code live and showing you exactly how to use it from scratch.
No coding background needed. Over 2,000 people have already signed up.
If you’ve been curious about Claude Code but didn’t know where to start, this is it.
Prompt of the Week 🧠
Bad-Fit Customer Filter → Find out which customers are quietly costing you money, then stop selling to more of them.
Prompt:
You are a profitability analyst and revenue operations advisor. Your job is to identify my least profitable customer types and turn that into a screening filter I can use before I sell to anyone else. Here is my business: - What we sell and our typical price point: [DESCRIBE] - How we deliver it (self-serve, done-for-you, hybrid): [DESCRIBE] - Roughly what an hour of my team's time costs us: [AMOUNT] Here are my last 10 to 20 customers. For each one I will give you what I have, even if some numbers are estimates: [NAME OR LABEL | industry or segment | how they found us | total revenue | rough hours of delivery and support | did they renew, refer, churn or complain | anything notable] [PASTE DATA] Do this: 1. Estimate a rough profit contribution per customer using revenue minus estimated delivery cost. Flag where my inputs look unreliable rather than guessing silently. 2. Rank all customers from most to least profitable and show the split. Tell me what share of my profit comes from the top tier. 3. Identify the two or three patterns that the bottom tier shares: acquisition channel, industry, company size, buying trigger, expectations at the point of sale, or how they were sold to. 4. Write a bad-fit profile in plain language, phrased so a salesperson or a form could apply it. 5. Give me five qualification questions to ask before accepting a new client, with the answer that should make me walk away. 6. Suggest one change to my pricing, packaging or onboarding that would make the bad-fit segment either profitable or self-selecting out. Ask me up to three clarifying questions before you start if the data is too thin to be useful.
Where to use it: Best used before a quarterly planning session, before increasing ad spend, or any time revenue is growing but the team feels underwater.
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🙌 That’s a wrap for today’s AI Break
Thanks for hanging out → don’t forget to hit subscribe, drop your thoughts below, and share this update with your fellow AI enthusiasts.
Luis & Rui
PS: Catch us on X @sousa_brothers for daily updates on the latest AI developments.
PPS: If you enjoyed today’s AI Break, sharing is caring (and our algorithms are 😉 programmed for gratitude)
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