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Hey fam 👋 Luis & Rui here with your Thursday AI coffee break.
Anthropic just dropped Claude Fable 5.1, the most capable Claude yet, and Google answered the very next day with Gemini 3.8 Flash, which is scary good for what it costs.
Oh, and the White House just picked OpenAI‘s side in the New York Times copyright fight. Not a quiet week.
Grab your coffee!
(3-minute coffee break ☕)
AI News around the world 🌍
🚨 Anthropic launched Claude Fable 5.1, its most capable model for coding and knowledge work, live now on Claude.ai, the API, and all three major clouds. (continue reading)
⚡ Google released Gemini 3.8 Flash and a Flash Cyber variant, bringing near-frontier coding and agentic performance at just $0.75 per million input tokens. (continue reading)
⚖️ The Trump administration filed a court brief backing OpenAI against The New York Times, arguing that training AI on copyrighted text is fair use. (continue reading)
🛡️ OpenAI says its upcoming Astra model is the first to hit its critical cybersecurity threshold, so it ships with tighter safeguards and limited access. (continue reading)
🎨 Google launched Pics, a Nano Banana powered image creation and editing tool inside Docs and Slides for AI Pro, Ultra, and Workspace users. (continue reading)
Trending AI Tools 🛠
💬 Jason AI SDR: Finds, engages, and follows up with your ideal prospects, automatically booking qualified demos for your sales team. 👉 Book your demo today
📧 Talki: An AI helpdesk for B2B teams that auto-resolves routine support tickets across web chat, email, and Telegram, with a free plan and paid seats from €9 a month.
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🎯 Mimelio: Rewrites your landing page headlines, copy, and CTAs in real time to match each visitor’s Google Ads search.
Tutorials 📝
Career & Capital 💼
AI Job Board
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🏥 UnitedHealth Group: Sr. AI/ML Engineer (Remote) – $120,100 to $214,500 (view job)
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🔍 Handshake: AI Safety Policy Evaluator (Remote) – $45 to $55/hr (view job)
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📊 Intrinsic: Data Scientist (Tampa, FL) – $115,000 to $160,000 (view job)
Investments in AI
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🏢 Wonderful: Raised a $550M Series C at a $5B valuation for its enterprise AI operating system that runs agents and workflows across company data. (link)
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🤗 Hugging Face: Nvidia has reportedly agreed to acquire the open-source AI model hub for about $13B. (link)
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🍽️ Owner: Raised a $240M Series D at a $2.3B valuation to build AI that runs marketing and tech for restaurants and local businesses. (link)
Prompt of the Week 🧠
AI Output QA Gate → Catch the mistakes in AI-generated work before your client does.
Claude Fable 5.1 just launched, and AI agents now run multi-step tasks on their own and hand back something that looks finished. The bottleneck has moved from doing the work to checking it, and this prompt is the review step between “the agent is done” and “I hit send” (it works just as well on a freelancer’s draft).
Prompt:
You are a strict but fair QA reviewer. Check a piece of work produced by an AI agent (or a contractor) against the brief it was given, before it goes to a client, a customer, or my boss. Assume nothing is correct until verified against the brief or the source material. Original brief: [PASTE THE TASK OR INSTRUCTIONS EXACTLY AS THEY WERE GIVEN] Deliverable to review: [PASTE THE OUTPUT - report, email, analysis, deck outline, etc.] Source material: [PASTE THE DATA, DOCS, OR NOTES THE WORK WAS SUPPOSED TO BE BASED ON, OR WRITE "NONE"] Who receives this: [CLIENT / CUSTOMER / EXEC / INTERNAL TEAM] Run these five checks in order: 1. COVERAGE - List every explicit requirement in the brief. Mark each one DONE, PARTIAL, or MISSING with a one-line reason. 2. ACCURACY - Flag every number, date, name, quote, or claim that does not appear in the source material. Quote the exact sentence. With no source material, flag any claim that sounds specific but is unsupported. 3. SCOPE DRIFT - Point out anything the deliverable does that the brief did not ask for, and anything it quietly reinterpreted or narrowed. 4. RECEIVER TEST - Read it as the named receiver would. Name the first thing they would question, push back on, or be confused by. 5. INTERNAL CONSISTENCY - Find contradictions inside the deliverable itself: numbers that do not add up, a conclusion the body does not support. Then give your verdict in exactly this format: VERDICT: SHIP / FIX THEN SHIP / REDO CONFIDENCE: High / Medium / Low, plus the single biggest reason MUST FIX BEFORE SENDING: numbered list, most severe first, with the exact location and the specific correction NICE TO HAVE: max 3 items ONE LINE FOR ME: what I should tell the person (or agent) who did the work Rules: - Do not rewrite the deliverable. Point to problems, do not fix them. - Do not praise. If something is fine, say nothing about it. - If you cannot verify a claim, say UNVERIFIED, never "correct". - If the brief was unclear, say so in one line at the end, but still grade against what was written.
Where to use it: Founders and operators delegating research, reports, or client deliverables to AI agents or freelancers, agency owners reviewing junior work before it reaches a client.
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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.
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