- AI Fire
- Posts
- 🚨 Anthropic’s Fable 5 Shutdown
In partnership with
Plus: Add This Tiny Prompt Trick Before Every ChatGPT, Gemini, Claude Prompt to Get Accurate Outputs
Anthropic just pulled Fable 5 and Mythos 5 after a rare U.S. government order. The real story isn’t the jailbreak. It’s who now gets to decide when a frontier AI model is too risky to stay online.
What's on FIRE 🔥
IN PARTNERSHIP WITH HUBSPOT
What happens when you throw out the GTM playbook
That investor was wrong. Gamma is now worth $2B, with 50M users and more than half their growth driven by word of mouth.
They're one of 6 AI-native startups in HubSpot for Startups' free Bold Bets Playbook. Replit grew revenue 50x after half the team pushed back on the strategy. Ramp generated 100M+ views from a single stunt. Clay's co-founder wouldn't hang up a sales call until the prospect DMed him in Slack.
Each one took a GTM risk most founders would never greenlight. Each one paid off.
AI INSIGHTS
Anthropic just got hit with a rare US government order. The company must suspend access to Fable 5 and Mythos 5 for all foreign nationals, including some of its own employees.
The government cited national security concerns, but did not give full details. Anthropic says the issue appears to involve a possible jailbreak method for Fable 5.
To comply, Anthropic is removing access to Fable 5 and Mythos 5 for all customers. Other Anthropic models are not affected.
Here’s the key part:
Anthropic says the jailbreak was narrow, not universal.
It was used to find a few previously known, minor software vulnerabilities.
Anthropic claims other public models, including OpenAI’s GPT-5.5, can do similar work.
No universal jailbreak has been found so far, according to Anthropic.
The bigger issue is the precedent. If one narrow jailbreak is enough to recall a frontier model, then every major AI lab could face slower launches, stricter rules, and heavier government control.
This is no longer just about model safety. It is about AI governance, national security, and who gets to decide when a powerful AI model is too risky to stay online.
PRESENTED BY HUBSPOT
HubSpot AEO
Picture this. A buyer opens ChatGPT and asks for a recommendation in your category. Your competitor's name comes up. Yours doesn't. And that buyer never makes it to your website.
That's happening right now in markets everywhere. And most teams don't know it's happening because it never shows up in their analytics.
HubSpot AEO shows you exactly where your brand stands in AI search, where competitors are getting recommended instead of you, and tells you specifically what to fix. No expertise needed.
Try it free for 28 days. Just $50 a month after.
AI SOURCES FROM AI FIRE
1. [Ultimate Codex Tutorial for Beginners in 2026] Full Course. Learn how to use ChatGPT Codex as a real coding workflow, from setup and permissions to projects, reusable skills, plugins, memory, and multi-tool automation.
2. I Made 50+ AI Videos for Free With This Video AI Generator. Test real Seedance models inside BytePlus, create images first, animate them with better control, and make free AI videos without wasting credits too fast.
3. Add This Tiny Prompt Trick Before Every ChatGPT, Gemini, Claude Prompt. Add one simple clarifying line before your AI prompt to help ChatGPT, Claude, and Gemini understand your goal better and give cleaner outputs with less editing.
FIRE RECAP: BIGGEST AI NEWS THIS WEEK
🔥 Anthropic launched Claude Fable 5 as a “Mythos-class” model, then suspended it just 3 days later. The reason: a U.S. directive over possible jailbreak risks and foreign access.
📈 OpenAI confidentially filed for a U.S. IPO. Reuters says the company could target a valuation as high as $1T, but OpenAI says timing and terms are not final yet.
🌍 Google launched Gemini 3.5 Live Translate, a near real-time voice translation model for 70+ languages. It keeps tone, pacing, and pitch, and works across Google Meet, Google Translate, and the API.
🧠 OpenAI published its new AGI roadmap, saying its next goals include an automated AI researcher, faster economic growth, and “personal AGI” for everyone.
🕵️ OpenAI’s threat report exposed China-linked accounts using ChatGPT for influence campaigns around U.S. AI data centers, tariffs, and fake breach stories.
TODAY IN AI
AI HIGHLIGHTS
🏛️ OpenAI is now under investigation by a group of U.S. state attorneys general. The subpoena reportedly asks for documents on ads, user engagement, minors, seniors, health data, and internal safety policies.
💸 Coinbase for Agents is live. Your AI agent can now trade crypto, rebalance your portfolio, and even pay for premium research data through x402. It works inside ChatGPT and Claude via Coinbase’s MCP server.
🧩 Meta’s $2B Manus deal is reportedly falling apart after pressure from Beijing. Meta has cut Manus off from internal systems and stopped data sharing, as China pushes harder to control strategic AI tech.
⚔️ Ukraine’s defence AI chief says war is moving toward a “war of operating systems.” Ukraine wants one AI network to connect drones, battlefield data, and command decisions faster than humans can alone.
🤖 Mark Zuckerberg told Meta employees the company made “mistakes” in its AI workforce shift. Meta still plans to spend up to $145B this year, while moving more teams around AI systems and model training.
💰 AI Daily Fundraising: Genspark raised a $100M Series B extension at a $2.6B valuation, bringing its total Series B funding to $485M. The company says its enterprise AI platform is now used by 6,000+ businesses, showing rising demand for AI systems that can complete real work across presentations, dashboards, research, and internal tools.
NEW EMPOWERED AI TOOLS
🚀 Vercel Drop lets you deploy a file or folder by dragging it into your browser, with no Git, CLI, or local setup needed.
💻 Kimi K2.7 Code is Moonshot AI’s coding model for long software tasks, 256K context, tool use, multimodal inputs, and open weights.
🔥 Prometheus by Firecrawl turns web data requests into Firecrawl code, then helps collect and maintain that data as pages change.
🍰 CakewordAI lets kids point a camera at any object to learn its name in another language, with 100% on-device AI and no data collection.
AI BREAKTHROUGH
We all know AI agents can write code like absolute rockstars, but new research from Anthropic reveals that when it comes to biological research, these models can fail before the actual science even begins.
If you ask an AI to pull data from biology databases, you might get wildly different answers to the exact same prompt. Here’s what the Anthropic team discovered:
In one test, Claude Sonnet 4 was asked to pull Ebola sequences. The expected answer was 266 sequences. Instead, across different runs, it returned 106, then 15, and then just 5, even though nothing in the prompt changed.
One faulty retrieval made an Ebola outbreak look like it traced back to 1922, rather than the true, manually curated date of early 2014.
The agents are forced to fight through scattered databases, hidden website rules, and fragile scripts just to scrape the correct information.
Think about the real-world impact of this. If researchers are relying on AI to gather biological data, a simple retrieval error can completely derail an experiment.
The good news? There is a very clear fix. The study's key finding is that equipping these agents with a repeatable retrieval tool made their data gathering far more accurate and significantly more consistent.
We read your emails, comments, and poll replies daily
How would you rate today’s newsletter?Your feedback helps us create the best newsletter possible |
Hit reply and say Hello – we'd love to hear from you!
Like what you're reading? Forward it to friends, and they can sign up here.
Cheers,
The AI Fire Team
Reply