Classified: Mythos 5 is loose? 🐉. .
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Plus: Build a Simple AI Loop Inside Any Normal Claude/ChatGPT Chat (Copy-Paste Version)
China just dropped its “Mythos” rival: Tulongfeng. It’s a 24/7 swarm of cyber agents, and the reported vulnerability numbers are wild. We’ll break down this below.
What’s on FIRE 🔥
IN PARTNERSHIP WITH SECTION
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The companies who win will make bold decisions, rethinking roles, reallocating work, and scaling intelligence.
On 7/23, Section is bringing in top executives from early Al supercompanies like Cloudflare and IgniteTech, to share strategies, insights, and mandates for building an Al-native company.
AI INSIGHTS
🐉 China Dropped Its Answer to America’s Mythos Cyber AI
Chinese cybersecurity giant 360 Security Technology has officially unveiled its domestic counter-measure: an AI vulnerability discovery tool called Tulongfeng. Billed by its founder as “China’s version of Mythos,” this launch is to ensure the U.S. doesn’t maintain a monopoly on automated bug hunting.
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360’s founder, Zhou Hongyi, acknowledged their base models still trail the U.S. by about 20-30% in raw computing power. To fix this, Tulongfeng acts as a “swarm” of specialized AI agents working together 24/7.
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Tulongfeng is already putting in work, reportedly discovering 3,432 software vulnerabilities, with 105 officially confirmed by Chinese authorities.
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They also launched a sister AI called Yitianzhen, designed specifically to automate cyber defense and incident response.
The U.S. previously locked down models like Mythos to keep advanced, automated exploit-hunting capabilities contained. But with tools like Tulongfeng now entering the arena, that containment strategy is being heavily tested.
The new frontier is about which AI system can secure, or expose, the critical digital infrastructure we all rely on. The gap isn’t just closing; the rules of the game have officially changed.
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AI SOURCES FROM AI FIRE
1. How to Create Your Own No-Code AI Support Agent in Base44 + Claude in Minutes. Learn step-by-step how to set up a Base44 AI agent that answers student questions instantly, handles refunds, and guides learners, all with no code.
2. [Claude AI Mastery Playbook] Lesson 8: Master 95% of Claude Code (Beginner- Intermediate). This lesson teaches the loop, workspace setup, Plan Mode, terminal use, slash commands, and file control in Claude Code. Perfect for beginners and non-coders who want to automate coding tasks safely.
💡 Build a Simple AI Loop Inside Any Normal Claude/ChatGPT Chat (Copy-Paste Version)
Prompt engineering is dead, it feels like something from the ’90s. Context engineering still has its uses, but there’s a new idea spreading even faster: loop engineering.
Loops let your AI check itself, improve automatically, and keep producing better results without constant input.
FYI, there’s a full loops guide and a bonus list of 5 powerful AI loops you can build.
But many still see those loops as too complex. They don’t want to deal with Claude Code or Codex setups. They just want to open a normal chat and get something that works.
So in this post, we’ll show how to build a simple AI loop for beginners, just inside a normal Claude or GPT chat, with no coding required.
TODAY IN AI
AI HIGHLIGHTS
👉 Today’s Event Highlight: Anthropic’s AI for Science Briefing in San Francisco. Register or Attend Virtually.
🤯 This is one of my fav vibecoded projects this week. It’s a PDF viewer that makes navigating long PDFs much easier. It should’ve been the default years ago. Try it here.
🍌 Gemini’s personalized AI image generation is now free in the U.S. Nano Banana can pull from your Photos & Google activity data to make images feel more personal.
👀 OpenClaw is now on mobile with apps for both iOS & Android. It looks like the app keeps the web version’s layout & feature set. We’ll try & see how well it works.
📱 Cursor made “phone coding” feel more real. With Cursor Mobile, you can start or manage coding agents on the go. Boris Cherny said most of his coding is now mobile.
🏛️ Anthropic will offer Claude to California government agencies at a 50% discount, with training included to help public employees move faster. Interesting split here.
🚫 Meta is limiting engineers’ use of Claude Code and Codex, according to reports. It’s because their outputs might end up inside Meta training data. That can be messy.
💰 Big AI Investment: South Korean tech giants committed $900B+ to AI chips and data centers, including $518B for new memory fabs, as the country races to ease the global “RAMageddon” shortage.
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Something has shifted in the agency world over the last 12 months.
Not their team size. Not their ad spend. The agencies pulling ahead right now have changed what they sell and how they charge for it.
That is exactly what Agency Advantage 2026 is built around. A free two-day virtual event on June 30 and July 1 where agency owners share what is actually working right now. Here is what you will walk away with:
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Which services to drop and which ones to charge more for
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What to hand over to AI and where your edge still lies
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How to win better clients at better rates
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What the most profitable agency models look like right now
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🧠 PMB gives Claude Code, Cursor, Codex persistent project memory through MCP. No cloud, no API keys, no LLM call on the read path.
AI BREAKTHROUGH
🤖 Agentic vs. Agentive: Today’s AI “Agents” Are Mostly Just Clever Tools
A fascinating new research paper is actively pushing back on the industry habit of slapping the agent label on every capable AI system. What actually makes something an agent in the first place?
The core argument of this paper is that today’s AI agents are mostly just advanced workflows wrapped around LLMs, not truly independent actors.
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Complex behavior ≠ self-directed behavior: An AI completing a browser task doesn’t maintain a durable sense of what it is doing, what its limits are, or why the task matters beyond the immediate instruction.
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Current systems are incredibly good at completing tasks. But their goals, roles, and update cycles are still entirely driven and defined by humans.
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Agentic AI simply looks autonomous from the outside. True agentive AI means the agency and drive actually originate from inside the system itself.
To bridge the gap between where we are and true machine agency, they propose a new framework called the Goal-Identity-Configurator model.
It would actively maintain long-term goals, update its own sense of identity, predict possible outcomes, decide on its own how much to “think,” and learn from both real and simulated experiences.
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The AI Fire Team
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