🌟 Gemi 3.5 Pro: Get pro acc ready!. .
Free AFIRE Guide | AI Academy | Advertise | AI Mastery A-Z
Plus: GPT-5.6 Pro LEAKED: Mythos 5 Level? Alignment Fix and 1.5M Token Context Inside (Free Report)
So we’ve entered a new phase where autonomous AI agents run continuously in the background, prompting other subagents to write and optimize code endlessly…
What’s on FIRE 🔥
IN PARTNERSHIP WITH SECTION
Free event: Managing a Team of AI Agents – July 16
What happens once you build a mixed team of humans and AI? How do you manage the work and build synergy amongst humans and AI coworkers?
On July 16, from 12 -1pm ET, get ahead and find out because soon teams will have 10 agents for every person and you’ll need to lead them effectively and safely.
AI INSIGHTS
🔁 Agents Prompting Agents. AI World is Getting ‘Loopy’
At Meta’s recent @Scale conference, Claude Code creator Boris Cherny made it clear that continuous AI loops are actively reshaping how work gets done. We are entering the era of agents prompting other agents.
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2 years ago, code was written by hand. Recently, we transitioned to agents writing the code. Now, the new baseline is setting up agents that prompt other agents to write the code.
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Loops authorize a swarm of agents to run continuously. Cherny noted that in his own work, agents constantly run in the background to unify duplicated abstractions and improve code architecture endlessly.
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To keep models from getting lost during these infinite runs, developers use simple tricks like the “Ralph Loop.”
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For “hill-climbing” problems like codebase optimization, an AI can just keep making incremental improvements for as long as there is compute to spend.
While the fundamental concept of a recursive loop is basic computer science, agentic loops are different. They rely on non-deterministic logic, meaning a subagent decides when to stop the loop.
The obvious catch here is the cost. Continuous loops burn through tokens at a wildly faster rate. Because the entire point is to keep the system running indefinitely, there is practically no ceiling to how much compute you can consume.
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LLM traffic converts 3× better than Google search
58% of buyers now start their research in ChatGPT or Gemini, not Google. Most startups aren’t showing up there yet.
The ones that are get cited by the AI tools their buyers, investors, and future hires already use. And they convert at 3×.
Download the free AEO Playbook for Startups from HubSpot and get the exact steps to start showing up. Five minutes to read.
PRO AI SOURCES FROM AI FIRE
1. 100% Worth Saving: 13 Secret Places to Get a Free API Key for Any of Your AI Models in 2026 (Claude, OpenAI, Gemini). As AI agents get more powerful, API costs can quickly get out of control. So this is the backup list for you to test every AI models without wasting money while building with agents.
2. GLM-5.2 vs Opus 4.8: Get Full #1 Open-Source Power for Free (Step-by-Step Guide). GLM-5.2 is out, and it’s basically Opus 4.8 but free. Learn the setup, key features, and workflows so you can get results fast without any paid subscriptions.
3. New NotebookLM 2.0 Updates are IMPRESSIVE! (Full Tutorial). NotebookLM 2.0 now generates real PowerPoint decks and Excel files directly from chat using your own sources. See exactly how this new Google update works.
FREE: GPT-5.6 PRO LEAKED
🚨 GPT-5.6 Pro LEAKED: Mythos 5 Level? Alignment Fix and 1.5M Token Context Inside (Free Report)
While you’re still using GPT-5.5 like normal, a few accounts on X have already posted results from something they call GPT-5.6 Pro.
Twitter tweet
Nobody invited them to test it. They just happened to be in the right place when OpenAI switched on a new checkpoint for a small group of Pro users.
→ GPT-5.6 Pro might already be sitting inside your ChatGPT Pro account since last week, waiting for you to learn how to call it out. Inside this post, you’ll see:
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Comparison between GPT-5.6 Pro and GPT-5.5, Fable 5, and Opus
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4 real leaked demos showing game, 3D world, SVG, and frontend output
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3D scene tests: WebGL house, Boeing 747, Blender robot, solar system
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What GPT-5.6 Pro seems good at
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What GPT-5.6 Pro still struggles with
⚠️ Note: This is reported access, not a guaranteed way to trigger GPT-5.6.
TODAY IN AI
AI HIGHLIGHTS
💻 If you’re still asking AI to “build the whole app,” this Anthropic demo is really worth watching. Their engineers show how they actually build AI software from scratch.
🚀 Google’s Gemini 3.5 Pro is nearing a June launch with a 2M-token context window and Deep Think reasoning. Pro and Ultra users may get access first. Let’s wait to see.
🧠 A fun new tool called “In The Weights” lets you check whether ChatGPT, Claude, or Gemini,… may have learned your name during training. See where you rank here.
💄 Soon, you might test Maybelline makeup inside ChatGPT before buying it. L’Oréal just partnered with OpenAI and revealed the virtual try-on tool at VivaTech 2026.
⚠️ Meta paused an internal AI training program after employee data got exposed.
FYI, the program tracked keystrokes & mouse movements to train Meta’s AI models.
🔐 Anthropic updated Claude’s privacy policy to allow ID checks for flagged users. The process may include passports, driver’s licenses, selfies, and face geometry data.
🎬 Google is investing $75M in A24 to build AI filmmaking tools with feedback from Hollywood artists. Yep, that studio behind ‘Everything Everywhere All At Once’ movie.
💰 Big AI Fundraising: Groq raised $650M after Nvidia’s $20B not-acqui-hire deal took key talent and LPU IP. Now it’s rebuilding leadership and betting on its AI inference cloud across 13 data centers.
NEW EMPOWERED AI TOOLS
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🛠️ Skybridge handles the dev loop so you can focus on your features: MCP server, view rendering, client compatibility, testing tunnel,…
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🧪 AgentX evaluates AI agents before they fail. Create test suites, run evaluations, and pinpoint issues before they reach production.
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🎨 Alai 2.0 captures every little detail about your brand. Use it to create social assets, ads, or any canvas size, all perfectly on-brand.
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📋 readywhen catches every decision and commitment across Slack, email, meetings, and docs. It drafts what’s needed next.
AI BREAKTHROUGH
🛡️ OpenAI’s “Patch the Planet” on Open-Source Security
If you build software, you know that open-source projects are the bedrock of the entire commercial tech industry. But because the ecosystem is heavily decentralized and mostly run by volunteers, securing that code is a problem. OpenAI just announced a new initiative to help solve this exact problem.
Dubbed “Patch the Planet” (a nod to the 1995 movie Hackers), the program teams OpenAI up with the cybersecurity firm Trail of Bits to actively defend open-source projects.
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Security engineers from Trail of Bits will use Codex Security, to identify and triage potential vulnerabilities in open-source projects.
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The security engineers review the findings first. They handle the heavy lifting before the project leads ever see the issue.
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The team actively works with projects to develop patches, write tests, and build reusable workflows so the software stays secure after the initial fix.
While it is still unclear exactly how “Patch the Planet” will scale up its operations long-term, it addresses a critical vulnerability in the tech ecosystem.
By putting a buffer between the bugs and the maintainers, OpenAI is aiming to secure the internet’s foundation while positioning its AI models as a necessary shield against modern cyber threats.
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The AI Fire Team
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