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- 🤯 Google’s New Gemini 4 Argon!
In partnership with
Google says Gemini 4 Argon can find and patch software vulnerabilities on its own. It’s already being used inside Google for debugging and codebase migrations.
What's on FIRE 🔥
IN PARTNERSHIP WITH VELO
A product doc. A screen recording. A few screenshots. A prompt. Your browser. Even a rough recording of yourself.
Velo turns your product context into a polished demo, explainer, tutorial, or walkthrough. Create from prompts or existing inputs, edit, add narration or avatars, record yourself, and keep everything on-brand, all in one workflow.
No camera. No editing expertise. Just a faster way to create work videos.
AI INSIGHTS
Google has announced Gemini 4 Argon, its new frontier model built for long-running coding. For now, access is limited to trusted cyber defenders through Google’s Fairwind Program before a broader rollout. The biggest upgrades:
1M output tokens, up from 64K, designed for unusually long reasoning and agent workflows.
DeepSWE v1.1: 77.9% for long-horizon software engineering.
AutomationBench: 51.3%, ranking #1 in Google’s disclosed comparison.
LVBench: 91.7% for long-video understanding.
CWE-bench v1: 68%, tying GPT-6 Astra for first on vulnerability remediation.
Across Google’s 18 disclosed comparisons, Argon led outright on 12 and tied for first on one. Astra and Opus still beat it on several coding, science-terminal, and post-training benchmarks.
Google is already using Argon internally. It says Argon agents found data-center optimizations freeing 300+ TiB of memory, are helping migrate large C/C++ codebases to Rust, and rewrote 32,000 lines of SIMD code in its libgav1 video decoder, producing a Rust version that ran 2.7× faster than the previous Rust port
After the introductory period, Google says pricing will rise to $4/M input and $20/M output.
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AI is moving from experiment… to essential.
Every major industry is integrating it.
Every major company is investing in it.
By late 2025, AI was already an $800B market — growing at a pace that could push it well beyond $1 trillion in the years ahead.
Cloud infrastructure is scaling fast.
AI-enabled devices are multiplying.
Automation is becoming standard.
But here’s the real question…
When trillions flow into this transformation — which stocks stand to benefit most?
Our new report reveals 10 AI stocks positioned across the backbone of this shift — from the companies powering the infrastructure… to those embedding intelligence into everyday systems.
If you want exposure to one of the defining growth trends of this decade, start here.
ALL YOU NEED TO WIN WITH AI
Thank you so much to Lou Bortone and everyone who joined our webinar! 👻 It was a great session, and we really appreciate all the questions, ideas, and energy you brought.
We’ll send the full recording, notes, prompts, and all webinar resources privately to registered attendees. Please keep an eye on your inbox. 📩
1. Free Guide: Build a Claude Business Dashboard That Updates Itself Every Day Like a Pro. Step by Step. With the right setup, Claude can help turn your business data into a living dashboard that stays updated day after day. Here’s the surprisingly simple workflow behind it.
2. Sonnet 5.5 is Here! And It Can Make Seriously Good Videos (5 Incredible Use Cases). Sonnet 5.5's video capabilities is insane. I tested it across 5 real use cases to see exactly what happens when you push it beyond normal text and coding tasks.
3. Start a 1-Person AI Business in 24 Hours: Idea, Website, Leads, Sales, Automation,... A step-by-step guide to turning one business idea into a working AI-powered system in less than 24 hours. Here's the full system using Claude for you.
RUN LOCAL AI ON ANYTHING
You don't need a monster GPU to run AI locally. Just a $5 chip, an 8GB Raspberry Pi, or even your old laptop.
If you have more powerful hardware, you can run LLMs, generate images and videos, write code, and build AI agents without sending everything to the cloud.
Oh, and you might already have enough hardware to run AI. The real question is what you can actually run on it.
In this guide, I'll show you how to run AI locally on almost anything, from $5 chips to massive 8×H100 setups.
I'll break down which models you can run, what actually works, where things get painfully slow, and what hardware you need for your next AI project.
TODAY IN AI
AI HIGHLIGHTS
🧑💻 Grok Bot can now hand coding tasks to Cursor, manage PRs through GitHub and Origin plugins, and even send video demos of what it builds. See its templates.
⚡ OpenAI just unveiled Decisions API, a Jev-like system that lets models choose between predefined options at high speed & low cost. Here's its practical design rule.
😬 Meta says Muse could not have secretly read private messages, while the journalist insists it happened with Full Disk Access off. One side clearly isn’t lining up.
🚫 Reddit is shutting down 2 big doors to its data: RSS feeds & public API access. Researchers, moderators, AI tools will all need new ways to access Reddit content.
🏛️ The U.S. launched America.gov, an AI front door for federal services. For now it answers questions, but passport renewals could become agent-powered next year.
💸 Anthropic’s leaked IPO filing reportedly pairs explosive growth with brutal losses and warnings about “existential risks.” It wants a $2T+ valuation (Reuters report)
💰 Big AI Fundraising: ElevenLabs just doubled its valuation to $22B, up from $11B in February. The voice AI startup also launched a $300M employee share sale, giving staff a chance to cash out.
NEW EMPOWERED AI TOOLS
🎨 Ideogram 4.5 delivers precise AI image editing at native 2K resolution, with prices starting at just $0.008 per image.
🎬 Pexo turns your product, website, or assets into polished launch videos, handling everything from storytelling to voiceovers, music, editing.
📚 Ferndesk keeps your help center up to date with an AI agent that checks every article against your product, and drafts fixes automatically.
🗺️ NotchDodo turns your Mac's notch into a handy dashboard with 14 built-in tools, giving you quick access to everyday utilities.
AI BREAKTHROUGH
Dyna Robotics just released Dyna-2.1, a physical-agent system built around its new semi-humanoid robot Taku, with an unusually convincing demo: roughly one hour of autonomous commercial laundry, shown uncut:
Taku has 2 7-DoF arms, a folding torso/lower body, and four steerable wheels so it can move between washers, dryers, folding tables, and shelves.
The laundry workflow involves about 79 physical steps per cycle and 13 higher-level decision points.
Dyna-2.1 doesn’t just repeat a fixed sequence. A vision-language orchestrator watches the room, tracks machine states, remembers what happened earlier, and decides what to do next.
It can recover from mistakes such as grabbing two towels, dropping items, or being interrupted while operating a machine.
Dyna says the same system can also learn workflows such as server servicing and retrieving items from a refrigerator.
Dyna is trying to prove something harder: that a robot can survive hundreds of small decisions and recoveries across an entire workflow.
Dyna hasn’t published an independent success rate across many hour-long attempts, so claims of “reliable” long-horizon autonomy still need outside validation.
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The AI Fire Team
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