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Hi {{first_name|everyone}},Google's new Gemini 4 Argon can keep working on a single job for up to a million tokens of output, which is why it's already tackling huge code migrations inside Google, and why most of us can't try it yet.
After that, we've got tools that take on the slow, fiddly parts of shipping a product, from the video to the docs to the actual hardware, plus a couple of AI updates for everyday life and a clever way to stretch your coding budget.
Let’s dive in.
🤿 DEEP DIVE
Image credit: Google
Google Built Argon for the Long Haul
Google is testing what happens when one AI job gets really, really long.
Most AI model launches eventually turn into a scoreboard. Better benchmark here, higher percentage there, number one on something with a name you’ve never heard before.
Gemini 4 Argon has plenty of that too.
But one number tells you a lot more about what Google is trying to do with this model.
1 million.
That’s Argon’s new output token limit, up from 64K.
Google’s pitch is basically that if you give a model enough room to keep reasoning and generating through one long trajectory, you can start handing it problems that don’t neatly fit into a short back-and-forth.
And the examples Google gives are pretty wild.
This isn’t just “write me some code”
Inside Google, Argon agents are being used on C and C++ to Rust migrations ranging from tens of thousands of lines all the way up to the 800K+ line Fuchsia Zircon kernel.
There’s also this oddly specific example involving libgav1, Google’s open source video decoder.
Argon agents took an existing Rust port and replaced 32K lines of SIMD code. They repeatedly profiled it, looked at the compiler output, then produced safe Rust that the compiler could automatically vectorize. Google says the result runs 2.7x faster than the previous Rust port while producing identical video output.
Another team had Argon agents analyze profiling data from across Google’s data centers, find memory optimizations and apply them. Google says the changes have already freed more than 300 TiB of memory, with estimated total savings between 500 TiB and 1 PiB.
That gives you a better feel for what Google means by “long-horizon workflows.” It isn’t really about getting a longer answer. It’s about keeping the model working through a much bigger job.
There’s a reason you can’t just use it yet
Argon isn’t getting a broad launch.
Google is initially rolling it out to trusted cyber defenders through its Fairwind Program while working through pre-release access with the U.S. government and continuing to test its safeguards. Wider access is planned later for developers, enterprises and consumers, starting with paid API customers and Google AI Ultra subscribers.
Cybersecurity seems to be a big reason for the caution.
Google says Argon can autonomously find, validate and patch critical software vulnerabilities. Trusted defenders will actually get a version without cyber guardrails so they can use its full defensive capabilities.
So this is a slightly unusual model announcement. Google is showing off what happens when an AI gets enough room to work through enormous tasks, while also being pretty explicit that those capabilities are exactly why the rollout needs to happen gradually.
The quick take
Gemini 4 Argon raises the output limit from 64K to 1 million tokens.
Google is already using it internally for large code migrations, optimization work and research.
Argon scored 77.9% on DeepSWE v1.1 and leads several enterprise-focused evaluations cited by Google.
Access starts with trusted cyber defenders, with broader availability planned later.
Introductory API pricing is $2 per million input tokens and $10 per million output tokens, with cached inputs priced 95% lower.
🤝 FROM OUR FRIENDS
A quick share we thought you might find useful
The best influencer marketing advice never comes from a report
It comes from someone who’s been there, done that, and has the receipts. Get ready for Return on Influence Festival ‘26. An entire day dedicated to influencer marketing with speakers running some of the best programs in the world.
October 21, 2026, 10 am - 5 pm ET. Free and online.
🤖 AI MADE THIS
Interesting and inspiring creations made with AI
Image credit: u/Rare_Guide_9830
A multi-model coding workflow that cut GPT-6 Astra usage by 98%
A developer built a multi-model coding workflow where GPT-6 Astra plans and reviews while DeepSeek V4.1 Flash handles the implementation and testing. The creator says the setup cut Astra usage by 98%, turning model orchestration itself into the interesting creation.
AI used
GPT-6 Astra, DeepSeek V4.1 Flash, plus Codex Router and the creator’s own agent skills and workflow policy
⚡ QUICK HITS
The latest in AI, tech, and productivity worth knowing
DoorDash has introduced a corporate ordering connector that gives compatible workplace AI agents the ability to find items, build carts, place orders, and track deliveries. Teams could even build a Slack bot that collects everyone’s lunch requests in a thread, while companies can join the broader beta waitlist starting September 30.
Airbnb is adding AI search, filters, listing descriptions, and side-by-side home comparisons in the U.S., including the ability to search across homes, experiences, and services using everyday language or voice. It’s also adding connections and a Travel Map, where people can see trips and recommendations shared by family, friends, and past travel companions.
⚒ TOOL SNAPSHOTS
Futuristic tools within AI, no-code, and productivity
🎬 Pexo
Makes launch videos feel more like directing than editing.
Why it’s useful: Handy for teams that want one place to go from a product idea to a finished video, then just point out what needs changing.
📚 Ferndesk
Keeps your help center from quietly drifting out of date.
Why it’s useful: Useful when product changes pile up and you need someone or something to spot outdated articles and draft the fixes.
🛠️ Autonomyware
Turns a physical product idea into actual engineering work.
Why it’s useful: Useful for hardware teams that want product definition, CAD, code, verification, and manufacturing prep kept together instead of scattered across the process.
ℹ️ ABOUT US
The Intelligent Worker helps you to be more productive at work with AI, automation, no-code, and other technologies.
We like real, practical, and tangible use-cases and hate hand-wavy, theoretical, and abstract concepts that don’t drive real-world outcomes.
Our mission is to empower individuals, boost their productivity, and future-proof their careers.
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