dayson — e/llm retweeted
I used Gemini 4 Argon to make Subway Surfers for the new flying Tesla Roadster 🚀
Fly over moving traffic, hit the thrusters to barrel roll in the sky, and collect air power-ups to set a high score.
Play + code below!
it blows my mind how many people get on here and start giving advice
i can barely figure out what we should be doing and how and every week things change
and anything i do find conviction on is rarely generalizable
but you all got advice for me
dayson — e/llm retweeted
Hot take: I don't like queueing messages.
Modern models are smart enough to take a "steer" message and not get distracted by it
<3 the hustle here! 👇
I’m 14 and I build open-source AI tools.
Now I’m looking for my first development sponsor.
I’m looking for a company willing to cover my Claude Max subscription ($100–200/month) so I can keep building, researching and shipping.
In return, I’ll recognize you as a sponsor across my GitHub and open-source projects.
So I’m shooting my shot:
@neondatabase @datadoghq @Railway @supabase @vercel @Cloudflare @cursor_ai @huggingface @Replit @getsentry @render @flydotio @planetscale @upstash @convex_dev @modal_labs @togethercompute @GroqInc @github @linear
If your company wants to sponsor a young open-source developer, reply below.
Let’s build some cool stuff.
dayson — e/llm retweeted
Google’s new Gemini 4 Argon equals GPT-6 Astra on the Artificial Analysis Intelligence Index at 60% of the Cost per Task with discounted prices. Google is now back to being one of the top three labs in intelligence achieved
Gemini 4 Argon is @GoogleDeepMind’s first proprietary model above the Flash class in over 7 months. With high reasoning (the highest available), it scores 53 on the Artificial Analysis Intelligence Index, matching GPT-6 Astra (max, 53) and 1 point ahead of GPT-6.1 Sol (max, 52), with gains driven by lower hallucinations and stronger agentic capabilities.
At its current 50% pricing discount and with cache discounts increased to 95%, Gemini 4 Argon costs $1.99 per Intelligence Index task, 60% of GPT-6 Astra (max), but 2.7x GPT-6.1 Sol (max). After the discount ends, this will rise to $3.98 (~1.2x GPT-6 Astra (max)).
Gemini 4 Argon is currently being rolled out to selected users and is not publicly available. The 50% discount is an initial promotion. Google has not yet confirmed the promotion end date
Key benchmarking results for Gemini 4 Argon with high reasoning:
➤ Google returns as one of the top three labs on intelligence: Gemini 4 Argon (high) scores 53 on the Artificial Analysis Intelligence Index, matching GPT-6 Astra (max, 53) and 1 point ahead of GPT-6.1 Sol (max, 52). This is 23 points above Google’s previous non-Flash model, Gemini 3.1 Pro Preview (30) and 12 points ahead of Gemini 3.8 Flash (high)
➤ Launch discounts of 50% make Gemini 4 Argon competitive on Cost per Task: At current discounted pricing, Gemini 4 Argon (high) costs $1.99 per Intelligence Index task, 60% of GPT-6 Astra (max, $3.26) for a comparable level of intelligence. This cost efficiency is driven by lower token prices, rather than reduced token use, with Gemini 4 Argon averaging 62k output tokens per task, compared with 27k for GPT-6 Astra (max). Google has not yet confirmed the promotion end date, but on standard pricing, Cost per Task will increase to $3.98
➤ Stronger agentic performance: Historically a weaker area for Gemini models, Gemini 4 Argon shows improvements across agentic evaluations. It ranks #1 on AutomationBench-AA at 77.5%, 6 points ahead of Claude Sonnet 5.5 (max, 71.3%). On Terminal Bench 4, Gemini 4 Argon achieves 57%, a +53 point improvement from Gemini 3.1 Pro Preview, only behind Claude Sonnet 5.5 (max, 64%), Claude Opus 5.5 (max, 60%) and GPT-6 Astra (59%). On AA-Briefcase, it reaches 1494 Elo. This is driven by a 65% rubric pass rate, the highest we have recorded, but lower Analytical Quality (1576 Elo) and Presentation Quality (1308 Elo)
➤ Lowest hallucination rate among leading models: On AA-Omniscience, Gemini 4 Argon has a 15% hallucination rate, the lowest of any model scoring 45+ on the Intelligence Index, compared with 51% for GPT-6 Astra (max) and 54% for GPT-6.1 Sol (max). This means Argon is much more likely to acknowledge when it does not know an answer rather than guess incorrectly. On accuracy, Gemini 4 Argon scores 50%, a 5 point decrease from Gemini 3.1 Pro Preview, and 13 points below GPT-6 Astra (max, 63%). With this slightly lower accuracy, its overall AA-Omniscience score of 42 remains in line with GPT-6 Astra (43) and GPT-6.1 Sol (42)
Key model details:
➤ Context Window: 1M tokens
➤ Multimodality: Text, image, video, and speech input, with text output
➤ Pricing: $4/$20 per 1M input/output tokens at standard pricing, currently discounted 50% to $2/$10. Cached input tokens receive a 95% discount ($0.10 per 1M at discounted pricing), up from 90% on Gemini 3.8 Flash
➤ Long Decode Continuation: We tested Gemini 4 Argon with Long Decode Continuation, a new Gemini API feature that pauses long responses and resumes them across follow-up calls. This lets reasoning run up to 1M output tokens without request timeouts
dayson — e/llm retweeted
Software should be fun. It should make you feel something, positive hopefully. Utilitarian software is the worst. The human experience is why life is worth living (even for something as teeny tiny as a terminal).
Learn to build a harness, folks.
It's not surprising to me that so many YC builders want to build domain-specific harnesses.
If you work long enough on a domain-specific problem, you quickly realize the opportunity. But you also realize how important that harness will be to stay competitive in the agentic era.
From a product perspective, harnesses open up interesting new surface areas and experiences for the services/products you provide.
From a technical perspective, harnesses are how you build and maintain a framework and set of best practices for how your users/customers interact with what you offer.
Understanding how to build and design a harness means you can build much stronger intelligence stacks, given that you can customize it and understand the domain well. That's extremely valuable. It may not seem apparent yet, but a harness wave is coming.
If you are getting started, give this list of harness papers to your agents and start upskilling: academy.dair.ai/papers/colle…
If you are already a builder, try building one for your specific domain. It's a lot of fun, and you learn a lot of interesting things to enhance your current agentic tools.
We can fix everything. wecanfixeverything.com
dayson — e/llm retweeted
I can’t stress enough how little an idea matters compared to the agency of the people executing the idea.
I have had the privilege of knowing and sometimes even working with some of the most successful people (by various metrics).
The difference between mediocre and excellent work and outcomes is predominantly one of agency.
In practice this means: they dont wait for things to happen to them they go out and make things happen for them.
They don’t wait for someone else to do something, for someone to teach them, for someone to give them the path, etc. They just go out and find a way to do it.
I think the single biggest superpower these people have is the realization/belief that the world around them is completely mutable. Most everything that happens is because a person made it happen.
I used to tell people to look around the room you’re sitting in. Look at everything. Every noun. It almost all exists because a person willed it into existence. Nothing is stopping you from doing the same.
I see people online all the time dismissing someone else’s success because “I had that idea first” or whatever. I mean… yeah? If so then the difference is… you. So a bit of a self own whenever I hear that.
Number one tip: act with agency.
dayson — e/llm retweeted
Beware people obsessed with outcomes instead of building outcome machines. Its worse than ever with AI, but these people existed before. Short term results above all else, etc. Don't fall into the trap. Invest in building strong fundamentals, invisible supports, and outcomes flow like water. An outcome machine.
dayson — e/llm retweeted
At this point I just want models to be faster and cheaper. I have enough intelligence. Please, size doesn't matter any more, I need performance.
🔥 we're turning Gemini on Android into a true agent that actually understands your phone! This is one of several upcoming releases that will enable Gemini to safely configure, personalize, optimize, troubleshoot your phone for you.
Try it under the 'labs' chip on Pixel + Android 17!
More to follow.
Google launched a new feature in @GeminiApp called "Device Help" which is now available on Pixel devices (Android 17).
An Android phone can typically have >300+ settings.
You don't have to be a power user any more to truly customize your phone! All troubleshooting questions are 1 prompt away!
We'll be rolling out to more Android devices in the future, with expanded set of capabilities.
More in 🧵
dayson — e/llm retweeted
Training tiny models for special purpose use cases works so incredibly well if you have a great self improving recursive flywheel. Shopify ML team is on fire.
finetuned 0.8b model beats GPT 5.6-sol xhigh in this very specialized task.
dayson — e/llm retweeted
Just built my first Omarchy plugin! This also happens to be the first piece of software I've ever made solo entirely with AI. Back-and-forth over English and nothing else. So two firsts for me. Super fun experience.
Here's a quick little tour. Hope you dig it.
i need this to succeed, if only so everyone gets to experience a tiling window manager at least once in their life
Omarchy is blowing up. I've never been involved with anything in my career that has grown this fast. With Ruby on Rails, we had years to build solid institutions, teams, and relationships. With Omarchy, we've been forced to figure it all out in twelve days. It's exhausting, but also incredibly exciting.
It was never sustainable with just Ryan and me running everything. That's how it was, more or less, up until Quattro. Lots of other contributors, but all the responsibility was on us to make sure the ship stayed afloat, the servers didn't crash, and fixes got pushed out quickly.
Now it's time to build a proper institution. Durable, resilient, and competent. That's what we're doing here on Basecamp now. I'm spinning up teams for every facet of responsible distro management, and I'm getting an absolute outpouring of interest for all of them. Everyone wants to be part of this. We're winning hearts, minds, and volunteers at an astounding rate. Great! We need all of it to succeed.
Because make no mistake: There are many people who'd love to see this rocket blow up before it reaches the moon. Aggrieved Linux users who don't like the sudden attention their exclusive hobby has received. Competing Linux distributions that are seeing our numbers explode. Mac stans who've sunk their identity into an apple. And, of course, any of the haters I've picked up in my quarter-century career speaking bluntly on the internet.
They're not going to succeed. Because we've already become unstoppable. There's too much momentum, too much money, and too much support now backing this effort. We're living the Mandate From Heaven meme at the moment. And we are here to fulfill the prophecy: The Year of Linux on the Desktop!
That has been a joke for two decades. But by the end of the year, nobody at Apple or Microsoft is going to be laughing. They're going to be scrambling. Because neither of these proud organizations currently has any method to counter the speed, vision, or ambition with which we're going to accelerate into the future of personal computing.
This is the moment. This is the opening. This is our chance.
For thirty years, we've been subject to one OS overlord or another. Dictating how we compute. Choking off competitors through platform malfeasance. Tollboothing the distribution. That ends now. Because Linux is going to win. And Linux is free. As in beer, speech, and source.
But just because it's inevitable doesn't mean it's going to be easy. We have a lot of work in front of us if we actually want to make our mark. But there's never been a better time for this kind of delusional ambition. The age of agents is the unlocking factor. It sounds like a LinkedIn slogan, but it's true. Where the application of tokens goes, the innovation follows.
We can fix everything.
Let's do it together.
Let's go.
---
This is what I sent to the dozens of new volunteers who've signed up for teams within the new Omarchy organization yesterday. But we might as well broadcast our mission and intentions to the world too.
dayson — e/llm retweeted
I'm big into optimizing my airline miles and using them at the right time, so I'm excited about today's launch, where we’re making that much easier in Search! You can now pull up the live cost in points or miles for flights and hotels directly in AI Mode.
Describe what you’re looking for (and the rewards program you have in mind) to see real-time rates directly from our partners. Once you find the option you want, AI Mode links you straight to the airline/hotel site to complete the booking.























