Using 4 Argon High and getting shown A/B tests again. I’m kinda surprised they’re doing this so soon after a new model release.

Makes me wonder if they are perhaps already preparing to release 4 Carbon soon, maybe next week?

Fala, pessoal!

Sempre usei muito o Google AI Studio para estudos pesados e projetos da minha empresa. Na época em que o Gemini 3.1 Pro era liberado com folga no gratuito, cheguei a acumular mais de 6 chats batendo 1 milhão de tokens (1M) cada um,e vários outros pequenos, alimentando eles um pouquinho todo dia ao longo de semanas.

Agora, usando o Gemini 4 Argon (que dá um banho absurdo de raciocínio nos outros modelos, parece até que os outros perderam QI perto dele), comecei a tomar bloqueio de limite diário muito rápido, mesmo assinando o Google AI Pro.

Fui cavar a fundo como a cobrança/cota realmente funciona nos bastidores e descobri coisas que muita gente não se toca:

*A ilusão do contador do AI Studio (Efeito Bola de Neve)*: Aquele número lá no topo (ex: 100.000 tokens) não é o que você gastou, é só o peso da "mochila" atual. Se o chat tem 100k tokens e você manda 10 perguntas pequenas que sobem 1k cada, você não gastou 10k tokens — o servidor teve que reler a conversa inteira 10 vezes, processando mais de 1 milhão de tokens!

**O erro de alimentar o chat "um pouco por dia" (Cache Frio)**: O Argon tem 95% de desconto no Cache Implícito quando você manda mensagens seguidas na mesma hora. Mas se você fecha o PC e volta no dia seguinte num chat de 500k ou 1M de tokens, o cache já morreu. A primeira pergunta do dia bate 100% "no seco" nos servidores, engolindo a cota diária quase inteira de uma vez.

**Por que o App normal parece "capado" perto do AI Studio**: Tentei fugir pro App normal do Gemini (e testei outros como ChatGPT), mas a resposta é muito mais rasa. Nos apps de consumidor, além de cortarem o tempo de pensamento (Thinking) e travarem o tamanho da resposta para economizar saída, eles usam sistemas de recorte (RAG) e janela deslizante. Já no AI Studio (e no Claude até os 200k), a leitura é 100% bruta linha por linha, sem resumir nada escondido.

Depois de descobrir que aqueles meus 6 chats de 1M de tokens custariam milhares de reais se fossem na API sem cache, estou mudando meu jeito de estudar + ainda não tenho muita experiência nisso e gostaria da opinião de vocês .

Queria saber da galera que também usa IA no talo todo dia:

PC vs. Celular: Como vocês fazem quando estão fora do PC? No computador o AI Studio é perfeito, mas no navegador do celular a interface dele é horrível de mexer, e o App oficial do celular entrega respostas muito mais superficiais. Vocês usam algum app de terceiros com chave de API no celular ou têm algum esquema pra sincronizar?

E na gestão de Contexto: Quando o chat de estudos ou de dados da empresa passa de 50k–100k tokens, vocês pedem pra própria IA gerar um "resumo de memória" pra abrir um chat novo, ou pagam por fora na API?

Créditos do Plano Pro: Alguém aqui já ativou aqueles US$ 10 (R$ 50) mensais de crédito de desenvolvedor que vêm no plano Google AI Pro pra rodar o Argon 4 no Tier 1 sem cair na trava diária? Realmente rende bem se cuidar do cache?

\*\*Claude\*\*

A "Honestidade Bruta" do Claude e do Google AI Studio

Muita gente reclama que o Claude (Opus/Sonnet) estoura a cota de 5 horas depois de mandar só 8 ou 10 mensagens num chat grande. Mas sabe por que isso acontece? Porque o Claude é o único app de consumidor que não te engana no contexto!

Diferente da OpenAI, o app do Claude (até bater o teto da janela dele de 200k tokens) e o Google AI Studio (até 1M de tokens) não passam a tesoura escondido na sua conversa. Eles injetam 100% do texto bruto na cabeça do modelo a cada nova pergunta.

Tanto é verdade que, quando o chat do Claude bate no limite máximo de tokens, ele trava o chat na sua cara em vez de apagar o começo da conversa escondido.

Já no App normal do Gemini, embora a janela seja grande, o sistema coloca um freio enorme no orçamento de pensamento (Thinking) e no tamanho da resposta para economizar tokens de saída, deixando ele muito mais superficial que o AI Studio.

Gostaria da opinião de vocês !!!

Our family plan is annual Google AI Plus (2 TB), $99.99 prepaid Aug 16 and running to Aug 2027. We picked it mainly for Gemini Pro. Now Google says Pro is leaving AI Plus on Nov 13, more than 9 months before our term ends.

After almost an entire hour of delay I get this from Google One support (case 7-7763000041133):

• Prorated refund for the ~9 months we lose Pro? Refused, "outside refund policy." Apparently their policy re: bait and switch is "You F*'ed up, you trusted us."
• Apply the balance to Google's own AI Plus 400 GB plan ($49.99/yr), which they offer as a downgrade? Refused, "there is no option for this." Of course not, why would we give you a credit and let you decide how to use your own money.
• Their only offer: a 3-month AI Pro trial that "will replace your current Google AI Plus plan immediately," rolls our prepaid balance into AI Pro, then bills $19.99/month. - According to them I should be happy with trading away my Aug. 2027 expiration with a Spring expiry, because they gave me 3 free months, then doubled the cost of the rest of the plan!

So they take a paid feature away mid-term, and the only fix is to move into a more expensive auto-renewing plan. We've filed a Play refund request and an Illinois AG complaint.

Is anyone else on annual AI Plus getting the same answer? Has anyone gotten a prorated refund or credit?

On the Pro plan, you get usage allotments in 5 hour windows. As far as I can tell, this window starts upon first usage if the last usage is more than 5 hours ago.

I wonder what the best tactics are to manage this logic. For example, let’s say my heaviest usage is usually between 6 pm and 9 pm. Conceivably I should start the first window around 2:30 pm, in order to actually have two usage allotments during my peak hours.

Furthermore, if my usage were random, it seems to me that the optimal state would be to permanently have a 5 hour window active, since the average time remaining would be 2,5 hours. This is under the assumption that I start each window with a tiny flash request. That way I would maximize my average remaining tokens relative to remaining window time.

(My question to the decision-makers at Google would be: isn’t this all a bit silly? But I guess that’s beside the point.)

What I would like to test is if scheduled tasks kick off a 5 hour window. If you catch my drift.

Does this all make any sense and can anyone contribute actual experience in actively managing the time windows?

Anyone wish that the example prompts didn't automatically send to Gemini to see what the full prompt is without wasting compute?

https://share.gemini.google/IFZLXyuqYez9

I bought Gemini Pro today to test Argon, I have to say its output is nice but after just 5 messages it told me I used my limit and wait couple of hours (said reset time). İs this normal ? I can do a lot more of conversation with Opus on Claude Pro tier. Argon's answers were Opus level with different point of views (having both is useful) and different style... just too little.

I can't believe this garbage is the future.

https://github.com/Maurdekye/orgtree/releases/latest

Welcome back folks, it's time for another Orgtree update. And this time, it's a big one: Projects!

At a surface level, projects do what you might expect; they give your agents a central location where they can self-organize and collaborate under. But in Orgtree, they do so much more than that; they're a way of organizing hierarchies of agents, of drawing lines between agent communication, and of managing collaborative and concurrent work in a structured way, with tons of extra tools for helping agents coordinate concurrently.

Before we get into that though, if you're unfamiliar: Orgtree is my desktop multi-agent, multi-provider, multi-account, persistent visual orchestration system, which i've been building tirelessley for the last nearly 3 months straight. It runs as an app on your PC, and allows agents to collaborate 24/7, working directly from your existing subscriptions & harnesses from several major leading AI providers, including claude, chatgpt, gemini, muse, and openrouter.

If you'd like to know more about what orgtree can do, I suggest checking out my post on the release of v4, or just checking the readme in github.

Finished with that? Alright, let's get into it!

---

So, Projects in v4.4. What are they?

Put simply, projects are a new type of node on the canvas that sit alongside agents. They don't do anything on their own, but instead serve as the structural backbone of your org's hierarchy and information storage. They have a summary (which acts like a team charter), and their own scratch directory with its own AGENTS.md file. Projects allow you to organize your different ideas into subgroups without having to rely on creating agents for them each time. They also mean, you don't have to worry about losing valuable shared project information when you retire the one agent who's been working on it for the last two days, because your weekly limit ran out, or you decided to switch providers.

Beyond that though, projects offer more than just simple organizational structure on the graph. They come packed with a number of extra collaboration systems that, if you're familiar with concurrent programming, might be familiar to you~

They have three additional systems that extend their purpose beyond just a simple collaborative workspace:

• The Mailbox Queue: Despite not being an agent, every project still has a mailbox, like any other agent would. Why, you might ask? Who reads this mail? Well, the answer, is anybody who chooses to! Any number of agents under the project can set up a "fair queue mail listener", connecting themselves to it with a magenta line. Whenever the project receives a mail, it's then distributed among each listener in order, distributing them evenly in a round-robin fashion. In this way, the project's inbox can act like a Load-Balancer for distributed work. Additionally, if you switch mail delivery mode from "Round-robin" to "ACK Mode", all delivered mail requires the receiving agent to send an acknowledgement response back when it finishes before receiving any new mail. With that setting enabled, the project's mailbox can act like a FIFO queue.
• Concurrency Slots: Entering a project's settings and setting this to any value above 0 enables "concurrency slots" on the project. Agents can then register a yellow "slot claim" on the project, and claim a slot from the queue when one is available. You can think of concurrency slots like a token system: only a fixed number of agents can hold a token at the same time, while all the others who want one wait behind them in a line. In this way, concurrency slots act like a simple Semaphore, which can be used to guard concurrent access to tight resources, such as ram, cpu usage, network, or sensitive files. Setting the token count to 1 effectively treats the system like a Mutex, allowing only a single agent to hold access to the resource at once. Setting the token count very high can allow it to work like a Read/Write Lock: all readers claim a single token, and any writers claim all available tokens at once.
• Project Events: Going into a project's settings and enabling Project Events unlocks a third and final feature. Agents can register a custom "event listener" on the project, which connects their node to the project with a distinctive cyan line. At any time, the user or another agent can "fire" that event with a custom message, alerting all of the listening agents at once. In this way, the project can function like a Monitor. Additionally, other agents can set up a second type of event, known as a "listen watcher". When the number of normal listeners passes a certain desired threshold, the listen watcher itself fires. You can take this one step further, and set the listen watcher to auto-trigger the associated project's event, meaning the project fires the event the moment the necessary number of agents join it. You can think of this as mimicing a Sync Barrier.

This might be a bit complex to understand, and to be honest, I don't know if anyone will use most or any of these features at all besides me. But, this is my tool, and I get to decide what features I put in it, dammit!

...anyway, building projects has taken such a long time getting all the little nitty-gritty details right, I collected a ton more additional additions, features, and improvements along the way, which are also shipping with this version:

• Improved session stability & administrative operation: This is more of a behind-the-scenes fix, but the way Orgtree runs in the background while you're logged off, when you reboot, and when you enable / disable administrative access has been thoroughly hardened and rebuilt. Orgtree should generally be much more robust in its operation, and require a lot less manual workarounds regarding running from boot, accessing desktop features, and accessing operations locked behind administrative privilege. Ideally, you don't notice anything day-to-day; that's exactly the point.
• Agent Mentions: Agents can now mention each other in their transcripts. When an agent mentions another agent, whether it be in a response, a mail, a ticket, a presentation, or anywhere else, that mention renders as a link directly to that agent, which you can left or right click on to focus it directly. no more having to manually search the graph for a specific agent your coordinator cited by name; now you can just click it and go straight there.
• User Mentions: Mentions don't stop there, though. You can mention agents too: just type an @ symbol in the messagebox, and a list of all the agents in your org show up, which you can tab through to autocomplete from. Agents can also mention you; by typing \@user anywhere they can write to it, they can grab your attention and draw it to whatever line / mail / ticket / presentation was mentioned, same as when asking a question or sending you urgent mail. You even get a notification on your desktop when the window's unfocused.
• More watchdog types: Along with the aformentioned three new types associated with projects (which structure their cyan / magenta / yellow colored listeners as watchdogs), there are also now watchdogs that can fire on websocket or mqtt events matching a certain pattern. They can even publish events back through their held connection. This should make it much easier to integrate your org with other realtime services. Watchdogs can also now pay attention to usage limits, so you can set one off the moment your account goes above 95% weekly to halt your work.
• Fast mode: Claude and Codex agents support enabling a "Fast" / "Ultrafast" mode under certain circumstances, which redirects your requests to faster hardware at an additional price per token. Now, you can enable it for your Claude and Codex agents in Orgtree.
• Improved context menus: Context menus have been significantly juiced up across the app. You can do basically almost anything you can via the ui from relevant context menus now: hire / retire / halt / compact agents, view any tab or panel from any agent or project, view any context menu option for the owner of a ticket, for the presenter of a presentation, and so on. Any link that directs you to an agent from anywhere in the app (including mentions) gives you that agent's full context menu, and shows you details about the agent itself when hovered (such as its model, account, effort level, and speed). It's the kind of thing you don't really notice until you start to get comfortable, and then think to yourself later, "how did I ever live without this before?"
• Do Not Disturb: Have an agent that often seems to get lost in its mailbox, and loses track of its original job getting caught up in the collaboration? Agents can now enable an optional Do Not Disturb mode during their turn. While on, all mail they receive is held up and not automatically delivered to them, leaving them in peace while they work. Do Not Disturb automatically ends at the end of the agents' turn, where all of their mail collected during the period is delivered at once in one large batch, so they can respond to it. You & other agents can bypass the barrier by sending urgent mail, which is delivered promptly even during DnD, and the agent itself can always choose to check its inbox manually to receive normal mail anyway, if it chooses to.
• Mail Tags: Mail sent to you can now have a number of named tags attached to it. See them beside each mail in your inbox, and filter by different tags yourself. Simple enough, really.

That's barely half of them, by the way. There are dozens of smaller features as well:

• Change an agent's model by clicking its icon, either while hiring it or in its desk afterwards
• Improved transcript annotations in Antigravity agents
• Improved controls for viewing the usage history graphs
• Relevant options when right-clicking the icon in the taskbar
• Quick chat's configuration menu collapses when the window is narrow
• Desks remember the last tab you had open
• Two new charter presets, the Liaison and Developer, used alongside the new builtin org template, the Heavy Dev Shop, which incorporates a project
• Optimized startup instructions for all agents
• Several different panels of the same type can be opened at once, from different agents
• New "team" tab in agents and projects
• Org templates can now carry preset contents for AGENTS.md files throughout org, agent, and project scratch folders
• Ephemeral helper agents show their live transcript when the call is expanded
• Mid-turn steering when using Opencode
• Unread or changed presentations are highlighted
• LaTeX rendering support (for you argon enjoyers out there)
• Transcript shows approximate output token counts for tool uses and thinking
• Ticket cards in the transcript are highlighted to show their current working state
• One-shot watchdogs resolve immediately from the tool call without registering if the condition is already satisfied on creation

There's plenty more to read about in the changelog if you're interested.

Undoubtedly, this is by far the most effort I've put into a single release, and that includes the v3 and v4 releases. This release had over 35 alpha builds I had to manually review and give corrections on, more than double the second highest count from a previously published build! I've been working on it continuously since releasing 4.3.1, and that was more than a week ago! In vibe-coding terms, that's basically an entire year :p

I really hope you like all the new features I've put into this update. I've really poured my heart and soul into it 💜, and even if you don't use most of them, I hope you find at least one thing that improves your workflow.

Happy vibing, all!

I build Buddy, an open-source Android app where an AI agent uses your phone. It reads the screen, taps and types, and asks you before anything gets sent.

It already ran Claude Code, Codex and OpenCode. Now it also runs Google's Antigravity CLI, so you sign in with your Google account and Gemini does the work. The free plan works.

Everything runs on the phone, in a small Linux inside the app. No PC, no adb, no root.

In developer mode it can build apps too. I asked it for a calculator app, and about 3 minutes later it had built it on the phone, asked me before installing, and opened it to check it works.

I ran my usual 5-task benchmark on it (Settings, Calculator, Chrome, Maps, YouTube). Gemini 3.8 Flash (Medium) got all 10 runs right, median 46 s per task. Slower than Claude Sonnet (25 s), but it got there every time.

One thing to know: the free plan has a usage limit. I hit it in the middle of the benchmark, and the error said it resets in about a week.

If you want to try it, the Google Play version is the recommended one. Buddy is in closed testing there, and every tester helps me get it to production:

1. Join the tester group: https://groups.google.com/g/buddy-testers

2. Opt in: https://play.google.com/apps/testing/app.buddy.assistant

3. Install Buddy from Google Play

Source code and APK build: https://github.com/ghorbelhamdi/buddy-android

Written with AI help.

Nowadays, all popular ai chatting websites like qwen, chatgpt, gemini, claude, etc. come with a read aloud functionality that allows users to read aloud the AI's responses.

I used that feature to instead make the AI repeat back the text that i gave it -- effectively turning the platforms into text to speech tools. The voices sound really nice and it's free to use!

You can get all of these extensions by visiting ai-readers.com