每天质问一下你们 @notionHQ ，是不是只想赚企业团队的钱，完全不在乎普通个人用户的使用体验了？ 你们到底能不能理解，打开Notion APP和对话框就能用确定且熟悉的AI与自己的数据笔记交互的重要性？ 知不知道用户长期信任你们这个「AI文本记忆层」，首先需要相信自己每个月都有充裕的AI额度完成最重要的工作？ 如果个人用户每个月的预期就是用原价API加价购买Extra Credits，消费比原来多十倍的钱，那么将记忆存储到你们数据库的意义何在，就是为了每个月多花十倍的钱吗？ 如果你们忽略内置AI的便利性，那样鼓励用户在定制任务上全都使用自己的AI+MCP，请问使用Notion的意义何在？你们的APP入口意义何在？一样是接API做数据和文本层，我为什么不用本地Markdown或者Google workspace？

The quota difference between the Gemini $99 Ultra subscription and the $199 version is absurd. I don't understand why Google is doing this, but the Pro subscription is essentially useless, and the Ultra version for $100 offers so much less quota. I really can't wrap my mind around that. They should at least tell the users it. Because, as far as I can see, they are not quantifying the actual quota differences specifically for Antigravity. I had two senior advisors, five implementers work on the codebase, and one QA agent using my entire platform for many hours to collect UX and UI issues. It started yesterday evening, after I upgraded to the $200 package, a decision that proved far superior. The $100 subscription would have exhausted its quota after just 1.5 days of the same work intensity, leaving me at only 16 % of the weekly quota. After upgrading, the agents worked all night in Argon on high, continued today, and ran an extensive QA session that simulated real users on my live production platform, creating accounts, receiving emails, and starting from scratch. I wrote a skill and a prompt for that QA agent, and I’m blown away by how well it works. It’s the first time I’ve had such an effective QA agent. The same prompt failed on the AutoClaw platform of GLM (which mimics Grok) and on AntiGravity with the Flash model (Flash 3.8 on high). In contrast, Argon completed a two‑hour perfect human‑QA simulation. I’m about to write a loop that integrates this process into my Constellation senior advisor/implementer, then runs a human QA tester. So far, only 8 % of the weekly quota has been used, and no cheaper model was involved. When I call sub‑agents, I force them to run Argon on high. In my view, the $200 Geminu Ultra plan is the best deal for coding. It outperforms Anthropic and OpenAI, offering the most reliable and capable coding model available. This level of autonomous testing matches what I’ve only seen from OpenAI’s Codex. It might also be due to the workflow harness that I'm using, the extensive agents.md file, and the local project memory that my agents.md instructions automatically create and update after every action. I saw yesterday someone publishing tips on working with Argon, and I saw there that it was specifically said that Argon loves instructions and also loves the task to test its work and to get detailed test descriptions. This would make it essentially the absolute opposite of the showboat models of OpenAI and Anthropic. My workflow harness combined with Argon might be a match in heaven. I can't quantify how many magnitudes better than anything that I've experienced since I started using AI for coding. I’m considering packaging all of this and putting it online, if I find the time.