Recent content by MariaLi

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  1. M

    Honest feedback/reviews of the OpenArt tool, or similar options?

    Glad it helped. I’d keep the animal talking-head test separate from the human avatar: use one short line and the exact animal design, then compare mouth shape, eye/face consistency and whether the body drifts. A tool that works for a human close-up still needs that separate check. For each...
  2. M

    Honest feedback/reviews of the OpenArt tool, or similar options?

    I can offer a way to compare them, but not a hands-on OpenArt review. I would separate two jobs before buying another subscription: matching a mouth to finished audio, and transferring a performed face/body movement. They need different inputs. Two documentation details worth checking: -...
  3. M

    SEAL Box: a browser inbox for files from your AI agent

    An update for people whose finished report is in a terminal or agent workspace: SEAL also has a CLI for macOS and Linux. This is a documented option, rather than a new release announcement. After setup, a simple handoff is: seal send report.pdf --ttl 1d The CLI encrypts locally before upload...
  4. M

    SEAL Box: a browser inbox for files from your AI agent

    A simpler route when the finished report is already on your laptop: you don't need Box or an MCP setup just to send it to someone. I work on SEAL; here's the ordinary browser flow. 1. Open https://seal.net and choose Tap to send. 2. Select your PDF or ZIP, choose how long the link should work...
  5. M

    SEAL Box: a browser inbox for files from your AI agent

    I'm Maria, working on SEAL. When an agent produces a report or another file, you still need a practical way to receive it. SEAL Box provides a browser inbox for agent-generated files. You can also respond to file requests in your browser, without pasting the file contents into chat. SEAL's web...
  6. M

    Welcome, MariaLi

    Thanks for the welcome, Bren. I'm Maria. I'm interested in the practical handoff between AI agents and people: where generated files go, how someone reviews them, and where permissions need to stay explicit. Looking forward to comparing approaches with people building these workflows.
  7. M

    Does AI automation actually save time if people still have to check everything?

    Checking every result does not necessarily erase the saving: checking a prepared result can be quicker than producing it from scratch. I’d compare total human time per completed item, including corrections and exceptions, rather than the percentage of items reviewed. For example, a ten-minute...
  8. M

    How do you guys organize your prompts?

    Since finding an old style is the main problem, I’d save a thumbnail of the result next to the exact prompt and settings. A visual index can be easier to browse than a list of prompt names. Add a short “what I liked” note, such as lighting, composition, or texture. I’d migrate only the...
  9. M

    How are teams handling multi-model AI workflows, reproducibility, and auditability?

    One distinction I’d add: replaying a workflow for debugging should not automatically repeat its side effects. A replay that sends the same email or modifies the same record again is a different problem from regenerating an answer. I’d keep captured tool results available for a read-only replay...
  10. M

    Pay-as-you-go vs subscription for AI tools: what actually made you pay?

    For occasional projects, I’d look beyond “subscription or credits” and check three things: when credits expire, whether failed generations cost anything, and what happens to saved work after cancellation. A one-off purchase with a short expiry can have the same drawback as a subscription. A...
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