Clark - An AI coworker with its own cloud computer
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Clark is an AI coworker with its own cloud computer - browser, terminal, files, and code. Hand it a real task, close the tab, and come back to finished work: wide, sourced research; websites; spreadsheets; decks; audits; or tested code. It can fan work out to parallel specialists, run on a schedule, and return artifacts with the evidence behind them. Use Clark on web or mobile, work in real repositories with Clark Code, or embed the agent through an OpenAI-compatible API.
Replies
Clark
@stanislav_kirdey Seriously the ability to walk away from a task and come back to finished work is exactly the kind of experience I've been hoping AI would evolve toward . Excited to try this out.
@stanislav_kirdey What’s one real task you’d hand Clark right now and why; and what would you need to see in the returned files or logs to feel confident you could rely on it again?
Clark
@swati_paliwal i handle it a lot of prototype app building, very wide research, git repo analysis, anything where agent with browser can be great like filling out forms etc, and it manages my calendar too!
@stanislav_kirdey the returned artifact bit is what i'd test first. say Clark gives me a sourced research deck, i send it to a client, and they flag one claim on slide 7. can that note come back with the exact file/section/version attached, or am i back to pasting a screenshot into chat? if there's a public sample deck/report, happy to run that handoff once.
Clark
@eason_zhou makes sense!
I've been looking for something that can manage research without constant supervision, and this sounds promising. The idea of parallel specialists is especially interesting. I'd love to know how the system decides which specialist handles each part of a project.
For me, the most valuable feature is returning complete deliverables instead of stopping halfway through the process. I've always felt that execution matters more than speed alone. I'd be interested in seeing a real example comparing the workflow with and without Clark on the same research task.
I'm intrigued by the combination of research, coding, spreadsheets, and presentations in one workflow. I've used separate tools for each of those tasks, so bringing everything together sounds efficient. My biggest question is how well it maintains context across longer projects where priorities and requirements change over several days.
The 'own cloud computer' framing is what separates this from a chat wrapper for me — but it lives or dies on state. Between tasks, is each job a fresh ephemeral VM wiped clean every time, or a durable workspace that keeps files and context so a scheduled monitor run actually builds on the last one? And with Clark Code in a real repo, does it work on a clone in its own env and hand back a PR/diff I can inspect, or does it need direct write access to the repo?
Clark
@noctis06 clark code it will work in the repo and do the changes just like codex or claude
Tried Clark on a market research task and came back to a clean spreadsheet with sources attached, which saved me a real chunk of time. The parallel specialists angle feels like more than a gimmick, the output actually held together.
Clark
@yeliz972799 thanks!
I love products that save me context switching , and this looks like it could do exactly that . Looking forward to putting it through its paces.
Clark
@connor_hayes1 thanks! would love your feedback!
@stanislav_kirdey Actually I appreciate the focus on real deliverables , websites, spreadsheets, research , code instead of just conversations. That's a practical vision . Best of luck with the launch.
Clark
@delilah_raine1 thank you!
Clark
@hamza_afzal_butt yes it can!
A cost and token usage breakdown for every completed task would be really helpful, especially for teams running large research or coding workflow.
Clark
@ill_robyn will add! 💜