Clark - An AI coworker with its own cloud computer

the scheduled monitor use case is the one I'd want most out of this. when it re-runs on a timer, does it diff against the last artifact and surface only what changed, or hand back a fresh full artifact every time and leave the comparison to you?

Love that Clark can fan work out to parallel specialists and hand back artifacts with sources. One thing I'd love is a simple "trust but verify" mode where I can quickly diff what Clark did against my own expectations before it writes to a repo or ships a spreadsheet, so I can catch small errors without babysitting the run.

Love that it actually hands you back evidence with the work, not just a wall of text. Closing the tab and coming back to a finished spreadsheet feels like cheating.

This looks cool! Was wondering what the difference is between this and /loop on claude code? Can't cc agents run autonomously already?

Congrats on the launch — #2 on the day is well earned. The under-discussed part IMO is the OpenAI-compatible API: an embeddable agent means other agents can delegate to Clark, and agent-to-agent work is where a lot of this space is heading. How does the API handle long-running tasks — does a caller get a job handle to poll, streamed progress, or a webhook when the artifact is ready?

Clark caught my eye today. Wishing the whole team an amazing launch! 🎉🚀

giving the agent its own cloud computer is the right bet imo 👏 the async close-the-tab flow is nice. hows reliability on longer tasks?

We stress-tested Clark on original mathematics research — specifically, an open gap in our Riemann Hypothesis program at MathLab (mathlab.quantiterate.com), a proof verification platform with an adversarial War Room.

We gave Clark a five-step forward path and told him to implement it. He produced two compilable LaTeX files: an unconditional lemma with correct proofs and a conditional strip theorem with five named hypotheses. When we critiqued structural defects in v1.0, he absorbed every point and produced a tighter v1.1 with a changelog. Rating: 7–8/10.

Your three questions:

1. First task: we went straight to the hardest thing we could think of. Most honest test.

2. "Own cloud computer" comes through — getting back compilable LaTeX with correct theorem numbering and cross-references is qualitatively different from chat.

3. Where we'd hesitate: autonomous long-horizon work. Clark is an excellent decomposer — he factors hard problems into clean sub-problems. But when the difficulty is a tension that doesn't decompose further, he'll keep refining the scaffold without resolving it. The human critique loop is what made him improve. Infrastructure, not engine. We'll use him again.

I'd be curious to know things with which this would help me out that a Claude Scheduler with cowork cannot.

P.S. - really like the innovation with AI agents that's currently happening

Congrats on the launch. I like that it's async, you send a task and leave instead of babysitting the agent the whole way. My one nervous question before handing an agent a real repo: when Clark Code patches something while I'm gone, is it scoped to a branch or PR I get to review, or can it land straight on main? Trying to picture the blast radius before I point it at anything that matters.