I Added a Pro Plan to OpenClawCloud Because Heavy Runs Hit Boring Limits First

try { if(localStorage) { let currentUser = localStorage.getItem('current_user'); if (currentUser) { currentUser = JSON.parse(currentUser); if (currentUser.id === 3766706) { document.getElementById('article-show-container').classList.add('current-user-is-article-author'); } } } } catch (e) { console.error(e); } João Pedro Silva Setas Posted on Apr 28 I Added a Pro Plan to OpenClawCloud Because Heavy Runs Hit Boring Limits First I Added a Pro Plan to OpenClawCloud Because Heavy Runs Hit Boring Limits First The first limit heavier AI workloads hit is usually not intelligence. It is the boring stuff. CPU. RAM. Disk. And a better way to see what is about to run before you let it go. That is why I added a Pro plan to OpenClawCloud. It is live at $29/month and keeps the same basic starting point as Hobby, but adds more headroom where it actually matters: 4 vCPU 8GB RAM 160GB SSD storage Run Preview before execution Instance Activity Log Priority support Hobby still makes sense when you are exploring, testing, or just getting your first setup running. Pro is for the point where that smaller box stops being comfortable. I wanted the step up to be practical, not ornamental. More room to run. More storage for longer-lived workspaces and heavier tasks. Better visibility into what is about to happen and what just happened. The broader OpenClawCloud direction I care about is still governed execution: clearer review surfaces, better failure inspection, and less dependence on one provider's policy decisions. Useful product work usually starts with the boring constraints first. If the runtime does not have enough headroom, the bigger thesis does not matter yet. So this is the current shape of the product: Hobby for smaller setups and exploration Pro for heavier runs that need more compute, more storage, and better visibility That feels like the right next step for where OpenClawCloud is now. If you are already past the point where the smallest plan feels comfortable, Pro is live. What becomes the first bottleneck for you when AI workloads get heavier: CPU, memory, storage, or visibility into each run? Top comments (0) Subscribe Personal Trusted User Create template Templates let you quickly answer FAQs or store snippets for re-use. Submit Preview Dismiss Code of Conduct • Report abuse Are you sure you want to hide this comment? It will become hidden in your post, but will still be visible via the comment's permalink. Hide child comments as well Confirm For further actions, you may consider blocking this person and/or reporting abuse

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